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tokushima vortis | https://en.wikipedia.org/wiki/Tokushima_Vortis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1276456-1.html.csv | comparative | attendance was higher during the 2010 season than the 2009 season . | {'row_1': '6', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2010 .', 'tostr': 'filter_eq { all_rows ; season ; 2010 }'}, 'attendance / g'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season ; 2010 } ; attendance / g }', 'tointer': 'select the rows whose season record fuzzily matches to 2010 . take the attendance / g record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2009'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose season record fuzzily matches to 2009 .', 'tostr': 'filter_eq { all_rows ; season ; 2009 }'}, 'attendance / g'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; season ; 2009 } ; attendance / g }', 'tointer': 'select the rows whose season record fuzzily matches to 2009 . take the attendance / g record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; season ; 2010 } ; attendance / g } ; hop { filter_eq { all_rows ; season ; 2009 } ; attendance / g } } = true', 'tointer': 'select the rows whose season record fuzzily matches to 2010 . take the attendance / g record of this row . select the rows whose season record fuzzily matches to 2009 . take the attendance / g record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; season ; 2010 } ; attendance / g } ; hop { filter_eq { all_rows ; season ; 2009 } ; attendance / g } } = true | select the rows whose season record fuzzily matches to 2010 . take the attendance / g record of this row . select the rows whose season record fuzzily matches to 2009 . take the attendance / g record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'season_7': 7, '2010_8': 8, 'attendance / g_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2009_12': 12, 'attendance / g_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'season_7': 'season', '2010_8': '2010', 'attendance / g_9': 'attendance / g', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2009_12': '2009', 'attendance / g_13': 'attendance / g'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2010_8': [0], 'attendance / g_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2009_12': [1], 'attendance / g_13': [3]} | ['season', 'div', 'tms', 'pos', 'attendance / g', 'j league cup', "emperor 's cup"] | [['2005', 'j2', '12', '9', '4366', '-', '4th round'], ['2006', 'j2', '13', '13', '3477', '-', '4th round'], ['2007', 'j2', '13', '13', '3289', '-', '4th round'], ['2008', 'j2', '15', '15', '3862', '-', '3rd round'], ['2009', 'j2', '18', '9', '4073', '-', '2nd round'], ['2010', 'j2', '19', '8', '4614', '-', '3rd round']] |
2004 scottish claymores season | https://en.wikipedia.org/wiki/2004_Scottish_Claymores_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29679510-2.html.csv | ordinal | during the 2004 scottish claymores season , the 2nd largest attendance occurred on april 10th . | {'row': '2', 'col': '8', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'saturday , april 10', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}, 'saturday , april 10'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; saturday , april 10 } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the date record of this row is saturday , april 10 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; saturday , april 10 } = true | select the row whose attendance record of all rows is 2nd maximum . the date record of this row is saturday , april 10 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'saturday , april 10_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'saturday , april 10_8': 'saturday , april 10'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'saturday , april 10_8': [2]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'sunday , april 4', '4:00 pm', 'berlin thunder', 'l 14 - 20', '0 - 1', 'olympic stadium', '14257'], ['2', 'saturday , april 10', '7:00 pm', 'rhein fire', 'l 3 - 31', '0 - 2', 'arena aufschalke', '17176'], ['3', 'sunday , april 18', '2:00 pm', 'amsterdam admirals', 'l 0 - 3', '0 - 3', 'hampden park', '10971'], ['4', 'saturday , april 24', '7:00 pm', 'cologne centurions', 'l 3 - 17', '0 - 4', 'rheinenergiestadion', '8761'], ['5', 'sunday , may 2', '2:00 pm', 'rhein fire', 'w 13 - 12', '1 - 4', 'hampden park', '9165'], ['6', 'sunday , may 9', '2:00 pm', 'frankfurt galaxy', 'l 13 - 15', '1 - 5', 'hampden park', '9017'], ['7', 'sunday , may 16', '4:00 pm', 'frankfurt galaxy', 'l 24 - 27', '1 - 6', 'waldstadion', '26879'], ['8', 'friday , may 21', '8:00 pm', 'amsterdam admirals', 'w 19 - 17', '2 - 6', 'amsterdam arena', '10738'], ['9', 'saturday , may 29', '2:00 pm', 'berlin thunder', 'l 19 - 27', '2 - 7', 'hampden park', '9153']] |
mark van bommel | https://en.wikipedia.org/wiki/Mark_van_Bommel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1886415-1.html.csv | count | there were four friendly matches played by mark van bommel . | {'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly .', 'tostr': 'filter_eq { all_rows ; competition ; friendly }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; competition ; friendly } }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; competition ; friendly } } ; 4 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; competition ; friendly } } ; 4 } = true | select the rows whose competition record fuzzily matches to friendly . 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, 'competition_5': 5, 'friendly_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', 'competition_5': 'competition', 'friendly_6': 'friendly', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly_6': [0], '4_7': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['14 march 2001', 'mini estadi , barcelona , spain', '0 - 5', '0 - 5', '2002 wcq'], ['15 august 2001', 'white hart lane , london , england', '0 - 1', '0 - 2', 'friendly'], ['5 september 2001', 'philips stadion , eindhoven , netherlands', '2 - 0', '5 - 0', '2002 wcq'], ['5 september 2001', 'philips stadion , eindhoven , netherlands', '4 - 0', '5 - 0', '2002 wcq'], ['2 april 2003', 'sheriff stadium , tiraspol , moldova', '1 - 2', '1 - 2', 'euro 2004 q'], ['18 august 2004', 'råsunda stadium , solna , sweden', '1 - 2', '2 - 2', 'friendly'], ['3 september 2004', 'galgenwaard stadium , utrecht , netherlands', '1 - 0', '3 - 0', 'friendly'], ['15 october 2008', 'ullevaal stadion , oslo , norway', '0 - 1', '0 - 1', '2010 wcq'], ['6 june 2009', 'laugardalsvöllur , reykjavík , iceland', '0 - 2', '1 - 2', '2010 wcq'], ['5 june 2010', 'amsterdam arena , amsterdam , netherlands', '4 - 1', '6 - 1', 'friendly']] |
russian football premier league | https://en.wikipedia.org/wiki/Russian_Football_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1167698-1.html.csv | ordinal | alania vladikavkaz was the third team to be runner-up in the russian football premier league . | {'row': '3', 'col': '1', 'order': '3', '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', 'season', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; season ; 3 }'}, 'runner - up'], 'result': 'alania vladikavkaz', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; season ; 3 } ; runner - up }'}, 'alania vladikavkaz'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; season ; 3 } ; runner - up } ; alania vladikavkaz } = true', 'tointer': 'select the row whose season record of all rows is 3rd minimum . the runner - up record of this row is alania vladikavkaz .'} | eq { hop { nth_argmin { all_rows ; season ; 3 } ; runner - up } ; alania vladikavkaz } = true | select the row whose season record of all rows is 3rd minimum . the runner - up record of this row is alania vladikavkaz . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'season_5': 5, '3_6': 6, 'runner - up_7': 7, 'alania vladikavkaz_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', 'season_5': 'season', '3_6': '3', 'runner - up_7': 'runner - up', 'alania vladikavkaz_8': 'alania vladikavkaz'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'season_5': [0], '3_6': [0], 'runner - up_7': [1], 'alania vladikavkaz_8': [2]} | ['season', 'champion', 'runner - up', 'third place', 'top scorer'] | [['1994', 'spartak moscow ( 3 )', 'dynamo moscow', 'lokomotiv moscow', 'igor simutenkov ( dinamo moscow , 21 goals )'], ['1995', 'alania vladikavkaz', 'lokomotiv moscow', 'spartak moscow', 'oleg veretennikov ( rotor volgograd , 25 goals )'], ['1996', 'spartak moscow ( 4 )', 'alania vladikavkaz', 'rotor volgograd', 'aleksandr maslov ( rostselmash , 23 goals )'], ['1997', 'spartak moscow ( 5 )', 'rotor volgograd', 'dynamo moscow', 'oleg veretennikov ( rotor volgograd , 22 goals )'], ['1998', 'spartak moscow ( 6 )', 'cska moscow', 'lokomotiv moscow', 'oleg veretennikov ( rotor volgograd , 22 goals )'], ['1999', 'spartak moscow ( 7 )', 'lokomotiv moscow', 'cska moscow', 'georgi demetradze ( alania vladikavkaz , 21 goals )'], ['2000', 'spartak moscow ( 8 )', 'lokomotiv moscow', 'torpedo moscow', 'dmitri loskov ( lokomotiv moscow , 18 goals )'], ['2001', 'spartak moscow ( 9 )', 'lokomotiv moscow', 'zenit saint petersburg', 'dmitri vyazmikin ( torpedo moscow , 18 goals )'], ['2003', 'cska moscow', 'zenit saint petersburg', 'rubin kazan', 'dmitri loskov ( lokomotiv moscow , 14 goals )'], ['2005', 'cska moscow ( 2 )', 'spartak moscow', 'lokomotiv moscow', 'dmitri kirichenko ( fc moscow , 14 goals )'], ['2006', 'cska moscow ( 3 )', 'spartak moscow', 'lokomotiv moscow', 'roman pavlyuchenko ( spartak moscow , 18 goals )'], ['2008', 'rubin kazan', 'cska moscow', 'dynamo moscow', 'vã ¡ gner love ( cska moscow , 20 goals )'], ['2009', 'rubin kazan ( 2 )', 'spartak moscow', 'zenit saint petersburg', 'welliton ( spartak moscow , 21 goals )'], ['2010', 'zenit saint petersburg ( 2 )', 'cska moscow', 'rubin kazan', 'welliton ( spartak moscow , 19 goals )']] |
city of angels ( musical ) | https://en.wikipedia.org/wiki/City_of_Angels_%28musical%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1773562-3.html.csv | unique | city of angels ( musical ) only has the result of a win once . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'won', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to won .', 'tostr': 'filter_eq { all_rows ; result ; won }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; won } } = true', 'tointer': 'select the rows whose result record fuzzily matches to won . there is only one such row in the table .'} | only { filter_eq { all_rows ; result ; won } } = true | select the rows whose result record fuzzily matches to won . 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, 'result_4': 4, 'won_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'result_4': 'result', 'won_5': 'won'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'result_4': [0], 'won_5': [0]} | ['year', 'award', 'category', 'nominee', 'result'] | [['1994', 'laurence olivier award', 'best new musical', 'best new musical', 'won'], ['1994', 'laurence olivier award', 'best actor in a musical', 'roger allam', 'nominated'], ['1994', 'laurence olivier award', 'best actress in a musical', 'haydn gwynne', 'nominated'], ['1994', 'laurence olivier award', 'best performance in a supporting role in a musical', 'henry goodman', 'nominated'], ['1994', 'laurence olivier award', 'best director of a musical', 'michael blakemore', 'nominated']] |
1925 vfl season | https://en.wikipedia.org/wiki/1925_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746200-17.html.csv | count | there were 6 game venues used during the 1925 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'] | [['melbourne', '9.9 ( 63 )', 'richmond', '2.12 ( 24 )', 'mcg', '16989', '12 september 1925'], ['hawthorn', '7.13 ( 55 )', 'north melbourne', '4.6 ( 30 )', 'glenferrie oval', '8000', '12 september 1925'], ['essendon', '10.7 ( 67 )', 'st kilda', '8.10 ( 58 )', 'windy hill', '15000', '12 september 1925'], ['geelong', '14.16 ( 100 )', 'footscray', '9.7 ( 61 )', 'corio oval', '10800', '12 september 1925'], ['south melbourne', '4.6 ( 30 )', 'collingwood', '14.11 ( 95 )', 'lake oval', '12000', '12 september 1925'], ['fitzroy', '7.24 ( 66 )', 'carlton', '9.10 ( 64 )', 'brunswick street oval', '20000', '12 september 1925']] |
comparison of java remote desktop projects | https://en.wikipedia.org/wiki/Comparison_of_Java_Remote_Desktop_projects | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18418837-1.html.csv | superlative | the last date rmi technology was used on java remote desktop projects was september 16 , 2009 . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'rmi'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'technology', 'rmi'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; technology ; rmi }', 'tointer': 'select the rows whose technology record fuzzily matches to rmi .'}, 'date'], 'result': 'september 16 , 2009', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; technology ; rmi } ; date }', 'tointer': 'select the rows whose technology record fuzzily matches to rmi . the maximum date record of these rows is september 16 , 2009 .'}, 'september 16 , 2009'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; technology ; rmi } ; date } ; september 16 , 2009 } = true', 'tointer': 'select the rows whose technology record fuzzily matches to rmi . the maximum date record of these rows is september 16 , 2009 .'} | eq { max { filter_eq { all_rows ; technology ; rmi } ; date } ; september 16 , 2009 } = true | select the rows whose technology record fuzzily matches to rmi . the maximum date record of these rows is september 16 , 2009 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'technology_5': 5, 'rmi_6': 6, 'date_7': 7, 'september 16 , 2009_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'technology_5': 'technology', 'rmi_6': 'rmi', 'date_7': 'date', 'september 16 , 2009_8': 'september 16 , 2009'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'technology_5': [0], 'rmi_6': [0], 'date_7': [1], 'september 16 , 2009_8': [2]} | ['project', 'license', 'date', 'protocol', 'technology', 'server', 'client', 'web client', 'multiple sessions', 'encryption', 'authentication', 'data compression', 'image quality', 'color quality', 'file transfer', 'clipboard transfer', 'chat', 'relay', 'http tunnel', 'proxy'] | [['ajax remote desktop viewer ( ajaxrd )', 'proprietary', 'june 24 , 2006', 'proprietary', 'socket', '✓', 'x', '✓', '✓', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'], ['dayon !', 'gpl', 'january 3 , 2009', 'proprietary', 'socket', '✓', '✓', 'x', 'x', 'x', 'x', '✓', '✓', '✓', 'x', 'x', 'x', 'x', 'x', 'x'], ['goto servers vnc java server ( gsvncj )', 'proprietary', 'february 17 , 2008', 'rdp , rfb ( vnc )', 'socket', '✓', 'x', 'x', 'x', 'des', '✓', 'x', '✓', '✓', 'x', 'x', 'x', 'x', 'x', 'x'], ['java remote control', 'mit', 'november 14 , 2007', 'proprietary', 'socket', '✓', '✓', 'x', 'x', 'x', '✓', '✓', 'x', 'x', 'x', 'x', 'x', '✓', '✓', '✓'], ['java remote desktop ( jrdesktop )', 'gpl', 'september 16 , 2009', 'proprietary', 'rmi', '✓', '✓', '✓', '✓', 'ssl', '✓', 'x', '✓', '✓', '✓', '✓', 'x', 'x', 'x', '✓'], ['jxta remote desktop', 'apache license', 'february 15 , 2005', 'proprietary', 'socket', '✓', '✓', 'x', '✓', 'x', '✓', 'x', '✓', 'x', '✓', 'x', '✓', '✓', '✓', '✓'], ['j remote desktop', 'gpl', 'may 25 , 2006', 'proprietary', 'rmi', '✓', '✓', 'x', 'x', 'x', '✓', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'], ['n - central', 'commercial', 'may 2011', 'ssh , udp , http', 'socket', '✓', '✓', '✓', '✓', '✓', '✓', 'x', '✓', '✓', '✓', 'x', '✓', '✓', '✓', '✓'], ['properjavardp', 'gpl', 'may 15 , 2007', 'rdp', 'socket', 'x', '✓', 'x', 'x', 'rc4', '✓', 'x', 'x', '✓', 'x', '✓', 'x', 'x', 'x', 'x'], ['webrdp', 'proprietary', 'june 17 , 2010', 'rdp', 'socket', 'html5 gateway', '✓', '✓', '✓', 'rc4 / ssl', '✓', '✓', '✓', '✓', 'x', '✓', 'x', '✓', '✓', '✓'], ['hoblink jwt', 'proprietary', 'february 6 , 2010', 'rdp', 'socket', 'x', '✓', '✓', '✓', 'ssl', '✓', '✓', '✓', '✓', '✓', '✓', 'x', '✓', '✓', '✓'], ['robo', 'gpl', 'november 21 , 2002', 'proprietary', 'socket', '✓', '✓', '✓', '✓', 'ssl', '✓', '✓', 'x', '✓', 'x', 'x', 'x', 'x', '✓', 'x'], ['vnc viewer', 'proprietary', '2004', 'rfb ( vnc )', 'socket', 'x', '✓', 'x', '✓', 'x', '✓', 'x', '✓', '✓', 'x', '✓', 'x', 'x', 'x', 'x'], ['vedivi vpn', 'proprietary', '2008', 'proprietary', 'socket', '✓', '✓', '✓', '✓', 'ssl', '✓', '✓', '✓', '✓', '✓', '✓', 'x', '✓', '✓', '✓'], ['wificheema', 'proprietary', '2010', 'proprietary', 'socket', '✓', '✓', '✓', '✓', 'ssl', '✓', '✓', '✓', '✓', 'x', 'x', '✓', 'x', 'x', 'x'], ['project', 'license', 'date', 'protocol', 'technology', 'server', 'client', 'web client', 'multiple sessions', 'encryption', 'authentication', 'data compression', 'image quality', 'color quality', 'file transfer', 'clipboard transfer', 'chat', 'relay', 'http tunnel', 'proxy']] |
merom ( microprocessor ) | https://en.wikipedia.org/wiki/Merom_%28microprocessor%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24099916-1.html.csv | ordinal | of the merom microprocessors , the mobile core 2 extreme had the most tdp at 44w . | {'row': '5', 'col': '7', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'tdp', '1'], 'result': '44 w', 'ind': 0, 'tostr': 'nth_max { all_rows ; tdp ; 1 }', 'tointer': 'the 1st maximum tdp record of all rows is 44 w .'}, '44 w'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; tdp ; 1 } ; 44 w }', 'tointer': 'the 1st maximum tdp record of all rows is 44 w .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'tdp', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; tdp ; 1 }'}, 'brand name'], 'result': 'mobile core 2 extreme', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; tdp ; 1 } ; brand name }'}, 'mobile core 2 extreme'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; tdp ; 1 } ; brand name } ; mobile core 2 extreme }', 'tointer': 'the brand name record of the row with 1st maximum tdp record is mobile core 2 extreme .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; tdp ; 1 } ; 44 w } ; eq { hop { nth_argmax { all_rows ; tdp ; 1 } ; brand name } ; mobile core 2 extreme } } = true', 'tointer': 'the 1st maximum tdp record of all rows is 44 w . the brand name record of the row with 1st maximum tdp record is mobile core 2 extreme .'} | and { eq { nth_max { all_rows ; tdp ; 1 } ; 44 w } ; eq { hop { nth_argmax { all_rows ; tdp ; 1 } ; brand name } ; mobile core 2 extreme } } = true | the 1st maximum tdp record of all rows is 44 w . the brand name record of the row with 1st maximum tdp record is mobile core 2 extreme . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'tdp_8': 8, '1_9': 9, '44 w_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'tdp_12': 12, '1_13': 13, 'brand name_14': 14, 'mobile core 2 extreme_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'tdp_8': 'tdp', '1_9': '1', '44 w_10': '44 w', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'tdp_12': 'tdp', '1_13': '1', 'brand name_14': 'brand name', 'mobile core 2 extreme_15': 'mobile core 2 extreme'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'tdp_8': [0], '1_9': [0], '44 w_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'tdp_12': [2], '1_13': [2], 'brand name_14': [3], 'mobile core 2 extreme_15': [4]} | ['processor', 'brand name', 'model ( list )', 'cores', 'l2 cache', 'socket', 'tdp'] | [['merom - l', 'mobile core 2 solo', 'u2xxx', '1', '2 mib', 'bga479', '5.5 w'], ['merom - 2 m', 'mobile core 2 duo', 'u7xxx', '2', '2 mib', 'bga479', '10 w'], ['merom', 'mobile core 2 duo', 'l7xxx', '2', '4 mib', 'bga479', '17 w'], ['merom merom - 2 m', 'mobile core 2 duo', 't5xxx t7xxx', '2', '2 - 4 mib', 'socket m socket p bga479', '35 w'], ['merom', 'mobile core 2 extreme', 'x7xxx', '2', '4 mib', 'socket p', '44 w'], ['merom', 'celeron m', '5x0', '1', '512 kib', 'socket m socket p', '30 w'], ['merom - l', 'celeron m', '5x0', '1', '512 kib', 'socket m socket p', '27 w'], ['merom - 2 m', 'celeron m', '5x5', '1', '1024 kib', 'socket p', '31 w'], ['merom - l', 'celeron m', '5x3', '1', '512 - 1024 kib', 'bga479', '5.5 - 10 w'], ['merom - 2 m', 'celeron dual - core', 't1xxx', '2', '512 - 1024 kib', 'socket p', '35 w']] |
1986 - 87 segunda división | https://en.wikipedia.org/wiki/1986%E2%80%9387_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12109851-2.html.csv | count | 4 clubs in the 1986 - 87 segunda división had 13 losses . | {'scope': 'all', 'criterion': 'equal', 'value': '13', 'result': '4', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'losses', '13'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose losses record is equal to 13 .', 'tostr': 'filter_eq { all_rows ; losses ; 13 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; losses ; 13 } }', 'tointer': 'select the rows whose losses record is equal to 13 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; losses ; 13 } } ; 4 } = true', 'tointer': 'select the rows whose losses record is equal to 13 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; losses ; 13 } } ; 4 } = true | select the rows whose losses record is equal to 13 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'losses_5': 5, '13_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'losses_5': 'losses', '13_6': '13', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'losses_5': [0], '13_6': [0], '4_7': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'valencia cf', '34', '46 + 12', '19', '8', '7', '53', '26', '+ 27'], ['2', 'deportivo de la coruña', '34', '43 + 9', '16', '11', '7', '46', '33', '+ 13'], ['3', 'cd logroñés', '34', '41 + 7', '16', '9', '9', '46', '33', '+ 13'], ['4', 'celta de vigo', '34', '40 + 6', '17', '6', '11', '56', '35', '+ 21'], ['5', 'recreativo de huelva', '34', '39 + 5', '18', '3', '13', '53', '44', '+ 9'], ['6', 'sestao', '34', '38 + 4', '13', '12', '9', '38', '23', '+ 15'], ['7', 'elche cf', '34', '36 + 2', '12', '12', '10', '31', '28', '+ 3'], ['8', 'rayo vallecano', '34', '35 + 1', '10', '15', '9', '28', '28', '0'], ['9', 'bilbao athletic', '34', '35 + 1', '12', '11', '11', '51', '54', '- 3'], ['10', 'cd castellón', '34', '34', '13', '8', '13', '38', '42', '- 4'], ['11', 'hércules cf', '34', '32 - 2', '12', '8', '14', '38', '43', '- 5'], ['12', 'cd málaga', '34', '32 - 2', '10', '12', '12', '43', '39', '+ 4'], ['13', 'barcelona atlètic', '34', '32 - 2', '11', '10', '13', '42', '46', '- 4'], ['14', 'real oviedo', '34', '30 - 4', '9', '12', '13', '33', '46', '- 13'], ['15', 'ue figueres', '34', '29 - 5', '9', '11', '14', '39', '40', '- 1'], ['16', 'cartagena fc', '34', '27 - 7', '7', '13', '14', '34', '51', '- 17'], ['17', 'castilla cf', '34', '24 - 10', '7', '10', '17', '30', '51', '- 21'], ['18', 'jerez deportivo', '34', '19 - 15', '4', '11', '19', '21', '58', '- 37']] |
28th united states congress | https://en.wikipedia.org/wiki/28th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-225206-3.html.csv | majority | the majority of 28th united states congress seats that were vacated were filled during the term . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'elected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date of successors formal installation', 'elected'], 'result': True, 'ind': 0, 'tointer': 'for the date of successors formal installation records of all rows , most of them fuzzily match to elected .', 'tostr': 'most_eq { all_rows ; date of successors formal installation ; elected } = true'} | most_eq { all_rows ; date of successors formal installation ; elected } = true | for the date of successors formal installation records of all rows , most of them fuzzily match to elected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date of successors formal installation_3': 3, 'elected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date of successors formal installation_3': 'date of successors formal installation', 'elected_4': 'elected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date of successors formal installation_3': [0], 'elected_4': [0]} | ['state ( class )', 'vacator', 'reason for change', 'successor', 'date of successors formal installation'] | [['tennessee ( 2 )', 'vacant', 'failure to elect', 'spencer jarnagin ( w )', 'elected october 17 , 1843'], ['maine ( 1 )', 'vacant', 'rep reuel williams resigned in previous congress', 'john fairfield ( d )', 'elected december 4 , 1843'], ['illinois ( 2 )', 'samuel mcroberts ( d )', 'died march 27 , 1843', 'james semple ( d )', 'elected december 4 , 1843'], ['missouri ( 3 )', 'lewis f linn ( d )', 'died october 3 , 1843', 'david r atchison ( d )', 'elected december 14 , 1843'], ['rhode island ( 1 )', 'william sprague ( d )', 'resigned january 17 , 1844', 'john b francis ( lo )', 'elected january 25 , 1844'], ['arkansas ( 2 )', 'william s fulton ( d )', 'died august 15 , 1844', 'chester ashley ( d )', 'elected november 8 , 1844'], ['new york ( 3 )', 'henry a foster ( d )', 'successor elected january 27 , 1845', 'john a dix ( d )', 'elected january 27 , 1845'], ['south carolina ( 2 )', 'daniel e huger ( d )', 'resigned march 3 , 1845', 'vacant', 'not filled this term'], ['florida ( 1 )', 'vacant', 'florida admitted to the union march 3 , 1845', 'vacant', 'not filled this term']] |
2010 - 11 detroit pistons season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Detroit_Pistons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27755603-11.html.csv | count | greg monroe had the high rebounds 4 times in the 2010-11 detroit pistons season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'greg monroe', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'greg monroe'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high rebounds record fuzzily matches to greg monroe .', 'tostr': 'filter_eq { all_rows ; high rebounds ; greg monroe }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high rebounds ; greg monroe } }', 'tointer': 'select the rows whose high rebounds record fuzzily matches to greg monroe . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high rebounds ; greg monroe } } ; 4 } = true', 'tointer': 'select the rows whose high rebounds record fuzzily matches to greg monroe . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; high rebounds ; greg monroe } } ; 4 } = true | select the rows whose high rebounds record fuzzily matches to greg monroe . 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, 'high rebounds_5': 5, 'greg monroe_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', 'high rebounds_5': 'high rebounds', 'greg monroe_6': 'greg monroe', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'greg monroe_6': [0], '4_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['75', 'april 1', 'chicago', 'l 96 - 101 ( ot )', 'richard hamilton ( 30 )', 'greg monroe ( 9 )', 'tayshaun prince ( 6 )', 'the palace of auburn hills 22076', '26 - 49'], ['77', 'april 5', 'washington', 'l 105 - 107 ( ot )', 'greg monroe ( 22 )', 'greg monroe ( 14 )', 'tracy mcgrady ( 6 )', 'verizon center 18131', '26 - 51'], ['78', 'april 6', 'new jersey', 'w 116 - 109 ( ot )', 'richard hamilton ( 25 )', 'greg monroe ( 10 )', 'rodney stuckey ( 10 )', 'the palace of auburn hills 14554', '27 - 51'], ['79', 'april 8', 'milwaukee', 'w 110 - 100 ( ot )', 'chris wilcox ( 27 )', 'chris wilcox ( 13 )', 'richard hamilton ( 6 )', 'the palace of auburn hills 16266', '28 - 51'], ['80', 'april 10', 'charlotte', 'w 112 - 101 ( ot )', 'rodney stuckey ( 24 )', 'greg monroe ( 9 )', 'rodney stuckey ( 11 )', 'time warner cable arena 16234', '29 - 51'], ['81', 'april 11', 'cleveland', 'l 101 - 110 ( ot )', 'rodney stuckey ( 29 )', 'jason maxiell ( 14 )', 'rodney stuckey ( 14 )', 'the palace of auburn hills 15589', '29 - 52']] |
chiefs - raiders rivalry | https://en.wikipedia.org/wiki/Chiefs%E2%80%93Raiders_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11840325-8.html.csv | majority | between 2010 and 2013 , kansas city lost most of their games against oakland . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'kansas city chiefs', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'loser', 'kansas city chiefs'], 'result': True, 'ind': 0, 'tointer': 'for the loser records of all rows , most of them fuzzily match to kansas city chiefs .', 'tostr': 'most_eq { all_rows ; loser ; kansas city chiefs } = true'} | most_eq { all_rows ; loser ; kansas city chiefs } = true | for the loser records of all rows , most of them fuzzily match to kansas city chiefs . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'loser_3': 3, 'kansas city chiefs_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'loser_3': 'loser', 'kansas city chiefs_4': 'kansas city chiefs'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'loser_3': [0], 'kansas city chiefs_4': [0]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['2010', 'november 7', 'oakland raiders', '23 - 20 ( ot )', 'kansas city chiefs', 'oakland - alameda county coliseum'], ['2010', 'january 2 ( 2011 )', 'oakland raiders', '31 - 10', 'kansas city chiefs', 'arrowhead stadium'], ['2011', 'october 23', 'kansas city chiefs', '28 - 0', 'oakland raiders', 'oco coliseum'], ['2011', 'december 24', 'oakland raiders', '16 - 13 ( ot )', 'kansas city chiefs', 'arrowhead stadium'], ['2012', 'october 28', 'oakland raiders', '26 - 16', 'kansas city chiefs', 'arrowhead stadium'], ['2012', 'december 16', 'oakland raiders', '15 - 0', 'kansas city chiefs', 'oco coliseum'], ['2013', 'october 13', 'kansas city chiefs', '24 - 7', 'oakland raiders', 'arrowhead stadium']] |
list of sumo record holders | https://en.wikipedia.org/wiki/List_of_sumo_record_holders | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634218-20.html.csv | aggregation | the average number of tournaments for the sumo record holders is 11.46 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '11.46', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'tournaments'], 'result': '11.46', 'ind': 0, 'tostr': 'avg { all_rows ; tournaments }'}, '11.46'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; tournaments } ; 11.46 } = true', 'tointer': 'the average of the tournaments record of all rows is 11.46 .'} | round_eq { avg { all_rows ; tournaments } ; 11.46 } = true | the average of the tournaments record of all rows is 11.46 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'tournaments_4': 4, '11.46_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'tournaments_4': 'tournaments', '11.46_5': '11.46'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'tournaments_4': [0], '11.46_5': [1]} | ['name', 'tournaments', 'pro debut', 'top division debut', 'highest rank'] | [['jōkōryū', '9', 'may 2011', 'november 2012', 'maegashira 7'], ['ōsunaarashi', '10', 'march 2012', 'november 2013', 'maegashira 15'], ['kotoōshū', '11', 'november 2002', 'september 2004', 'ōzeki'], ['aran', '11', 'january 2007', 'november 2008', 'sekiwake'], ['itai', '12', 'september 1978', 'september 1980', 'komusubi'], ['konishiki', '12', 'july 1982', 'july 1984', 'ōzeki'], ['tochiazuma ii', '12', 'november 1994', 'november 1996', 'ōzeki'], ['asashōryū', '12', 'january 1999', 'january 2001', 'yokozuna'], ['tokitenkū', '12', 'july 2002', 'july 2004', 'komusubi'], ['yoshikaze', '12', 'january 2004', 'january 2006', 'maegashira 1'], ['baruto', '12', 'may 2004', 'may 2006', 'ōzeki'], ['sakaizawa', '12', 'march 2006', 'march 2008', 'maegashira 15'], ['yamamotoyama', '12', 'january 2007', 'january 2009', 'maegashira 9']] |
the whole thing 's started | https://en.wikipedia.org/wiki/The_Whole_Thing%27s_Started | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17071146-1.html.csv | superlative | the longest 7 " single release of the album the whole thing 's started is empty pages . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'length'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; length }'}, 'tracks'], 'result': 'empty pages', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; length } ; tracks }'}, 'empty pages'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; length } ; tracks } ; empty pages } = true', 'tointer': 'select the row whose length record of all rows is maximum . the tracks record of this row is empty pages .'} | eq { hop { argmax { all_rows ; length } ; tracks } ; empty pages } = true | select the row whose length record of all rows is maximum . the tracks record of this row is empty pages . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, 'tracks_6': 6, 'empty pages_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'length_5': 'length', 'tracks_6': 'tracks', 'empty pages_7': 'empty pages'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], 'tracks_6': [1], 'empty pages_7': [2]} | ['date', 'tracks', 'length', 'label', 'catalog'] | [['1977', 'do what you do', '3:47', 'cbs', 'ba 222304'], ['1977', "it 's automatic", '2:57', 'cbs', 'ba 222304'], ['1977', "that 's how the whole thing started", '4:03', 'cbs', 'ba 222325'], ['1977', "there 's nothing i can do", '3:38', 'cbs', 'ba 222325'], ['1978', 'do it again', '3:35', 'columbia', 'c4 - 8217'], ['1978', 'empty pages', '4:20', 'columbia', 'c4 - 8217']] |
list of mr. belvedere episodes | https://en.wikipedia.org/wiki/List_of_Mr._Belvedere_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20967430-3.html.csv | majority | all of the mr. belvedere episodes were directed by noam pitlik . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'noam pitlik', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'directed by', 'noam pitlik'], 'result': True, 'ind': 0, 'tointer': 'for the directed by records of all rows , all of them fuzzily match to noam pitlik .', 'tostr': 'all_eq { all_rows ; directed by ; noam pitlik } = true'} | all_eq { all_rows ; directed by ; noam pitlik } = true | for the directed by records of all rows , all of them fuzzily match to noam pitlik . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'directed by_3': 3, 'noam pitlik_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'directed by_3': 'directed by', 'noam pitlik_4': 'noam pitlik'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'directed by_3': [0], 'noam pitlik_4': [0]} | ['ep', 'season', 'title', 'directed by', 'written by', 'original air date', 'prod code'] | [['30', '1', 'the thief', 'noam pitlik', 'jeffrey ferro & fredric weiss', 'september 26 , 1986', '5a03'], ['31', '2', 'grandma', 'noam pitlik', 'frank dungan & jeff stein & tony sheehan', 'october 03 , 1986', '5a04'], ['32', '3', 'debut', 'noam pitlik', 'fredric weiss & jeffrey ferro', 'october 17 , 1986', '5a05'], ['33', '4', "kevin 's date", 'noam pitlik', 'tony sheehan', 'october 24 , 1986', '5a07'], ['34', '5', 'halloween', 'noam pitlik', 'jeffrey ferro & fredric weiss', 'october 31 , 1986', '5a08'], ['35', '6', 'deportation : part 1', 'noam pitlik', 'frank dungan & jeff stein & tony sheehan', 'november 07 , 1986', '5a01'], ['36', '7', 'deportation : part 2', 'noam pitlik', 'frank dungan & jeff stein & tony sheehan', 'november 14 , 1986', '5a02'], ['37', '8', 'reunion', 'noam pitlik', 'frank dungan & jeff stein', 'november 21 , 1986', '5a10'], ['38', '9', 'the spelling bee', 'noam pitlik', 'fredric weiss & jeffrey ferro', 'december 05 , 1986', '5a11'], ['39', '10', 'pills', 'noam pitlik', 'gene braunstein & bob perlow', 'december 12 , 1986', '5a09'], ['40', '11', 'the ticket', 'noam pitlik', 'tony sheehan', 'january 30 , 1987', '5a12'], ['41', '12', 'college bound', 'noam pitlik', 'jeffrey ferro & fredric weiss', 'january 09 , 1987', '5a13'], ['42', '13', 'inky', 'noam pitlik', 'frank dungan & jeff stein', 'january 16 , 1987', '5a14'], ['43', '14', 'jobless', 'noam pitlik', 'frank dungan & jeff stein & tony sheehan', 'january 23 , 1987', '5a15'], ['44', '15', 'the crush', 'noam pitlik', 'fredric weiss & jeffrey ferro', 'february 06 , 1987', '5a16'], ['46', '17', 'the cadet', 'noam pitlik', 'jeffrey ferro & fredric weiss', 'february 20 , 1987', '5a18'], ['47', '18', "kevin 's older woman", 'noam pitlik', 'frank dungan & jeff stein & tony sheehan', 'february 27 , 1987', '5a19'], ['48', '19', 'baby', 'noam pitlik', 'lisa albert', 'march 06 , 1987', '5a06'], ['49', '20', 'separation', 'noam pitlik', 'frank dungan & jeff stein', 'may 01 , 1987', '5a21'], ['50', '21', 'the mogul', 'noam pitlik', 'frank dungan & jeff stein & tony sheehan', 'may 08 , 1987', '5a22']] |
1966 american football league draft | https://en.wikipedia.org/wiki/1966_American_Football_League_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17706792-1.html.csv | count | three running backs were drafted in the 1966 american football league draft . | {'scope': 'all', 'criterion': 'equal', 'value': 'running back', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to running back .', 'tostr': 'filter_eq { all_rows ; position ; running back }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; running back } }', 'tointer': 'select the rows whose position record fuzzily matches to running back . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; running back } } ; 3 } = true', 'tointer': 'select the rows whose position record fuzzily matches to running back . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; position ; running back } } ; 3 } = true | select the rows whose position record fuzzily matches to running back . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'running back_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'running back_6': 'running back', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'running back_6': [0], '3_7': [2]} | ['pick', 'afl team', 'player', 'position', 'college'] | [['1', 'miami dolphins', 'jim grabowski', 'running back', 'illinois'], ['2', 'miami dolphins', 'rick norton', 'quarterback', 'kentucky'], ['3', 'boston patriots', 'karl singer', 'offensive tackle', 'purdue'], ['4', 'denver broncos', 'jerry shay', 'offensive tackle', 'purdue'], ['5', 'houston oilers', 'tommy nobis', 'linebacker', 'texas'], ['6', 'kansas city chiefs', 'aaron brown', 'end', 'minnesota'], ['7', 'san diego chargers', 'don davis', 'offensive tackle', 'cal state - la'], ['8', 'buffalo bills', 'mike dennis', 'running back', "ole ' miss"], ['9', 'new york jets', 'bill yearby', 'offensive tackle', 'michigan'], ['10', 'oakland raiders', 'rodger bird', 'running back', 'kentucky']] |
usa today all - usa high school baseball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-3.html.csv | count | two of the players of the usa high school baseball team were drafted on to the pirates . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'pirates', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mlb draft', 'pirates'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mlb draft record fuzzily matches to pirates .', 'tostr': 'filter_eq { all_rows ; mlb draft ; pirates }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; mlb draft ; pirates } }', 'tointer': 'select the rows whose mlb draft record fuzzily matches to pirates . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; mlb draft ; pirates } } ; 2 } = true', 'tointer': 'select the rows whose mlb draft record fuzzily matches to pirates . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; mlb draft ; pirates } } ; 2 } = true | select the rows whose mlb draft record fuzzily matches to pirates . 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, 'mlb draft_5': 5, 'pirates_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', 'mlb draft_5': 'mlb draft', 'pirates_6': 'pirates', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'mlb draft_5': [0], 'pirates_6': [0], '2_7': [2]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['ben davis', 'catcher', 'malvern prep', 'malvern , pa', '1st round - 2nd pick of 1995 draft ( padres )'], ['chad hutchinson', 'pitcher', 'torrey pines high school', 'san diego , ca', 'attended stanford'], ['kerry wood', 'pitcher', 'grand prairie high school', 'grand prairie , tx', '1st round - 4th pick of 1995 draft ( cubs )'], ['michael barrett', 'infielder', 'pace academy', 'atlanta , ga', '1st round - 28th pick of 1995 draft ( expos )'], ['chad hermansen', 'infielder', 'green valley high school', 'henderson , nv', '1st round - 10th pick of 1995 draft ( pirates )'], ['jay hood', 'infielder', 'germantown high school', 'germantown , tn', 'attended georgia tech'], ['nate rolison', 'infielder', 'petal high school', 'petal , ms', '2nd round - 36th pick of 1995 draft ( marlins )'], ['shion newton', 'outfielder', 'boys and girls high school', 'brooklyn , ny', '9th round - 6th pick of 1995 draft ( pirates )'], ['reggie taylor', 'outfielder', 'newberry high school', 'newberry , sc', '1st round - 14th pick of 1995 draft ( phillies )']] |
united states house of representatives elections , 1950 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1950 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342198-33.html.csv | count | of the incumbents who were first elected to the united states house of representatives in the 1930 " s , only 1 was unopposed in the 1950 election . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'unopposed', 'result': '1', 'col': '6', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '193'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first elected', '193'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; first elected ; 193 }', 'tointer': 'select the rows whose first elected record fuzzily matches to 193 .'}, 'candidates', 'unopposed'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose first elected record fuzzily matches to 193 . among these rows , select the rows whose candidates record fuzzily matches to unopposed .', 'tostr': 'filter_eq { filter_eq { all_rows ; first elected ; 193 } ; candidates ; unopposed }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; first elected ; 193 } ; candidates ; unopposed } }', 'tointer': 'select the rows whose first elected record fuzzily matches to 193 . among these rows , select the rows whose candidates record fuzzily matches to unopposed . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; first elected ; 193 } ; candidates ; unopposed } } ; 1 } = true', 'tointer': 'select the rows whose first elected record fuzzily matches to 193 . among these rows , select the rows whose candidates record fuzzily matches to unopposed . the number of such rows is 1 .'} | eq { count { filter_eq { filter_eq { all_rows ; first elected ; 193 } ; candidates ; unopposed } } ; 1 } = true | select the rows whose first elected record fuzzily matches to 193 . among these rows , select the rows whose candidates record fuzzily matches to unopposed . 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, 'first elected_6': 6, '193_7': 7, 'candidates_8': 8, 'unopposed_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', 'first elected_6': 'first elected', '193_7': '193', 'candidates_8': 'candidates', 'unopposed_9': 'unopposed', '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], 'first elected_6': [0], '193_7': [0], 'candidates_8': [1], 'unopposed_9': [1], '1_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'john h kerr', 'democratic', '1923', 're - elected', 'john h kerr ( d ) unopposed'], ['north carolina 3', 'graham arthur barden', 'democratic', '1934', 're - elected', 'graham arthur barden ( d ) unopposed'], ['north carolina 4', 'harold d cooley', 'democratic', '1934', 're - elected', 'harold d cooley ( d ) 72.8 % ray f swain ( r ) 27.2 %'], ['north carolina 5', 'richard thurmond chatham', 'democratic', '1948', 're - elected', 'richard thurmond chatham ( d ) unopposed'], ['north carolina 6', 'carl t durham', 'democratic', '1938', 're - elected', 'carl t durham ( d ) 75.4 % a a mcdonald ( r ) 24.6 %']] |
little east conference | https://en.wikipedia.org/wiki/Little_East_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974545-2.html.csv | unique | only salem state university has a men 's lacrosse team among the sports teams listed . | {'scope': 'all', 'row': '4', 'col': '8', 'col_other': '1', 'criterion': 'equal', 'value': "men 's lacrosse", 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'lec sport', "men 's lacrosse"], 'result': None, 'ind': 0, 'tointer': "select the rows whose lec sport record fuzzily matches to men 's lacrosse .", 'tostr': "filter_eq { all_rows ; lec sport ; men 's lacrosse }"}], 'result': True, 'ind': 1, 'tostr': "only { filter_eq { all_rows ; lec sport ; men 's lacrosse } }", 'tointer': "select the rows whose lec sport record fuzzily matches to men 's lacrosse . there is only one such row in the table ."}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'lec sport', "men 's lacrosse"], 'result': None, 'ind': 0, 'tointer': "select the rows whose lec sport record fuzzily matches to men 's lacrosse .", 'tostr': "filter_eq { all_rows ; lec sport ; men 's lacrosse }"}, 'institution'], 'result': 'salem state university', 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; lec sport ; men 's lacrosse } ; institution }"}, 'salem state university'], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; lec sport ; men 's lacrosse } ; institution } ; salem state university }", 'tointer': 'the institution record of this unqiue row is salem state university .'}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; lec sport ; men 's lacrosse } } ; eq { hop { filter_eq { all_rows ; lec sport ; men 's lacrosse } ; institution } ; salem state university } } = true", 'tointer': "select the rows whose lec sport record fuzzily matches to men 's lacrosse . there is only one such row in the table . the institution record of this unqiue row is salem state university ."} | and { only { filter_eq { all_rows ; lec sport ; men 's lacrosse } } ; eq { hop { filter_eq { all_rows ; lec sport ; men 's lacrosse } ; institution } ; salem state university } } = true | select the rows whose lec sport record fuzzily matches to men 's lacrosse . there is only one such row in the table . the institution record of this unqiue row is salem state university . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'lec sport_7': 7, "men's lacrosse_8": 8, 'str_eq_3': 3, 'str_hop_2': 2, 'institution_9': 9, 'salem state university_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'lec sport_7': 'lec sport', "men's lacrosse_8": "men 's lacrosse", 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'institution_9': 'institution', 'salem state university_10': 'salem state university'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'lec sport_7': [0], "men's lacrosse_8": [0], 'str_eq_3': [4], 'str_hop_2': [3], 'institution_9': [2], 'salem state university_10': [3]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'primary conference', 'lec sport'] | [['bridgewater state university', 'bridgewater , massachusetts', 'bears', '1840', 'public', '11201', 'mascac', 'field hockey tennis'], ['fitchburg state university', 'fitchburg , massachusetts', 'falcons', '1894', 'public', '5201', 'mascac', 'field hockey'], ['framingham state university', 'framingham , massachusetts', 'rams', '1839', 'public', '5903', 'mascac', 'field hockey'], ['salem state university', 'salem , massachusetts', 'vikings', '1854', 'public', '10125', 'mascac', "field hockey men 's lacrosse tennis"], ['westfield state university', 'westfield , massachusetts', 'owls', '1838', 'public', '5500', 'mascac', 'field hockey']] |
dave penney | https://en.wikipedia.org/wiki/Dave_Penney | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1175663-1.html.csv | aggregation | the average number of losses for dave penney was 28.2 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '28.2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'lost'], 'result': '28.2', 'ind': 0, 'tostr': 'avg { all_rows ; lost }'}, '28.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; lost } ; 28.2 } = true', 'tointer': 'the average of the lost record of all rows is 28.2 .'} | round_eq { avg { all_rows ; lost } ; 28.2 } = true | the average of the lost record of all rows is 28.2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'lost_4': 4, '28.2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'lost_4': 'lost', '28.2_5': '28.2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'lost_4': [0], '28.2_5': [1]} | ['team', 'nation', 'from', 'matches', 'drawn', 'lost', 'win %'] | [['doncaster rovers', 'england', '22 april 2000', '6', '1', '1', '66.7'], ['doncaster rovers', 'england', '27 december 2001', '241', '62', '65', '47.3'], ['darlington', 'england', '30 october 2006', '139', '35', '44', '43.2'], ['oldham athletic', 'england', '30 april 2009', '48', '13', '22', '27.1'], ['bristol rovers', 'england', '10 january 2011', '13', '2', '9', '15.38']] |
1988 los angeles rams season | https://en.wikipedia.org/wiki/1988_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11157007-1.html.csv | count | in the 1988 los angeles rams season , three of the games were in the month of december . | {'scope': 'all', 'criterion': 'equal', 'value': 'december', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to december .', 'tostr': 'filter_eq { all_rows ; date ; december }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; december } }', 'tointer': 'select the rows whose date record fuzzily matches to december . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; december } } ; 3 } = true', 'tointer': 'select the rows whose date record fuzzily matches to december . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; date ; december } } ; 3 } = true | select the rows whose date record fuzzily matches to december . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'december_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'december_6': 'december', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'december_6': [0], '3_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 4 , 1988', 'green bay packers', 'w 34 - 7', '53769'], ['2', 'september 11 , 1988', 'detroit lions', 'w 17 - 10', '46262'], ['3', 'september 18 , 1988', 'los angeles raiders', 'w 22 - 17', '84870'], ['4', 'september 25 , 1988', 'new york giants', 'w 45 - 31', '75617'], ['5', 'october 2 , 1988', 'phoenix cardinals', 'l 41 - 27', '49830'], ['6', 'october 9 , 1988', 'atlanta falcons', 'w 33 - 0', '30852'], ['7', 'october 16 , 1988', 'san francisco 49ers', 'l 24 - 21', '65450'], ['8', 'october 23 , 1988', 'seattle seahawks', 'w 31 - 10', '57033'], ['9', 'october 30 , 1988', 'new orleans saints', 'w 12 - 10', '68238'], ['10', 'november 6 , 1988', 'philadelphia eagles', 'l 30 - 24', '65624'], ['11', 'november 13 , 1988', 'new orleans saints', 'l 14 - 10', '63305'], ['12', 'november 20 , 1988', 'san diego chargers', 'l 38 - 24', '45462'], ['13', 'november 27 , 1988', 'denver broncos', 'l 35 - 24', '74141'], ['14', 'december 5 , 1988', 'chicago bears', 'w 23 - 3', '65579'], ['15', 'december 11 , 1988', 'atlanta falcons', 'w 22 - 7', '42828'], ['16', 'december 18 , 1988', 'san francisco 49ers', 'w 38 - 16', '62444']] |
1998 formula one season | https://en.wikipedia.org/wiki/1998_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1137694-3.html.csv | unique | in the 1998 formula one season , when mika häkkinen had the pole position , the only time damon hill was the winning driver was in round 13 . | {'scope': 'subset', 'row': '13', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'damon hill', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'mika häkkinen'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pole position', 'mika häkkinen'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; pole position ; mika häkkinen }', 'tointer': 'select the rows whose pole position record fuzzily matches to mika häkkinen .'}, 'winning driver', 'damon hill'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose pole position record fuzzily matches to mika häkkinen . among these rows , select the rows whose winning driver record fuzzily matches to damon hill .', 'tostr': 'filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } }', 'tointer': 'select the rows whose pole position record fuzzily matches to mika häkkinen . among these rows , select the rows whose winning driver record fuzzily matches to damon hill . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pole position', 'mika häkkinen'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; pole position ; mika häkkinen }', 'tointer': 'select the rows whose pole position record fuzzily matches to mika häkkinen .'}, 'winning driver', 'damon hill'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose pole position record fuzzily matches to mika häkkinen . among these rows , select the rows whose winning driver record fuzzily matches to damon hill .', 'tostr': 'filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill }'}, 'round'], 'result': '13', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } ; round }'}, '13'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } ; round } ; 13 }', 'tointer': 'the round record of this unqiue row is 13 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } } ; eq { hop { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } ; round } ; 13 } } = true', 'tointer': 'select the rows whose pole position record fuzzily matches to mika häkkinen . among these rows , select the rows whose winning driver record fuzzily matches to damon hill . there is only one such row in the table . the round record of this unqiue row is 13 .'} | and { only { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } } ; eq { hop { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } ; round } ; 13 } } = true | select the rows whose pole position record fuzzily matches to mika häkkinen . among these rows , select the rows whose winning driver record fuzzily matches to damon hill . there is only one such row in the table . the round record of this unqiue row is 13 . | 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, 'pole position_8': 8, 'mika häkkinen_9': 9, 'winning driver_10': 10, 'damon hill_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'round_12': 12, '13_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', 'pole position_8': 'pole position', 'mika häkkinen_9': 'mika häkkinen', 'winning driver_10': 'winning driver', 'damon hill_11': 'damon hill', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'round_12': 'round', '13_13': '13'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'pole position_8': [0], 'mika häkkinen_9': [0], 'winning driver_10': [1], 'damon hill_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'round_12': [3], '13_13': [4]} | ['round', 'grand prix', 'pole position', 'fastest lap', 'winning driver', 'winning constructor', 'report'] | [['1', 'australian grand prix', 'mika häkkinen', 'mika häkkinen', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['2', 'brazilian grand prix', 'mika häkkinen', 'mika häkkinen', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['3', 'argentine grand prix', 'david coulthard', 'alexander wurz', 'michael schumacher', 'ferrari', 'report'], ['4', 'san marino grand prix', 'david coulthard', 'michael schumacher', 'david coulthard', 'mclaren - mercedes', 'report'], ['5', 'spanish grand prix', 'mika häkkinen', 'mika häkkinen', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['6', 'monaco grand prix', 'mika häkkinen', 'mika häkkinen', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['7', 'canadian grand prix', 'david coulthard', 'michael schumacher', 'michael schumacher', 'ferrari', 'report'], ['8', 'french grand prix', 'mika häkkinen', 'david coulthard', 'michael schumacher', 'ferrari', 'report'], ['9', 'british grand prix', 'mika häkkinen', 'michael schumacher', 'michael schumacher', 'ferrari', 'report'], ['10', 'austrian grand prix', 'giancarlo fisichella', 'david coulthard', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['11', 'german grand prix', 'mika häkkinen', 'david coulthard', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['12', 'hungarian grand prix', 'mika häkkinen', 'michael schumacher', 'michael schumacher', 'ferrari', 'report'], ['13', 'belgian grand prix', 'mika häkkinen', 'michael schumacher', 'damon hill', 'jordan - mugen - honda', 'report'], ['14', 'italian grand prix', 'michael schumacher', 'mika häkkinen', 'michael schumacher', 'ferrari', 'report'], ['15', 'luxembourg grand prix', 'michael schumacher', 'mika häkkinen', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['16', 'japanese grand prix', 'michael schumacher', 'michael schumacher', 'mika häkkinen', 'mclaren - mercedes', 'report']] |
solids with icosahedral symmetry | https://en.wikipedia.org/wiki/Solids_with_icosahedral_symmetry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13727381-6.html.csv | superlative | the truncated icosidodecahedron has the highest number of edges of all dual archimedean solids . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'edges'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; edges }'}, 'dual archimedean solid'], 'result': 'truncated icosidodecahedron', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; edges } ; dual archimedean solid }'}, 'truncated icosidodecahedron'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; edges } ; dual archimedean solid } ; truncated icosidodecahedron } = true', 'tointer': 'select the row whose edges record of all rows is maximum . the dual archimedean solid record of this row is truncated icosidodecahedron .'} | eq { hop { argmax { all_rows ; edges } ; dual archimedean solid } ; truncated icosidodecahedron } = true | select the row whose edges record of all rows is maximum . the dual archimedean solid record of this row is truncated icosidodecahedron . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'edges_5': 5, 'dual archimedean solid_6': 6, 'truncated icosidodecahedron_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'edges_5': 'edges', 'dual archimedean solid_6': 'dual archimedean solid', 'truncated icosidodecahedron_7': 'truncated icosidodecahedron'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'edges_5': [0], 'dual archimedean solid_6': [1], 'truncated icosidodecahedron_7': [2]} | ['picture', 'dual archimedean solid', 'faces', 'edges', 'vertices', 'face polygon'] | [['( video )', 'icosidodecahedron', '30', '60', '32', 'rhombus'], ['( video )', 'truncated dodecahedron', '60', '90', '32', 'isosceles triangle'], ['( video )', 'truncated icosahedron', '60', '90', '32', 'isosceles triangle'], ['( video )', 'rhombicosidodecahedron', '60', '120', '62', 'kite'], ['( video )', 'truncated icosidodecahedron', '120', '180', '62', 'scalene triangle']] |
list of members - elect of the united states house of representatives who never took their seats | https://en.wikipedia.org/wiki/List_of_members-elect_of_the_United_States_House_of_Representatives_who_never_took_their_seats | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14158567-1.html.csv | majority | the majority of member-elect representatives did not take their seats due to dying . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'died', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'reason for non - seating', 'died'], 'result': True, 'ind': 0, 'tointer': 'for the reason for non - seating records of all rows , most of them fuzzily match to died .', 'tostr': 'most_eq { all_rows ; reason for non - seating ; died } = true'} | most_eq { all_rows ; reason for non - seating ; died } = true | for the reason for non - seating records of all rows , most of them fuzzily match to died . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'reason for non - seating_3': 3, 'died_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'reason for non - seating_3': 'reason for non - seating', 'died_4': 'died'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'reason for non - seating_3': [0], 'died_4': [0]} | ['member - elect', 'party', 'district', 'election date', 'congress', 'reason for non - seating'] | [['augustus f allen', 'democratic', 'ny - 33', 'november 3 , 1874', '44th', 'died january 22 , 1875'], ['andrew j campbell', 'republican', 'ny - 10', 'november 5 , 1894', '54th', 'died december 6 , 1894'], ['john cantine', 'democratic - republican', 'ny - 7', 'april 27 to 29 , 1802', '8th', 'elected , but declined to take office'], ['william dowse', 'federalist', 'ny - 15', 'december 15 to 17 , 1812', '13th', 'died on february 18 , 1813'], ['richard p giles', 'democratic', 'mo - 1', 'november 3 , 1896', '55th', 'died november 17 , 1896'], ['samuel marx', 'democratic', 'ny - 19', 'november 7 , 1922', '68th', 'died november 30 , 1922'], ['washington poe', 'whig', 'ga - 3', 'november 5 , 1844', '29th', 'resigned before taking office'], ['jack swigert', 'republican', 'co - 6', 'november 2 , 1982', '98th', 'died before taking office']] |
2006 u.s. open ( golf ) | https://en.wikipedia.org/wiki/2006_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12523044-4.html.csv | aggregation | the average score of players in the 2006 u.s. open is 70.46 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '70.46', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '70.46', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '70.46'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 70.46 } = true', 'tointer': 'the average of the score record of all rows is 70.46 .'} | round_eq { avg { all_rows ; score } ; 70.46 } = true | the average of the score record of all rows is 70.46 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '70.46_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '70.46_5': '70.46'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '70.46_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'colin montgomerie', 'scotland', '69', '- 1'], ['t2', 'jim furyk', 'united states', '70', 'e'], ['t2', 'david howell', 'england', '70', 'e'], ['t2', 'miguel ángel jiménez', 'spain', '70', 'e'], ['t2', 'phil mickelson', 'united states', '70', 'e'], ['t2', 'steve stricker', 'united states', '70', 'e'], ['t7', 'john cook', 'united states', '71', '+ 1'], ['t7', 'kenneth ferrie', 'england', '71', '+ 1'], ['t7', 'fred funk', 'united states', '71', '+ 1'], ['t7', 'graeme mcdowell', 'northern ireland', '71', '+ 1'], ['t7', 'geoff ogilvy', 'australia', '71', '+ 1'], ['t7', 'vijay singh', 'fiji', '71', '+ 1'], ['t7', 'mike weir', 'canada', '71', '+ 1']] |
1922 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1922_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18007045-1.html.csv | aggregation | in the 1922 u.s. open , the average number of strokes to par is 13.4 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '13.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'to par'], 'result': '13.4', 'ind': 0, 'tostr': 'avg { all_rows ; to par }'}, '13.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; to par } ; 13.4 } = true', 'tointer': 'the average of the to par record of all rows is 13.4 .'} | round_eq { avg { all_rows ; to par } ; 13.4 } = true | the average of the to par record of all rows is 13.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'to par_4': 4, '13.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '13.4_5': '13.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'to par_4': [0], '13.4_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'gene sarazen', 'united states', '72 + 73 + 75 + 68 = 288', '+ 8', '500'], ['t2', 'john black', 'scotland', '71 + 71 + 75 + 72 = 289', '+ 9', '300'], ['t2', 'bobby jones ( a )', 'united states', '74 + 72 + 70 + 73 = 289', '+ 9', '0'], ['4', 'bill mehlhorn', 'united states', '73 + 71 + 72 + 74 = 290', '+ 10', '200'], ['5', 'walter hagen', 'united states', '68 + 77 + 74 + 72 = 291', '+ 11', '150'], ['6', 'george duncan', 'scotland', '76 + 73 + 75 + 72 = 296', '+ 16', '100'], ['7', 'leo diegel', 'united states', '77 + 76 + 73 + 71 = 297', '+ 17', '90'], ['t8', 'mike brady', 'united states', '73 + 75 + 74 + 76 = 298', '+ 18', '73'], ['t8', 'johnny golden', 'united states', '73 + 77 + 77 + 71 = 298', '+ 18', '73'], ['t8', 'jock hutchison', 'united states', '78 + 74 + 71 + 75 = 298', '+ 18', '73']] |
varvara lepchenko | https://en.wikipedia.org/wiki/Varvara_Lepchenko | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10577658-3.html.csv | majority | the majority of tennis tournaments that varvara lepchenko played in were on a hard surface . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'date', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', '21 april 2003', 'clay', 'julie ditty', 'milagros sequera christina wheeler', '7 - 5 1 - 6 2 - 6'], ['winner', '31 may 2004', 'hard', 'cory - ann avants', 'tanner cochran jaslyn hewitt', '6 - 2 3 - 6 6 - 3'], ['runner - up', '7 june 2004', 'hard', 'cory - ann avants', 'angela haynes diana ospina', '0 - 6 2 - 6'], ['runner - up', '5 april 2005', 'clay', 'edina gallovits', 'tatiana poutchek anastasia rodionova', '2 - 6 4 - 6'], ['runner - up', '18 april 2006', 'clay', 'edina gallovits', 'monique adamczak soledad esperón', '4 - 6 6 - 3 4 - 6'], ['runner - up', '25 july 2006', 'hard', 'akgul amanmuradova', 'chin - wei chan abigail spears', '1 - 6 1 - 6'], ['runner - up', '31 july 2006', 'hard', 'akgul amanmuradova', 'chin - wei chan tetiana luzhanska', '2 - 6 6 - 1 0 - 6'], ['runner - up', '18 september 2007', 'hard', 'liga dekmeijere', 'melinda czink angela haynes', '5 - 7 4 - 6'], ['runner - up', '1 july 2008', 'hard', 'yulia fedossova', 'chin - wei chan natalie grandin', '4 - 6 3 - 6'], ['runner - up', '27 september 2011', 'hard', 'melanie oudin', 'alexa glatch mashona washington', '4 - 6 2 - 6'], ['runner - up', '11 october 2011', 'hard', 'mashona washington', 'elena bovina valeria savinykh', '6 - 7 ( 6 - 8 ) 3 - 6']] |
united states house of representatives elections , 1920 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1920 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342451-16.html.csv | majority | all of the incumbents in the 1920 united states house of representatives elections were with the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'} | all_eq { all_rows ; party ; democratic } = true | for the party records of all rows , all of them fuzzily match to democratic . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', "james o'connor", 'democratic', '1918', 're - elected', "james o'connor ( d ) unopposed"], ['louisiana 2', 'henry garland dupré', 'democratic', '1908', 're - elected', 'henry garland dupré ( d ) unopposed'], ['louisiana 3', 'whitmell p martin', 'democratic', '1914', 're - elected', 'whitmell p martin ( d ) unopposed'], ['louisiana 4', 'john t watkins', 'democratic', '1904', 'lost renomination democratic hold', 'john n sandlin ( d ) unopposed'], ['louisiana 5', 'riley joseph wilson', 'democratic', '1914', 're - elected', 'riley joseph wilson ( d ) unopposed'], ['louisiana 6', 'jared y sanders , sr', 'democratic', '1916', 'retired to run for us senate democratic hold', 'george k favrot ( d ) unopposed'], ['louisiana 7', 'ladislas lazaro', 'democratic', '1912', 're - elected', 'ladislas lazaro ( d ) unopposed']] |
lone star alliance | https://en.wikipedia.org/wiki/Lone_Star_Alliance | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28243691-1.html.csv | comparative | the university of texas at austin has a larger enrollment than texas christian university . | {'row_1': '12', 'row_2': '9', 'col': '5', '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', 'institution', 'university of texas at austin'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to university of texas at austin .', 'tostr': 'filter_eq { all_rows ; institution ; university of texas at austin }'}, 'enrollment'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; institution ; university of texas at austin } ; enrollment }', 'tointer': 'select the rows whose institution record fuzzily matches to university of texas at austin . take the enrollment record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'texas christian university'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose institution record fuzzily matches to texas christian university .', 'tostr': 'filter_eq { all_rows ; institution ; texas christian university }'}, 'enrollment'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; institution ; texas christian university } ; enrollment }', 'tointer': 'select the rows whose institution record fuzzily matches to texas christian university . take the enrollment record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; institution ; university of texas at austin } ; enrollment } ; hop { filter_eq { all_rows ; institution ; texas christian university } ; enrollment } } = true', 'tointer': 'select the rows whose institution record fuzzily matches to university of texas at austin . take the enrollment record of this row . select the rows whose institution record fuzzily matches to texas christian university . take the enrollment record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; institution ; university of texas at austin } ; enrollment } ; hop { filter_eq { all_rows ; institution ; texas christian university } ; enrollment } } = true | select the rows whose institution record fuzzily matches to university of texas at austin . take the enrollment record of this row . select the rows whose institution record fuzzily matches to texas christian university . take the enrollment 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, 'institution_7': 7, 'university of texas at austin_8': 8, 'enrollment_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'institution_11': 11, 'texas christian university_12': 12, 'enrollment_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', 'institution_7': 'institution', 'university of texas at austin_8': 'university of texas at austin', 'enrollment_9': 'enrollment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'institution_11': 'institution', 'texas christian university_12': 'texas christian university', 'enrollment_13': 'enrollment'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'institution_7': [0], 'university of texas at austin_8': [0], 'enrollment_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'institution_11': [1], 'texas christian university_12': [1], 'enrollment_13': [3]} | ['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname', 'primary conference'] | [['baylor university', 'waco , texas', '1845', 'private , baptist', '14769', 'bears', 'big 12 ( division i )'], ['university of louisiana at lafayette', 'lafayette , louisiana', '1898', 'public', '16361', "ragin ' cajuns", 'sunbelt ( division i )'], ['louisiana state university', 'baton rouge , louisiana', '1860', 'public', '25215', 'tigers', 'sec ( division i )'], ['university of north texas', 'denton , texas', '1890', 'public', '36206', 'mean green', 'c - usa ( division i )'], ['university of oklahoma', 'norman , oklahoma', '1890', 'public', '29931', 'sooners', 'big 12 ( division i )'], ['rice university', 'houston , texas', '1891', 'private / non - sectarian', '6799', 'owls', 'c - usa ( division i )'], ['southern methodist university', 'university park , texas', '1911', 'private / methodist', '10693', 'mustangs', 'american ( division i )'], ['texas a & m university', 'college station , texas', '1871', 'public', '48702', 'aggies', 'sec ( division i )'], ['texas christian university', 'fort worth , texas', '1873', 'private / disciples of christ', '8696', 'horned frogs', 'big 12 ( division i )'], ['texas state universitysan marcos', 'san marcos , texas', '1899', 'public', '32586', 'bobcats', 'sunbelt ( division i )'], ['texas tech university', 'lubbock , texas', '1923', 'public', '30049', 'red raiders', 'big 12 ( division i )'], ['university of texas at austin', 'austin , texas', '1883', 'public', '50995', 'longhorns', 'big 12 ( division i )']] |
2008 australian sports sedan series | https://en.wikipedia.org/wiki/2008_Australian_Sports_Sedan_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18124534-2.html.csv | count | there were only a total of 5 races in the 2008 australian sports sedan series . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'race title'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race title record is arbitrary .', 'tostr': 'filter_all { all_rows ; race title }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; race title } }', 'tointer': 'select the rows whose race title record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; race title } } ; 5 } = true', 'tointer': 'select the rows whose race title record is arbitrary . the number of such rows is 5 .'} | eq { count { filter_all { all_rows ; race title } } ; 5 } = true | select the rows whose race title 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, 'race title_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'race title_5': 'race title', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'race title_5': [0], '5_6': [2]} | ['race title', 'circuit', 'city / state', 'date', 'winner'] | [['mallala', 'mallala motor sport park', 'adelaide , south australia', '1718 may', 'luke youlden'], ['phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '14 - 15 jun', 'darren hossack'], ['eastern creek', 'eastern creek raceway', 'sydney , new south wales', '12 - 13 jul', 'darren hossack'], ['oran park', 'oran park raceway', 'sydney , new south wales', '30 - 31 aug', 'tony ricciardello'], ['sandown', 'sandown raceway', 'melbourne , victoria', '29 - 30 nov', 'tony ricciardello']] |
elvis ' gold records volume 5 | https://en.wikipedia.org/wiki/Elvis%27_Gold_Records_Volume_5 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15582798-3.html.csv | unique | track number four , titled moody blue , is the only song in this album that is written by mark james . | {'scope': 'all', 'row': '4', 'col': '6', 'col_other': '1,5', 'criterion': 'equal', 'value': 'mark james', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'writer ( s )', 'mark james'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to mark james .', 'tostr': 'filter_eq { all_rows ; writer ( s ) ; mark james }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; writer ( s ) ; mark james } }', 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to mark james . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'writer ( s )', 'mark james'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to mark james .', 'tostr': 'filter_eq { all_rows ; writer ( s ) ; mark james }'}, 'track'], 'result': '4', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; track }'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; track } ; 4 }', 'tointer': 'the track record of this unqiue row is 4 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'writer ( s )', 'mark james'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to mark james .', 'tostr': 'filter_eq { all_rows ; writer ( s ) ; mark james }'}, 'song title'], 'result': 'moody blue', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; song title }'}, 'moody blue'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; song title } ; moody blue }', 'tointer': 'the song title record of this unqiue row is moody blue .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; track } ; 4 } ; eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; song title } ; moody blue } }', 'tointer': 'the track record of this unqiue row is 4 . the song title record of this unqiue row is moody blue .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; writer ( s ) ; mark james } } ; and { eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; track } ; 4 } ; eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; song title } ; moody blue } } } = true', 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to mark james . there is only one such row in the table . the track record of this unqiue row is 4 . the song title record of this unqiue row is moody blue .'} | and { only { filter_eq { all_rows ; writer ( s ) ; mark james } } ; and { eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; track } ; 4 } ; eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; song title } ; moody blue } } } = true | select the rows whose writer ( s ) record fuzzily matches to mark james . there is only one such row in the table . the track record of this unqiue row is 4 . the song title record of this unqiue row is moody blue . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'writer (s)_10': 10, 'mark james_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'track_12': 12, '4_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'song title_14': 14, 'moody blue_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'writer (s)_10': 'writer ( s )', 'mark james_11': 'mark james', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'track_12': 'track', '4_13': '4', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'song title_14': 'song title', 'moody blue_15': 'moody blue'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'writer (s)_10': [0], 'mark james_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'track_12': [2], '4_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'song title_14': [4], 'moody blue_15': [5]} | ['track', 'recorded', 'catalogue', 'release date', 'song title', 'writer ( s )', 'time'] | [['1', '3 / 28 / 72', '74 - 0769', '8 / 1 / 72', 'burning love', 'dennis linde', '2:50'], ['2', '12 / 11 / 73', 'apbo 0280', '5 / 10 / 74', 'if you talk in your sleep', 'red west and johnny christopher', '2:34'], ['3', '2 / 5 / 76', 'pb 10601b', '3 / 12 / 76', 'for the heart', 'dennis linde', '3:22'], ['4', '2 / 4 / 76', 'pb 10857', '11 / 29 / 76', 'moody blue', 'mark james', '3:22'], ['5', '10 / 29 / 76', 'pb 10998', '6 / 6 / 77', 'way down', 'layng martine jr', '2:38']] |
1957 formula one season | https://en.wikipedia.org/wiki/1957_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1140111-5.html.csv | count | jean behra was the winning driver four times in the 1957 formula one season . | {'scope': 'all', 'criterion': 'equal', 'value': 'jean behra', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning driver', 'jean behra'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning driver record fuzzily matches to jean behra .', 'tostr': 'filter_eq { all_rows ; winning driver ; jean behra }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; winning driver ; jean behra } }', 'tointer': 'select the rows whose winning driver record fuzzily matches to jean behra . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; winning driver ; jean behra } } ; 4 } = true', 'tointer': 'select the rows whose winning driver record fuzzily matches to jean behra . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; winning driver ; jean behra } } ; 4 } = true | select the rows whose winning driver record fuzzily matches to jean behra . 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, 'winning driver_5': 5, 'jean behra_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', 'winning driver_5': 'winning driver', 'jean behra_6': 'jean behra', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winning driver_5': [0], 'jean behra_6': [0], '4_7': [2]} | ['race name', 'circuit', 'date', 'winning driver', 'constructor', 'report'] | [['xi gran premio ciudad de buenos aires', 'buenos aires', '27 january', 'juan manuel fangio', 'maserati', 'report'], ['vii gran premio di siracusa', 'syracuse', '7 april', 'peter collins', 'lancia - ferrari', 'report'], ['xvii pau grand prix', 'pau', '22 april', 'jean behra', 'maserati', 'report'], ['v glover trophy', 'goodwood', '22 april', 'stuart lewis - evans', 'connaught - alta', 'report'], ['x gran premio di napoli', 'posillipo', '28 april', 'peter collins', 'lancia - ferrari', 'report'], ['xxiii grand prix de reims', 'reims - gueux', '14 july', 'luigi musso', 'lancia - ferrari', 'report'], ['v grand prix de caen', 'caen', '28 july', 'jean behra', 'brm', 'report'], ['ix brdc international trophy', 'silverstone', '14 september', 'jean behra', 'brm', 'report'], ['v gran premio di modena', 'modena', '22 september', 'jean behra', 'maserati', 'report']] |
ian woosnam | https://en.wikipedia.org/wiki/Ian_Woosnam | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1034991-8.html.csv | superlative | ian woosnam has more top 25 finishes in the open championship than any other tournament . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'top - 25'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; top - 25 }'}, 'tournament'], 'result': 'the open championship', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; top - 25 } ; tournament }'}, 'the open championship'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; top - 25 } ; tournament } ; the open championship } = true', 'tointer': 'select the row whose top - 25 record of all rows is maximum . the tournament record of this row is the open championship .'} | eq { hop { argmax { all_rows ; top - 25 } ; tournament } ; the open championship } = true | select the row whose top - 25 record of all rows is maximum . the tournament record of this row is the open championship . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'top - 25_5': 5, 'tournament_6': 6, 'the open championship_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'top - 25_5': 'top - 25', 'tournament_6': 'tournament', 'the open championship_7': 'the open championship'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'top - 25_5': [0], 'tournament_6': [1], 'the open championship_7': [2]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '1', '1', '1', '7', '25', '13'], ['us open', '0', '1', '2', '4', '10', '7'], ['the open championship', '0', '4', '5', '10', '23', '17'], ['pga championship', '0', '0', '2', '3', '18', '9'], ['totals', '1', '6', '10', '24', '76', '46']] |
1996 - 97 toronto raptors season | https://en.wikipedia.org/wiki/1996%E2%80%9397_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13557843-3.html.csv | aggregation | throughout the 1996-97 toronto raptors season , damon stoudamire made 95 high assists . | {'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '95', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'damon stoudamire'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'damon stoudamire'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high assists ; damon stoudamire }', 'tointer': 'select the rows whose high assists record fuzzily matches to damon stoudamire .'}, 'high assists'], 'result': '95', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; high assists ; damon stoudamire } ; high assists }'}, '95'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; high assists ; damon stoudamire } ; high assists } ; 95 } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to damon stoudamire . the sum of the high assists record of these rows is 95 .'} | round_eq { sum { filter_eq { all_rows ; high assists ; damon stoudamire } ; high assists } ; 95 } = true | select the rows whose high assists record fuzzily matches to damon stoudamire . the sum of the high assists record of these rows is 95 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'damon stoudamire_6': 6, 'high assists_7': 7, '95_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'damon stoudamire_6': 'damon stoudamire', 'high assists_7': 'high assists', '95_8': '95'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'damon stoudamire_6': [0], 'high assists_7': [1], '95_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['1', 'november 1', 'new york', 'l 99 - 107 ( ot )', 'damon stoudamire ( 28 )', 'popeye jones ( 9 )', 'damon stoudamire ( 10 )', 'skydome 28457', '0 - 1'], ['2', 'november 2', 'charlotte', 'l 98 - 109 ( ot )', 'damon stoudamire ( 19 )', 'carlos rogers ( 8 )', 'damon stoudamire ( 5 )', 'charlotte coliseum 24042', '0 - 2'], ['3', 'november 5', 'dallas', 'w 100 - 96 ( ot )', 'walt williams ( 34 )', 'carlos rogers ( 12 )', 'damon stoudamire ( 8 )', 'skydome 17065', '1 - 2'], ['4', 'november 8', 'la lakers', 'w 93 - 92 ( ot )', 'damon stoudamire ( 21 )', 'damon stoudamire ( 10 )', 'damon stoudamire ( 10 )', 'skydome 27357', '2 - 2'], ['5', 'november 11', 'denver', 'l 93 - 104 ( ot )', 'marcus camby ( 26 )', 'carlos rogers ( 9 )', 'damon stoudamire ( 6 )', 'skydome 17132', '2 - 3'], ['6', 'november 13', 'philadelphia', 'w 110 - 98 ( ot )', 'marcus camby ( 23 )', 'popeye jones ( 14 )', 'damon stoudamire ( 12 )', 'skydome 17385', '3 - 3'], ['7', 'november 14', 'new york', 'l 96 - 99 ( ot )', 'marcus camby ( 29 )', 'popeye jones ( 8 )', 'damon stoudamire ( 13 )', 'madison square garden 19763', '3 - 4'], ['8', 'november 16', 'orlando', 'l 87 - 92 ( ot )', 'walt williams ( 29 )', 'doug christie ( 7 )', 'damon stoudamire ( 5 )', 'orlando arena 17248', '3 - 5'], ['9', 'november 19', 'seattle', 'l 98 - 106 ( ot )', 'doug christie ( 31 )', 'popeye jones ( 11 )', 'marcus camby ( 4 )', 'skydome 18803', '3 - 6'], ['10', 'november 21', 'cleveland', 'l 81 - 89 ( ot )', 'damon stoudamire ( 24 )', 'acie earl ( 8 )', 'damon stoudamire ( 6 )', 'skydome 16835', '3 - 7'], ['11', 'november 23', 'atlanta', 'l 88 - 91 ( ot )', 'damon stoudamire ( 22 )', 'popeye jones ( 9 )', 'damon stoudamire ( 8 )', 'skydome 16838', '3 - 8'], ['12', 'november 26', 'sacramento', 'l 87 - 98 ( ot )', 'damon stoudamire ( 27 )', 'popeye jones ( 16 )', 'damon stoudamire ( 6 )', 'skydome 15037', '3 - 9'], ['13', 'november 27', 'charlotte', 'w 92 - 88 ( ot )', 'walt williams ( 23 )', 'popeye jones ( 18 )', 'damon stoudamire ( 6 )', 'skydome 15710', '4 - 9']] |
central collegiate lacrosse association | https://en.wikipedia.org/wiki/Central_Collegiate_Lacrosse_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28211213-2.html.csv | comparative | the enrollment at lawrence technological university is lower than the enrollment at northern michigan university . | {'row_1': '10', 'row_2': '13', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'lawrence technological university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to lawrence technological university .', 'tostr': 'filter_eq { all_rows ; institution ; lawrence technological university }'}, 'enrollment'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; institution ; lawrence technological university } ; enrollment }', 'tointer': 'select the rows whose institution record fuzzily matches to lawrence technological university . take the enrollment record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'northern michigan university'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose institution record fuzzily matches to northern michigan university .', 'tostr': 'filter_eq { all_rows ; institution ; northern michigan university }'}, 'enrollment'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; institution ; northern michigan university } ; enrollment }', 'tointer': 'select the rows whose institution record fuzzily matches to northern michigan university . take the enrollment record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; institution ; lawrence technological university } ; enrollment } ; hop { filter_eq { all_rows ; institution ; northern michigan university } ; enrollment } } = true', 'tointer': 'select the rows whose institution record fuzzily matches to lawrence technological university . take the enrollment record of this row . select the rows whose institution record fuzzily matches to northern michigan university . take the enrollment record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; institution ; lawrence technological university } ; enrollment } ; hop { filter_eq { all_rows ; institution ; northern michigan university } ; enrollment } } = true | select the rows whose institution record fuzzily matches to lawrence technological university . take the enrollment record of this row . select the rows whose institution record fuzzily matches to northern michigan university . take the enrollment record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'institution_7': 7, 'lawrence technological university_8': 8, 'enrollment_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'institution_11': 11, 'northern michigan university_12': 12, 'enrollment_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'institution_7': 'institution', 'lawrence technological university_8': 'lawrence technological university', 'enrollment_9': 'enrollment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'institution_11': 'institution', 'northern michigan university_12': 'northern michigan university', 'enrollment_13': 'enrollment'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'institution_7': [0], 'lawrence technological university_8': [0], 'enrollment_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'institution_11': [1], 'northern michigan university_12': [1], 'enrollment_13': [3]} | ['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname', 'primary conference'] | [['aquinas college', 'grand rapids , michigan', '1886', 'private', '2159', 'saints', 'whac ( naia )'], ['butler university', 'indianapolis , indiana', '1855', 'private', '4512', 'bulldogs', 'horizon ( division i )'], ['carnegie mellon university', 'pittsburgh , pennsylvania', '1900', 'private / nonsectarian', '10875', 'tartans', 'uaa ( division iii )'], ['university of dayton', 'dayton , ohio', '1850', 'private / catholic', '10569', 'flyers', 'atlantic 10 ( division i )'], ['ferris state university', 'big rapids , michigan', '1884', 'public', '13865', 'bulldogs', 'gliac ( division ii )'], ['grand valley state university', 'allendale , michigan', '1960', 'public', '24408', 'lakers', 'gliac ( division ii )'], ['grove city college', 'grove city , pennsylvania', '1876', 'private / christian', '2500', 'wolverines', 'pac ( division iii )'], ['indiana institute of technology', 'fort wayne , indiana', '1930', 'private', '3207', 'warriors', 'whac ( naia )'], ['john carroll university', 'university heights , ohio', '1886', 'private / catholic', '3709', 'blue streaks', 'oac ( division iii )'], ['lawrence technological university', 'southfield , mi', '1932', 'private', '4000', 'blue devils', 'whac ( naia )'], ['lourdes college', 'sylvania , oh', '1958', 'private / catholic', '2616', 'gray wolves', 'whac ( naia )'], ['university of michigan - dearborn', 'dearborn , michigan', '1959', 'public', '8634', 'wolves', 'wolverine - hoosier ( naia )'], ['northern michigan university', 'marquette , michigan', '1899', 'public', '8578', 'wildcats', 'gliac ( division ii )'], ['northwood university', 'midland , michigan', '1961', 'private', '1987', 'timberwolves', 'gliac ( division ii )'], ['oakland university', 'rochester , michigan', '1957', 'public', '18553', 'grizzlies', 'the summit league ( division i )'], ['siena heights university', 'adrian , michigan', '1919', 'private / catholic', '2274', 'saints', 'wolverine - hoosier ( naia )']] |
2009 world rally championship season | https://en.wikipedia.org/wiki/2009_World_Rally_Championship_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811741-15.html.csv | unique | sébastien loeb had the most stage wins in the 2009 world rally championship season . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '7', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 7 .', 'tostr': 'filter_eq { all_rows ; wins ; 7 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; wins ; 7 } }', 'tointer': 'select the rows whose wins record is equal to 7 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 7 .', 'tostr': 'filter_eq { all_rows ; wins ; 7 }'}, 'driver'], 'result': 'sébastien loeb', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; wins ; 7 } ; driver }'}, 'sébastien loeb'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; wins ; 7 } ; driver } ; sébastien loeb }', 'tointer': 'the driver record of this unqiue row is sébastien loeb .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; wins ; 7 } } ; eq { hop { filter_eq { all_rows ; wins ; 7 } ; driver } ; sébastien loeb } } = true', 'tointer': 'select the rows whose wins record is equal to 7 . there is only one such row in the table . the driver record of this unqiue row is sébastien loeb .'} | and { only { filter_eq { all_rows ; wins ; 7 } } ; eq { hop { filter_eq { all_rows ; wins ; 7 } ; driver } ; sébastien loeb } } = true | select the rows whose wins record is equal to 7 . there is only one such row in the table . the driver record of this unqiue row is sébastien loeb . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'wins_7': 7, '7_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'sébastien loeb_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'wins_7': 'wins', '7_8': '7', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'sébastien loeb_10': 'sébastien loeb'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'wins_7': [0], '7_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'sébastien loeb_10': [3]} | ['driver', 'starts', 'finishes', 'wins', 'podiums', 'stage wins', 'points'] | [['sébastien loeb', '12', '11', '7', '9', '88', '93'], ['mikko hirvonen', '12', '11', '4', '11', '51', '92'], ['daniel sordo', '12', '12', '0', '7', '18', '64'], ['jari - matti latvala', '12', '10', '1', '4', '40', '41'], ['petter solberg', '10', '7', '0', '2', '10', '35'], ['henning solberg', '12', '12', '0', '2', '8', '33'], ['matthew wilson', '12', '11', '0', '0', '2', '28'], ['sébastien ogier', '12', '8', '0', '1', '13', '24'], ['federico villagra', '8', '7', '0', '0', '0', '16'], ['conrad rautenbach', '12', '7', '0', '0', '0', '9'], ['mads østberg', '7', '4', '0', '0', '1', '7'], ['khalid al - qassimi', '9', '9', '0', '0', '0', '6'], ['chris atkinson', '1', '1', '0', '0', '0', '4'], ['evgeny novikov', '8', '4', '0', '0', '4', '4'], ['matti rantanen', '1', '1', '0', '0', '0', '4'], ['krzysztof hołowczyc', '1', '1', '0', '0', '0', '3'], ['jari ketomaa', '1', '1', '0', '0', '0', '3'], ['nasser al - attiyah', '6', '5', '0', '0', '0', '1'], ['urmo aava', '3', '3', '0', '0', '0', '1'], ['lambros athanassoulas', '2', '2', '0', '0', '0', '1']] |
inside business | https://en.wikipedia.org/wiki/Inside_Business | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10888144-1.html.csv | unique | season 1 was the only season of inside business that had less than 40 episodes . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'less_than', 'value': '40', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'episodes', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episodes record is less than 40 .', 'tostr': 'filter_less { all_rows ; episodes ; 40 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; episodes ; 40 } }', 'tointer': 'select the rows whose episodes record is less than 40 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'episodes', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episodes record is less than 40 .', 'tostr': 'filter_less { all_rows ; episodes ; 40 }'}, 'season no'], 'result': '1', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; episodes ; 40 } ; season no }'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; episodes ; 40 } ; season no } ; 1 }', 'tointer': 'the season no record of this unqiue row is 1 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; episodes ; 40 } } ; eq { hop { filter_less { all_rows ; episodes ; 40 } ; season no } ; 1 } } = true', 'tointer': 'select the rows whose episodes record is less than 40 . there is only one such row in the table . the season no record of this unqiue row is 1 .'} | and { only { filter_less { all_rows ; episodes ; 40 } } ; eq { hop { filter_less { all_rows ; episodes ; 40 } ; season no } ; 1 } } = true | select the rows whose episodes record is less than 40 . there is only one such row in the table . the season no record of this unqiue row is 1 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'episodes_7': 7, '40_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season no_9': 9, '1_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'episodes_7': 'episodes', '40_8': '40', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season no_9': 'season no', '1_10': '1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'episodes_7': [0], '40_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season no_9': [2], '1_10': [3]} | ['season no', 'season start', 'season end', 'episodes', 'host'] | [['1', '4 august 2002', '8 december 2002', '19', 'alan kohler'], ['2', '9 february 2003', '30 november 2003', '41', 'alan kohler'], ['3', '15 february 2004', '5 december 2004', '41', 'alan kohler'], ['4', '13 february 2005', '4 december 2005', '42', 'alan kohler'], ['5', '12 february 2006', '10 december 2006', '43', 'alan kohler'], ['6', '11 february 2007', '9 december 2007', '43', 'alan kohler']] |
list of journeyman episodes | https://en.wikipedia.org/wiki/List_of_Journeyman_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13426649-1.html.csv | count | according to the list of journeyman episodes , among the episodes written by kevin falls , 2 of them were directed by alex graves . | {'scope': 'subset', 'criterion': 'equal', 'value': 'alex graves', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'kevin falls'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'kevin falls'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; written by ; kevin falls }', 'tointer': 'select the rows whose written by record fuzzily matches to kevin falls .'}, 'directed by', 'alex graves'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose written by record fuzzily matches to kevin falls . among these rows , select the rows whose directed by record fuzzily matches to alex graves .', 'tostr': 'filter_eq { filter_eq { all_rows ; written by ; kevin falls } ; directed by ; alex graves }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; written by ; kevin falls } ; directed by ; alex graves } }', 'tointer': 'select the rows whose written by record fuzzily matches to kevin falls . among these rows , select the rows whose directed by record fuzzily matches to alex graves . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; written by ; kevin falls } ; directed by ; alex graves } } ; 2 } = true', 'tointer': 'select the rows whose written by record fuzzily matches to kevin falls . among these rows , select the rows whose directed by record fuzzily matches to alex graves . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; written by ; kevin falls } ; directed by ; alex graves } } ; 2 } = true | select the rows whose written by record fuzzily matches to kevin falls . among these rows , select the rows whose directed by record fuzzily matches to alex graves . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'written by_6': 6, 'kevin falls_7': 7, 'directed by_8': 8, 'alex graves_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'written by_6': 'written by', 'kevin falls_7': 'kevin falls', 'directed by_8': 'directed by', 'alex graves_9': 'alex graves', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'written by_6': [0], 'kevin falls_7': [0], 'directed by_8': [1], 'alex graves_9': [1], '2_10': [3]} | ['', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['1', 'a love of a lifetime', 'alex graves', 'kevin falls', 'september 24 , 2007', '1anj79', '9.16'], ['2', 'friendly skies', 'alex graves', 'kevin falls', 'october 1 , 2007', '1anj01', '8.23'], ['3', 'game three', 'alex graves', 'tom szentgyorgyi', 'october 8 , 2007', '1anj02', '6.94'], ['4', 'the year of the rabbit', 'laura innes', 'joan b weiss', 'october 15 , 2007', '1anj03', '6.75'], ['5', 'the legend of dylan mccleen', 'allison liddi', 'matt mcguinness', 'october 22 , 2007', '1anj04', '6.06'], ['6', 'keepers', 'andrew bernstein', 'paul redford', 'october 29 , 2007', '1anj05', '5.75'], ['7', 'double down', 'alex graves', 'j r orci', 'november 5 , 2007', '1anj06', '5.13'], ['8', 'winterland', 'helen shaver', 'dana calvo', 'november 12 , 2007', '1anj07', '6.09'], ['9', 'emily ( part 1 )', 'frederick king keller', 'juan carlos coto', 'november 19 , 2007', '1anj08', '5.61'], ['10', 'blowback ( part 2 )', 'karen gaviola', 'kevin falls', 'november 26 , 2007', '1anj09', '6.05'], ['11', 'home by another way', 'lesli linka glatter', 'tom szentgyorgyi', 'december 10 , 2007', '1anj10', '5.28'], ['12', 'the hanged man ( part 1 )', 'steven depaul', 'tracy mcmillan', 'december 17 , 2007', '1anj11', '4.24']] |
jeju international airport | https://en.wikipedia.org/wiki/Jeju_International_Airport | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1783616-4.html.csv | majority | for the majority of other airports in china that jeju airport flies to , there are over 100 aircraft movements . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '100', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'aircraft movements', '100'], 'result': True, 'ind': 0, 'tointer': 'for the aircraft movements records of all rows , most of them are greater than 100 .', 'tostr': 'most_greater { all_rows ; aircraft movements ; 100 } = true'} | most_greater { all_rows ; aircraft movements ; 100 } = true | for the aircraft movements records of all rows , most of them are greater than 100 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'aircraft movements_3': 3, '100_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'aircraft movements_3': 'aircraft movements', '100_4': '100'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'aircraft movements_3': [0], '100_4': [0]} | ['rank', 'airport', 'passengers', 'aircraft movements', 'carriers'] | [['1', 'shanghai , china', '192701', '1465', 'china eastern airlines , jin air'], ['2', 'osaka , japan', '131338', '1157', 'jeju air , korean air'], ['3', 'tokyo , japan', '124296', '734', 'korean air'], ['4', 'beijing , china', '97055', '768', 'china eastern airlines , korean air'], ['5', 'taipei , republic of china ( taiwan )', '73754', '585', 'jin air , transasia airways'], ['6', 'ningbo , china', '44067', '303', 'china eastern airlines , eastar jet'], ['7', 'nagoya , japan', '41460', '416', 'korean air'], ['8', 'harbin , china', '31574', '201', 'china southern airlines , jin air'], ['9', 'changchun , china', '29129', '214', 'china southern airlines'], ['10', 'fukuoka , japan', '27592', '306', 'asiana airlines'], ['11', 'shenyang , china', '26168', '238', 'china southern airlines'], ['12', 'dalian , china', '25359', '204', 'china southern airlines'], ['13', 'hong kong', '24940', '208', 'dragonair'], ['14', 'hangzhou , china', '22191', '165', 'china eastern airlines'], ['15', 'macau', '21278', '178', 'eastar jet'], ['16', 'nanning , china', '17114', '122', 'eastar jet'], ['17', "xi'an , china", '15022', '107', 'jin air'], ['18', 'guangzhou , china', '14983', '95', 'korean air'], ['19', 'hefei , china', '14226', '105', 'eastar jet'], ['20', 'changsha , china', '12947', '105', 'eastar jet']] |
wayne gardner | https://en.wikipedia.org/wiki/Wayne_Gardner | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1861430-3.html.csv | majority | wayne gardner drove with the team rothmans honda for the majority of years . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rothmans honda', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'team', 'rothmans honda'], 'result': True, 'ind': 0, 'tointer': 'for the team records of all rows , most of them fuzzily match to rothmans honda .', 'tostr': 'most_eq { all_rows ; team ; rothmans honda } = true'} | most_eq { all_rows ; team ; rothmans honda } = true | for the team records of all rows , most of them fuzzily match to rothmans honda . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team_3': 3, 'rothmans honda_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team_3': 'team', 'rothmans honda_4': 'rothmans honda'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team_3': [0], 'rothmans honda_4': [0]} | ['year', 'class', 'team', 'machine', 'points', 'wins'] | [['1983', '500cc', 'honda britain', 'ns500', '0', '0'], ['1984', '500cc', 'honda britain', 'ns500', '33', '0'], ['1985', '500cc', 'rothmans honda', 'nsr500', '73', '0'], ['1986', '500cc', 'rothmans honda', 'nsr500', '117', '3'], ['1987', '500cc', 'rothmans honda', 'nsr500', '178', '7'], ['1988', '500cc', 'rothmans honda', 'nsr500', '229', '4'], ['1989', '500cc', 'rothmans honda', 'nsr500', '67', '1'], ['1990', '500cc', 'rothmans honda', 'nsr500', '138', '2'], ['1991', '500cc', 'rothmans honda', 'nsr500', '161', '0'], ['1992', '500cc', 'rothmans honda', 'nsr500', '78', '1']] |
lost souls ( doves album ) | https://en.wikipedia.org/wiki/Lost_Souls_%28Doves_album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1523661-2.html.csv | count | a total of two versions of the lost souls album were released by astralwerks records . | {'scope': 'all', 'criterion': 'equal', 'value': 'astralwerks records', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'astralwerks records'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to astralwerks records .', 'tostr': 'filter_eq { all_rows ; label ; astralwerks records }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; label ; astralwerks records } }', 'tointer': 'select the rows whose label record fuzzily matches to astralwerks records . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; label ; astralwerks records } } ; 2 } = true', 'tointer': 'select the rows whose label record fuzzily matches to astralwerks records . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; label ; astralwerks records } } ; 2 } = true | select the rows whose label record fuzzily matches to astralwerks records . 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, 'label_5': 5, 'astralwerks records_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', 'label_5': 'label', 'astralwerks records_6': 'astralwerks records', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'label_5': [0], 'astralwerks records_6': [0], '2_7': [2]} | ['country', 'date', 'label', 'format', 'catalogue'] | [['united kingdom', '3 april 2000', 'heavenly records', 'cd', 'hvnlp26cd'], ['united kingdom', '3 april 2000', 'heavenly records', 'double lp ( heavyweight vinyl , gatefold sleeve )', 'hvnlp26'], ['united states', '17 october 2000', 'astralwerks records', 'cd ( 3 bonus tracks )', 'asw 50248 ( 724385024825 )'], ['united states', '17 october 2000', 'astralwerks records', 'double lp ( numbered edition , gatefold sleeve )', 'asw 50248 ( 724385024818 )'], ['japan', '7 march 2001', 'toshiba - emi', 'cd ( 3 bonus tracks )', 'tocp - 65682']] |
2011 the dominion tankard | https://en.wikipedia.org/wiki/2011_The_Dominion_Tankard | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29565601-2.html.csv | superlative | in the dominion tankard in 2011 , the highest number of ends won was by chris gardner . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'ends won'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; ends won }'}, 'skip ( club )'], 'result': 'chris gardner ( renfrew )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; ends won } ; skip ( club ) }'}, 'chris gardner ( renfrew )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; ends won } ; skip ( club ) } ; chris gardner ( renfrew ) } = true', 'tointer': 'select the row whose ends won record of all rows is maximum . the skip ( club ) record of this row is chris gardner ( renfrew ) .'} | eq { hop { argmax { all_rows ; ends won } ; skip ( club ) } ; chris gardner ( renfrew ) } = true | select the row whose ends won record of all rows is maximum . the skip ( club ) record of this row is chris gardner ( renfrew ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'ends won_5': 5, 'skip (club)_6': 6, 'chris gardner (renfrew)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'ends won_5': 'ends won', 'skip (club)_6': 'skip ( club )', 'chris gardner (renfrew)_7': 'chris gardner ( renfrew )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'ends won_5': [0], 'skip (club)_6': [1], 'chris gardner (renfrew)_7': [2]} | ['skip ( club )', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends'] | [['peter corner ( brampton )', '8', '2', '69', '54', '41', '36', '8', '11'], ['glenn howard ( coldwater )', '8', '2', '79', '35', '40', '22', '8', '11'], ['greg balsdon ( loonie )', '7', '3', '80', '57', '46', '37', '5', '12'], ['john epping ( donalda )', '7', '3', '76', '64', '43', '41', '5', '10'], ['mark bice ( sarnia )', '6', '4', '70', '76', '45', '44', '8', '7'], ['chris gardner ( renfrew )', '5', '5', '73', '72', '47', '41', '7', '16'], ['dale matchett ( bradford )', '4', '6', '57', '75', '35', '42', '7', '7'], ['mark kean ( annandale )', '3', '7', '53', '67', '43', '35', '12', '8'], ['howard rajala ( rideau )', '3', '7', '67', '71', '43', '48', '5', '9'], ['nick rizzo ( brantford )', '3', '7', '56', '74', '35', '42', '4', '5']] |
1940 vfl season | https://en.wikipedia.org/wiki/1940_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807253-15.html.csv | aggregation | the average crowd size during the 1940 vfl season is 12000 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '12000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '12000', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '12000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 12000 } = true', 'tointer': 'the average of the crowd record of all rows is 12000 .'} | round_eq { avg { all_rows ; crowd } ; 12000 } = true | the average of the crowd record of all rows is 12000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '12000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '12000_5': '12000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '12000_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '10.19 ( 79 )', 'south melbourne', '10.13 ( 73 )', 'glenferrie oval', '8000', '10 august 1940'], ['geelong', '12.15 ( 87 )', 'richmond', '16.11 ( 107 )', 'corio oval', '10000', '10 august 1940'], ['essendon', '10.12 ( 72 )', 'fitzroy', '10.15 ( 75 )', 'windy hill', '18000', '10 august 1940'], ['collingwood', '12.21 ( 93 )', 'north melbourne', '6.17 ( 53 )', 'victoria park', '6500', '10 august 1940'], ['st kilda', '13.9 ( 87 )', 'footscray', '15.22 ( 112 )', 'junction oval', '13000', '10 august 1940'], ['melbourne', '14.12 ( 96 )', 'carlton', '20.13 ( 133 )', 'mcg', '16500', '10 august 1940']] |
eisbären berlin | https://en.wikipedia.org/wiki/Eisb%C3%A4ren_Berlin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1790061-7.html.csv | count | among the seasons when eisbären berlin played more than 48 games , 2 of the years they scored exactly 27 goals . | {'scope': 'subset', 'criterion': 'equal', 'value': '27', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '48'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'games', '48'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; games ; 48 }', 'tointer': 'select the rows whose games record is greater than 48 .'}, 'goals', '27'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose games record is greater than 48 . among these rows , select the rows whose goals record is equal to 27 .', 'tostr': 'filter_eq { filter_greater { all_rows ; games ; 48 } ; goals ; 27 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; games ; 48 } ; goals ; 27 } }', 'tointer': 'select the rows whose games record is greater than 48 . among these rows , select the rows whose goals record is equal to 27 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; games ; 48 } ; goals ; 27 } } ; 2 } = true', 'tointer': 'select the rows whose games record is greater than 48 . among these rows , select the rows whose goals record is equal to 27 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater { all_rows ; games ; 48 } ; goals ; 27 } } ; 2 } = true | select the rows whose games record is greater than 48 . among these rows , select the rows whose goals record is equal to 27 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'games_6': 6, '48_7': 7, 'goals_8': 8, '27_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'games_6': 'games', '48_7': '48', 'goals_8': 'goals', '27_9': '27', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'games_6': [0], '48_7': [0], 'goals_8': [1], '27_9': [1], '2_10': [3]} | ['name', 'season', 'games', 'goals', 'assists', 'points'] | [['name', 'season', 'games', 'goals', 'assists', 'points'], ['mark jooris', '1991 - 1992', '50', '54', '69', '123'], ['steve walker', '2007 - 2008', '53', '27', '58', '85'], ['jiří dopita', '1994 - 1995', '42', '28', '40', '68'], ['thomas graul', '1991 - 1992', '47', '28', '32', '60'], ['alex hicks', '2000 - 2001', '56', '27', '31', '58']] |
2009 copa sudamericana | https://en.wikipedia.org/wiki/2009_Copa_Sudamericana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17282875-3.html.csv | superlative | san lorenzo was the team that scored the most goals in the 2009 copa sudamericana . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team 1'], 'result': 'san lorenzo', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team 1 }'}, 'san lorenzo'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; team 1 } ; san lorenzo } = true', 'tointer': 'select the row whose points record of all rows is maximum . the team 1 record of this row is san lorenzo .'} | eq { hop { argmax { all_rows ; points } ; team 1 } ; san lorenzo } = true | select the row whose points record of all rows is maximum . the team 1 record of this row is san lorenzo . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team 1_6': 6, 'san lorenzo_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 1_6': 'team 1', 'san lorenzo_7': 'san lorenzo'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team 1_6': [1], 'san lorenzo_7': [2]} | ['team 1', 'points', 'team 2', '1st leg', '2nd leg'] | [['cerro porteño', '( a ) 3 - 3', 'goiás', '2 - 0', '1 - 3'], ['vélez sarsfield', '4 - 1', 'unión española', '3 - 2', '2 - 2'], ['river plate', '4 - 1', 'vitória', '4 - 1', '1 - 1'], ['internacional', '1 - 4', 'universidad de chile', '1 - 1', '0 - 1'], ['alianza atlético', '1 - 4', 'fluminense', '2 - 2', '1 - 4'], ['san lorenzo', '6 - 0', 'cienciano', '3 - 0', '2 - 0'], ['ldu quito', '4 - 1', 'lanús', '4 - 0', '1 - 1']] |
.38 special | https://en.wikipedia.org/wiki/.38_Special | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-173103-1.html.csv | superlative | the .357 magnum gun cartridge has the highest muzzle energy in joules . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '12', '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', 'muzzle energy'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; muzzle energy }'}, 'cartridge'], 'result': '.357 magnum', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; muzzle energy } ; cartridge }'}, '.357 magnum'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; muzzle energy } ; cartridge } ; .357 magnum } = true', 'tointer': 'select the row whose muzzle energy record of all rows is maximum . the cartridge record of this row is .357 magnum .'} | eq { hop { argmax { all_rows ; muzzle energy } ; cartridge } ; .357 magnum } = true | select the row whose muzzle energy record of all rows is maximum . the cartridge record of this row is .357 magnum . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'muzzle energy_5': 5, 'cartridge_6': 6, '.357 magnum_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'muzzle energy_5': 'muzzle energy', 'cartridge_6': 'cartridge', '.357 magnum_7': '.357 magnum'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'muzzle energy_5': [0], 'cartridge_6': [1], '.357 magnum_7': [2]} | ['cartridge', 'bullet weight', 'muzzle velocity', 'muzzle energy', 'max pressure'] | [['.38 short colt', 'gr ( g )', 'ft / s ( m / s )', '181ft lbf ( 245 j )', '7500 cup'], ['.38 long colt', 'gr ( g )', 'ft / s ( m / s )', '201ft lbf ( 273 j )', '12000 cup'], ['.38 s & w', 'gr ( g )', 'ft / s ( m / s )', '206ft lbf ( 279 j )', '14500 psi'], ['.38 s & w special', 'gr ( g )', 'ft / s ( m / s )', '310ft lbf ( 420 j )', '17000 psi'], ['.38 special + p', 'gr ( g )', 'ft / s ( m / s )', '351ft lbf ( 476 j )', '20000 psi'], ['.38 special + p +', 'gr ( g )', 'ft / s ( m / s )', '295ft lbf ( 400 j )', '> 20000 psi'], ['.380 acp', 'gr ( g )', 'ft / s ( m / s )', '178ft lbf ( 241 j )', '21500 psi'], ['9x19 mm parabellum', 'gr ( g )', 'ft / s ( m / s )', '420ft lbf ( 570 j )', '39200 psi'], ['9x19 mm parabellum', 'gr ( g )', 'ft / s ( m / s )', '383ft lbf ( 520 j )', '39200 psi'], ['9x18 mm makarov', 'gr ( g )', 'ft / s ( m / s )', '231ft lbf ( 313 j )', '23206 psi'], ['.38 super', 'grains ( g )', 'ft / s ( m / s )', '468ft lbf ( 634 j )', '36500 psi'], ['.357 magnum', 'grains ( g )', 'ft / s ( m / s )', '639ft lbf ( 866 j )', '35000 psi'], ['.357 sig', 'grains ( g )', 'ft / s ( m / s )', '506ft lbf ( 686 j )', '40000 psi']] |
primera división de fútbol profesional apertura 2002 | https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2002 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13013383-1.html.csv | ordinal | san salvador fc scored the second highest amount of goals in the primera división de fútbol profesional apertura 2002 . | {'row': '3', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'goals scored', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; goals scored ; 2 }'}, 'team'], 'result': 'san salvador fc', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; goals scored ; 2 } ; team }'}, 'san salvador fc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; goals scored ; 2 } ; team } ; san salvador fc } = true', 'tointer': 'select the row whose goals scored record of all rows is 2nd maximum . the team record of this row is san salvador fc .'} | eq { hop { nth_argmax { all_rows ; goals scored ; 2 } ; team } ; san salvador fc } = true | select the row whose goals scored record of all rows is 2nd maximum . the team record of this row is san salvador fc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'goals scored_5': 5, '2_6': 6, 'team_7': 7, 'san salvador fc_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', 'goals scored_5': 'goals scored', '2_6': '2', 'team_7': 'team', 'san salvador fc_8': 'san salvador fc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'goals scored_5': [0], '2_6': [0], 'team_7': [1], 'san salvador fc_8': [2]} | ['place', 'team', 'played', 'draw', 'lost', 'goals scored', 'goals conceded', 'points'] | [['1', 'cd fas', '18', '5', '3', '24', '20', '35'], ['2', 'municipal limeño', '18', '4', '5', '33', '19', '31'], ['3', 'san salvador fc', '18', '7', '4', '28', '21', '28'], ['4', 'cd águila', '18', '9', '3', '26', '20', '27'], ['5', 'cd luis ángel firpo', '18', '6', '5', '23', '24', '27'], ['6', 'ad isidro metapán', '18', '6', '7', '22', '24', '21'], ['7', 'cd arcense', '18', '6', '7', '15', '17', '21'], ['8', 'cd atlético balboa', '18', '5', '9', '21', '31', '17'], ['9', 'alianza fc', '18', '7', '8', '17', '22', '16'], ['10', 'cd dragón', '18', '7', '8', '20', '31', '16']] |
2006 - 07 golden state warriors season | https://en.wikipedia.org/wiki/2006%E2%80%9307_Golden_State_Warriors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14677944-8.html.csv | majority | in april of 2007 , the warriors were the visiting team for most of their games . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'warriors', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'visitor', 'warriors'], 'result': True, 'ind': 0, 'tointer': 'for the visitor records of all rows , most of them fuzzily match to warriors .', 'tostr': 'most_eq { all_rows ; visitor ; warriors } = true'} | most_eq { all_rows ; visitor ; warriors } = true | for the visitor records of all rows , most of them fuzzily match to warriors . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'visitor_3': 3, 'warriors_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'visitor_3': 'visitor', 'warriors_4': 'warriors'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'visitor_3': [0], 'warriors_4': [0]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['2007 - 04 - 01', 'grizzlies', '117 - 122', 'warriors', 'jason richardson ( 26 )', '17198', '35 - 39'], ['2007 - 04 - 04', 'warriors', '110 - 99', 'rockets', 'jason richardson ( 26 )', '13929', '36 - 39'], ['2007 - 04 - 06', 'warriors', '116 - 104', 'grizzlies', 'baron davis ( 31 )', '14087', '37 - 39'], ['2007 - 04 - 07', 'warriors', '99 - 112', 'spurs', 'jason richardson ( 23 )', '18797', '37 - 40'], ['2007 - 04 - 09', 'jazz', '102 - 126', 'warriors', 'stephen jackson ( 28 )', '17453', '38 - 40'], ['2007 - 04 - 13', 'warriors', '125 - 108', 'kings', 'stephen jackson ( 26 )', '17317', '39 - 40'], ['2007 - 04 - 15', 'timberwolves', '108 - 121', 'warriors', 'jason richardson ( 32 )', '18223', '40 - 40'], ['2007 - 04 - 17', 'mavericks', '82 - 111', 'warriors', 'mickaël piétrus ( 22 )', '20073', '41 - 40'], ['2007 - 04 - 18', 'warriors', '120 - 98', 'blazers', 'stephen jackson ( 31 )', '19455', '42 - 40']] |
iowa corn cy - hawk series | https://en.wikipedia.org/wiki/Iowa_Corn_Cy-Hawk_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14175075-5.html.csv | majority | the majority of events took place in ames . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ames', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'site', 'ames'], 'result': True, 'ind': 0, 'tointer': 'for the site records of all rows , most of them fuzzily match to ames .', 'tostr': 'most_eq { all_rows ; site ; ames } = true'} | most_eq { all_rows ; site ; ames } = true | for the site records of all rows , most of them fuzzily match to ames . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'site_3': 3, 'ames_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'site_3': 'site', 'ames_4': 'ames'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'site_3': [0], 'ames_4': [0]} | ['date', 'site', 'sport', 'winning team', 'series'] | [['september 4 , 2007', 'cedar rapids', 'm golf', 'iowa state', 'iowa state 2 - 0'], ['september 8 , 2007', 'des moines', 'volleyball', 'iowa state', 'iowa state 4 - 0'], ['september 9 , 2007', 'iowa city', 'w soccer', 'tie', 'iowa state 5 - 1'], ['september 15 , 2007', 'ames', 'football', 'iowa state', 'iowa state 8 - 1'], ['november 10 , 2007', 'peoria', 'm cross country', 'iowa state', 'iowa state 10 - 1'], ['november 10 , 2007', 'peoria', 'w cross country', 'iowa', 'iowa state 10 - 3'], ['december 5 , 2007', 'ames', 'w basketball', 'iowa state', 'iowa state 12 - 3'], ['december 7 , 2007', 'ames', 'w swimming', 'iowa state', 'iowa state 14 - 3'], ['december 8 , 2007', 'ames', 'm basketball', 'iowa state', 'iowa state 16 - 3'], ['december 9 , 2007', 'ames', 'wrestling', 'iowa', 'iowa state 16 - 5'], ['february 22 , 2008', 'ames', 'w gymnastics', 'iowa state', 'iowa state 18 - 5'], ['march 7 , 2008', 'iowa city', 'w gymnastics', 'iowa', 'iowa state 18 - 7'], ['april 1 , 2008', 'ames', 'softball', 'iowa', 'iowa state 18 - 9']] |
chicago throwbacks | https://en.wikipedia.org/wiki/Chicago_Throwbacks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10595672-1.html.csv | count | james booyer had a total of two high rebounds performances for the chicago throwbacks . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'james booyer', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'james booyer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high rebounds record fuzzily matches to james booyer .', 'tostr': 'filter_eq { all_rows ; high rebounds ; james booyer }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high rebounds ; james booyer } }', 'tointer': 'select the rows whose high rebounds record fuzzily matches to james booyer . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high rebounds ; james booyer } } ; 2 } = true', 'tointer': 'select the rows whose high rebounds record fuzzily matches to james booyer . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; high rebounds ; james booyer } } ; 2 } = true | select the rows whose high rebounds record fuzzily matches to james booyer . 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, 'high rebounds_5': 5, 'james booyer_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', 'high rebounds_5': 'high rebounds', 'james booyer_6': 'james booyer', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'james booyer_6': [0], '2_7': [2]} | ['date', 'opponent', 'home / away', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['january 2', 'battle creek knights', 'away', '113 - 120', 'stanley thomas ( 23 )', "michael o'neal ( 8 )", 'imari sawyer ( 7 )', 'kellogg arena ( 1257 )', '0 - 1'], ['january 4', 'detroit panthers', 'away', '110 - 106', 'stanley thomas ( 24 )', 'stanley thomas & marcus jackson ( 9 )', 'imari sawyer ( 8 )', 'groves high school', '1 - 1'], ['january 10', 'battle creek knights', 'home', '106 - 94', 'imari sawyer ( 18 )', 'dameon mason ( 7 )', 'imari sawyer ( 5 )', 'attack athletics', '1 - 2'], ['january 12', 'quebec kebs', 'home', '91 - 92', 'dameon mason ( 19 )', 'stanley thomas & michael herman ( 7 )', 'imari sawyer ( 10 )', 'attack athletics', '2 - 2'], ['january 18', 'detroit panthers', 'home', '107 - 119', 'stanley thomas ( 21 )', 'james booyer ( 11 )', "michael o'neal ( 3 )", 'attack athletics', '3 - 2'], ['january 23', 'mid - michigan destroyers', 'away', '105 - 116', 'anthony simmons ( 27 )', 'anthony simmons ( 10 )', 'stanley thomas ( 3 )', 'bay city western high school', '3 - 3'], ['january 24', 'rochester razorsharks', 'home', '112 - 83', 'dameon mason ( 22 )', 'james booyer ( 12 )', 'stanley thomas & michael herman ( 3 )', 'attack athletics', '3 - 4'], ['january 26', 'mid - michigan destroyers', 'home', '117 - 104', 'michael herman ( 28 )', 'amir major ( 16 )', 'imari sawyer ( 10 )', 'attack athletics', '3 - 5'], ['february 6', 'battle creek knights', 'away', '112 - 117', 'stanley thomas ( 29 )', 'anthony simmons ( 11 )', 'michael herman ( 6 )', 'kellogg arena', '3 - 6'], ['february 8', 'detroit panthers', 'away', '114 - 113', 'dameon mason ( 24 )', 'casey love ( 13 )', 'imari sawyer ( 8 )', 'groves high school', '4 - 6'], ['february 13', 'mid - michigan destroyers', 'home', '108 - 121', 'stanley thomas ( 32 )', 'stanley thomas ( 9 )', 'imari sawyer ( 9 )', 'attack athletics', '5 - 6'], ['february 20', 'quebec kebs', 'away', '109 - 104', 'imari sawyer ( 28 )', 'anthony simmons ( 8 )', 'imari sawyer ( 11 )', 'pavillon de la jeunesse', '6 - 6'], ['february 22', 'augusta groove', 'away', '105 - 119', 'willie mitchell ( 25 )', 'imari sawyer ( 9 )', "michael o'neal ( 4 )", 'richmond academy', '6 - 7'], ['february 27', 'manchester millrats', 'away', '105 - 124', 'dameon mason ( 22 )', 'casey love ( 12 )', 'imari sawyer & michael herman ( 7 )', 'southern new hampshire fieldhouse', '6 - 8'], ['march 6', 'detroit panthers', 'home', '123 - 116', 'dameon mason ( 28 )', 'willie mitchell & dameon mason ( 4 )', 'imari sawyer ( 10 )', 'attack athletics', '6 - 9'], ['march 8', 'battle creek knights', 'home', '114 - 109', 'casey love ( 22 )', 'willie mitchell ( 8 )', 'imari sawyer ( 11 )', 'attack athletics', '6 - 10'], ['march 13', 'battle creek knights', 'home', '120 - 123', 'stanley thomas ( 46 )', 'casey love ( 15 )', 'imari sawyer ( 10 )', 'attack athletics', '6 - 11'], ['march 15', 'manchester millrats', 'home', '122 - 99', 'stanley thomas ( 25 )', 'stanley thomas ( 11 )', 'imari sawyer ( 8 )', 'attack athletics', '6 - 12'], ['march 27', 'battle creek knights', 'home', '121 - 95', 'casey love ( 28 )', 'casey love ( 11 )', 'imari sawyer ( 10 )', 'attack athletics', '6 - 13']] |
united states house of representatives elections , 1970 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1970 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341718-36.html.csv | comparative | of the incumbents in the 1970 election for the united states house of representatives , the date that frank t bow was first elected was 18 years before louis stokes was first elected . | {'row_1': '6', 'row_2': '8', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '18 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'frank t bow'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to frank t bow .', 'tostr': 'filter_eq { all_rows ; incumbent ; frank t bow }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; frank t bow } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to frank t bow . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'louis stokes'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to louis stokes .', 'tostr': 'filter_eq { all_rows ; incumbent ; louis stokes }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; louis stokes } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to louis stokes . take the first elected record of this row .'}], 'result': '-18 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; incumbent ; frank t bow } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; louis stokes } ; first elected } }'}, '-18 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; incumbent ; frank t bow } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; louis stokes } ; first elected } } ; -18 years } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to frank t bow . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to louis stokes . take the first elected record of this row . the second record is 18 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; incumbent ; frank t bow } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; louis stokes } ; first elected } } ; -18 years } = true | select the rows whose incumbent record fuzzily matches to frank t bow . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to louis stokes . take the first elected record of this row . the second record is 18 years larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'incumbent_8': 8, 'frank t bow_9': 9, 'first elected_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'incumbent_12': 12, 'louis stokes_13': 13, 'first elected_14': 14, '-18 years_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'incumbent_8': 'incumbent', 'frank t bow_9': 'frank t bow', 'first elected_10': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'incumbent_12': 'incumbent', 'louis stokes_13': 'louis stokes', 'first elected_14': 'first elected', '-18 years_15': '-18 years'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'incumbent_8': [0], 'frank t bow_9': [0], 'first elected_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'incumbent_12': [1], 'louis stokes_13': [1], 'first elected_14': [3], '-18 years_15': [5]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['ohio 5', 'del latta', 'republican', '1958', 're - elected', 'del latta ( r ) 71.1 % carl g sherer ( d ) 28.9 %'], ['ohio 6', 'bill harsha', 'republican', '1960', 're - elected', 'bill harsha ( r ) 67.8 % raymond h stevens ( d ) 32.2 %'], ['ohio 8', 'jackson edward betts', 'republican', '1950', 're - elected', 'jackson edward betts ( r ) unopposed'], ['ohio 10', 'clarence e miller', 'republican', '1966', 're - elected', 'clarence e miller ( r ) 66.5 % doug arnett ( d ) 33.5 %'], ['ohio 11', 'j william stanton', 'republican', '1964', 're - elected', 'j william stanton ( r ) 68.2 % ralph rudd ( d ) 31.8 %'], ['ohio 16', 'frank t bow', 'republican', '1950', 're - elected', 'frank t bow ( r ) 56.2 % virgil l musser ( d ) 43.8 %'], ['ohio 18', 'wayne l hays', 'democratic', '1948', 're - elected', 'wayne l hays ( d ) 68.3 % robert stewart ( r ) 31.7 %'], ['ohio 21', 'louis stokes', 'democratic', '1968', 're - elected', 'louis stokes ( d ) 77.6 % bill mack ( r ) 22.4 %']] |
1965 american football league draft | https://en.wikipedia.org/wiki/1965_American_Football_League_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-7.html.csv | unique | in the 1965 american football league draft , the only player drafted from pittsburgh was marty shottenheimer . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'pittsburgh', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'pittsburgh'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to pittsburgh .', 'tostr': 'filter_eq { all_rows ; college ; pittsburgh }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; pittsburgh } }', 'tointer': 'select the rows whose college record fuzzily matches to pittsburgh . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'pittsburgh'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to pittsburgh .', 'tostr': 'filter_eq { all_rows ; college ; pittsburgh }'}, 'player'], 'result': 'marty schottenheimer', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; pittsburgh } ; player }'}, 'marty schottenheimer'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; pittsburgh } ; player } ; marty schottenheimer }', 'tointer': 'the player record of this unqiue row is marty schottenheimer .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; pittsburgh } } ; eq { hop { filter_eq { all_rows ; college ; pittsburgh } ; player } ; marty schottenheimer } } = true', 'tointer': 'select the rows whose college record fuzzily matches to pittsburgh . there is only one such row in the table . the player record of this unqiue row is marty schottenheimer .'} | and { only { filter_eq { all_rows ; college ; pittsburgh } } ; eq { hop { filter_eq { all_rows ; college ; pittsburgh } ; player } ; marty schottenheimer } } = true | select the rows whose college record fuzzily matches to pittsburgh . there is only one such row in the table . the player record of this unqiue row is marty schottenheimer . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'pittsburgh_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'marty schottenheimer_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'pittsburgh_8': 'pittsburgh', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'marty schottenheimer_10': 'marty schottenheimer'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'pittsburgh_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'marty schottenheimer_10': [3]} | ['pick', 'team', 'player', 'position', 'college'] | [['49', 'denver broncos', 'jim garcia', 'defensive end', 'purdue'], ['50', 'kansas city chiefs ( from houston oilers )', 'gloster richardson', 'wide receiver', 'jackson state'], ['51', 'new york jets ( from oakland raiders )', 'archie roberts', 'quarterback', 'columbia'], ['52', 'new york jets', 'jim harris , jr', 'defensive tackle', 'utah state'], ['53', 'kansas city chiefs', 'lou bobich', 'defensive back', 'michigan state'], ['54', 'san diego chargers', 'jack snow', 'wide receiver', 'notre dame'], ['55', 'boston patriots', 'tom neville', 'defensive tackle', 'mississippi state'], ['56', 'buffalo bills', 'marty schottenheimer', 'linebacker', 'pittsburgh']] |
campbeltown and machrihanish light railway | https://en.wikipedia.org/wiki/Campbeltown_and_Machrihanish_Light_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1820430-1.html.csv | unique | the princess railway was the only railway built by kerr stuart . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'kerr stuart', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'kerr stuart'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose builder record fuzzily matches to kerr stuart .', 'tostr': 'filter_eq { all_rows ; builder ; kerr stuart }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; builder ; kerr stuart } }', 'tointer': 'select the rows whose builder record fuzzily matches to kerr stuart . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'kerr stuart'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose builder record fuzzily matches to kerr stuart .', 'tostr': 'filter_eq { all_rows ; builder ; kerr stuart }'}, 'name'], 'result': 'princess', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; builder ; kerr stuart } ; name }'}, 'princess'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; builder ; kerr stuart } ; name } ; princess }', 'tointer': 'the name record of this unqiue row is princess .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; builder ; kerr stuart } } ; eq { hop { filter_eq { all_rows ; builder ; kerr stuart } ; name } ; princess } } = true', 'tointer': 'select the rows whose builder record fuzzily matches to kerr stuart . there is only one such row in the table . the name record of this unqiue row is princess .'} | and { only { filter_eq { all_rows ; builder ; kerr stuart } } ; eq { hop { filter_eq { all_rows ; builder ; kerr stuart } ; name } ; princess } } = true | select the rows whose builder record fuzzily matches to kerr stuart . there is only one such row in the table . the name record of this unqiue row is princess . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'builder_7': 7, 'kerr stuart_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'princess_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'builder_7': 'builder', 'kerr stuart_8': 'kerr stuart', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'princess_10': 'princess'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'builder_7': [0], 'kerr stuart_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'princess_10': [3]} | ['name', 'builder', 'type', 'works number', 'built'] | [['pioneer', 'andrew barclay & co', '0 - 4 - 0 wt ( converted to 0 - 4 - 2 wt )', 'unknown', '1876'], ['chevalier', 'andrew barclay & co', '0 - 4 - 0 st ( converted to 0 - 4 - 2 st )', '269', '1885'], ['princess', 'kerr stuart', '0 - 4 - 2 t', '717', '1900'], ['argyll', 'andrew barclay & co', '0 - 6 - 2 t', '1049', '1906'], ['atlantic', 'andrew barclay & co', '0 - 6 - 2 t', '1098', '1907']] |
equatorial bulge | https://en.wikipedia.org/wiki/Equatorial_bulge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-143023-1.html.csv | count | among the planets with equatorial bulge above 1000 km , 2 of them have polar diameter greater than 100,000 km . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '100,000', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '1000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'equatorial bulge', '1000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; equatorial bulge ; 1000 }', 'tointer': 'select the rows whose equatorial bulge record is greater than 1000 .'}, 'polar diameter', '100,000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose equatorial bulge record is greater than 1000 . among these rows , select the rows whose polar diameter record is greater than 100,000 .', 'tostr': 'filter_greater { filter_greater { all_rows ; equatorial bulge ; 1000 } ; polar diameter ; 100,000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_greater { all_rows ; equatorial bulge ; 1000 } ; polar diameter ; 100,000 } }', 'tointer': 'select the rows whose equatorial bulge record is greater than 1000 . among these rows , select the rows whose polar diameter record is greater than 100,000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_greater { all_rows ; equatorial bulge ; 1000 } ; polar diameter ; 100,000 } } ; 2 } = true', 'tointer': 'select the rows whose equatorial bulge record is greater than 1000 . among these rows , select the rows whose polar diameter record is greater than 100,000 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_greater { all_rows ; equatorial bulge ; 1000 } ; polar diameter ; 100,000 } } ; 2 } = true | select the rows whose equatorial bulge record is greater than 1000 . among these rows , select the rows whose polar diameter record is greater than 100,000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'equatorial bulge_6': 6, '1000_7': 7, 'polar diameter_8': 8, '100,000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'equatorial bulge_6': 'equatorial bulge', '1000_7': '1000', 'polar diameter_8': 'polar diameter', '100,000_9': '100,000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'equatorial bulge_6': [0], '1000_7': [0], 'polar diameter_8': [1], '100,000_9': [1], '2_10': [3]} | ['body', 'equatorial diameter', 'polar diameter', 'equatorial bulge', 'flattening ratio'] | [['earth', '12756.28 km', '12713.56 km', '42.72 km', '1:298.2575'], ['mars', '6805 km', '6754.8 km', '50.2 km', '1:135.56'], ['ceres', '975 km', '909 km', '66 km', '1:14.77'], ['jupiter', '143884 km', '133709 km', '10175 km', '1:14.14'], ['saturn', '120536 km', '108728 km', '11808 km', '1:10.21'], ['uranus', '51118 km', '49946 km', '1172 km', '1:43.62'], ['neptune', '49528 km', '48682 km', '846 km', '1:58.54']] |
cryengine | https://en.wikipedia.org/wiki/CryEngine | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1241866-4.html.csv | unique | star citizen was the only game made in the cryengine game engine developed by cloud imperium games corporation . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'cloud imperium games corporation', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'developer', 'cloud imperium games corporation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose developer record fuzzily matches to cloud imperium games corporation .', 'tostr': 'filter_eq { all_rows ; developer ; cloud imperium games corporation }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; developer ; cloud imperium games corporation } }', 'tointer': 'select the rows whose developer record fuzzily matches to cloud imperium games corporation . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'developer', 'cloud imperium games corporation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose developer record fuzzily matches to cloud imperium games corporation .', 'tostr': 'filter_eq { all_rows ; developer ; cloud imperium games corporation }'}, 'title'], 'result': 'star citizen', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; developer ; cloud imperium games corporation } ; title }'}, 'star citizen'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; developer ; cloud imperium games corporation } ; title } ; star citizen }', 'tointer': 'the title record of this unqiue row is star citizen .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; developer ; cloud imperium games corporation } } ; eq { hop { filter_eq { all_rows ; developer ; cloud imperium games corporation } ; title } ; star citizen } } = true', 'tointer': 'select the rows whose developer record fuzzily matches to cloud imperium games corporation . there is only one such row in the table . the title record of this unqiue row is star citizen .'} | and { only { filter_eq { all_rows ; developer ; cloud imperium games corporation } } ; eq { hop { filter_eq { all_rows ; developer ; cloud imperium games corporation } ; title } ; star citizen } } = true | select the rows whose developer record fuzzily matches to cloud imperium games corporation . there is only one such row in the table . the title record of this unqiue row is star citizen . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'developer_7': 7, 'cloud imperium games corporation_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'star citizen_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'developer_7': 'developer', 'cloud imperium games corporation_8': 'cloud imperium games corporation', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'star citizen_10': 'star citizen'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'developer_7': [0], 'cloud imperium games corporation_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'star citizen_10': [3]} | ['title', 'year', 'developer', 'publisher', 'platform'] | [['homefront 2', '2014', 'crytek uk', 'crytek', 'tba'], ['ryse : son of rome', '2013', 'crytek gmbh', 'microsoft studios', 'xbox one'], ['star citizen', '2014', 'cloud imperium games corporation', 'cloud imperium games corporation', 'microsoft windows'], ['unannounced arkane studios title', 'tba', 'arkane studios', 'bethesda softworks', 'tba'], ['unannounced battlecry studios title', 'tba', 'battlecry studios', 'bethesda softworks', 'tba']] |
maura viceconte | https://en.wikipedia.org/wiki/Maura_Viceconte | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15671631-1.html.csv | count | maura viceconte finished in 1st place of marathons a total of six times . | {'scope': 'all', 'criterion': 'equal', 'value': '1st', 'result': '6', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', '1st'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to 1st .', 'tostr': 'filter_eq { all_rows ; position ; 1st }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; 1st } }', 'tointer': 'select the rows whose position record fuzzily matches to 1st . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; 1st } } ; 6 } = true', 'tointer': 'select the rows whose position record fuzzily matches to 1st . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; position ; 1st } } ; 6 } = true | select the rows whose position record fuzzily matches to 1st . 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, 'position_5': 5, '1st_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', 'position_5': 'position', '1st_6': '1st', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], '1st_6': [0], '6_7': [2]} | ['year', 'competition', 'venue', 'position', 'event', 'notes'] | [['1995', 'venice marathon', 'venice , italy', '1st', 'marathon', '2:29:11'], ['1996', 'olympic games', 'atlanta , united states', 'n / a', 'marathon', 'dnf'], ['1997', 'monaco marathon', 'monte carlo , monaco', '1st', 'marathon', '2:28:16'], ['1998', 'italian marathon', 'carpi , italy', '1st', 'marathon', '2:31:23'], ['1998', 'european championships', 'budapest , hungary', '3rd', 'marathon', '2:28:31'], ['1999', 'rome city marathon', 'rome , italy', '1st', 'marathon', '2:29:36'], ['2000', 'vienna marathon', 'vienna , austria', '1st', 'marathon', '2:23:47'], ['2000', 'olympic games', 'sydney , australia', '12th', 'marathon', '2:29:26'], ['2001', 'prague marathon', 'prague , czech republic', '1st', 'marathon', '2:26:33']] |
who dares wins ( uk game show ) | https://en.wikipedia.org/wiki/Who_Dares_Wins_%28UK_game_show%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14523485-9.html.csv | unique | in who dares wins , when the top prize was at least 10000 , the only time the host was jason gunn was when the channel was tvnz . | {'scope': 'subset', 'row': '4', 'col': '3', 'col_other': '4,6', 'criterion': 'equal', 'value': 'jason gunn', 'subset': {'col': '6', 'criterion': 'greater_than_eq', 'value': '10000'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'top prize', '10000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; top prize ; 10000 }', 'tointer': 'select the rows whose top prize record is greater than or equal to 10000 .'}, 'host', 'jason gunn'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose top prize record is greater than or equal to 10000 . among these rows , select the rows whose host record fuzzily matches to jason gunn .', 'tostr': 'filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } }', 'tointer': 'select the rows whose top prize record is greater than or equal to 10000 . among these rows , select the rows whose host record fuzzily matches to jason gunn . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'top prize', '10000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; top prize ; 10000 }', 'tointer': 'select the rows whose top prize record is greater than or equal to 10000 .'}, 'host', 'jason gunn'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose top prize record is greater than or equal to 10000 . among these rows , select the rows whose host record fuzzily matches to jason gunn .', 'tostr': 'filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn }'}, 'channel'], 'result': 'tvnz', 'ind': 3, 'tostr': 'hop { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } ; channel }'}, 'tvnz'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } ; channel } ; tvnz }', 'tointer': 'the channel record of this unqiue row is tvnz .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } } ; eq { hop { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } ; channel } ; tvnz } } = true', 'tointer': 'select the rows whose top prize record is greater than or equal to 10000 . among these rows , select the rows whose host record fuzzily matches to jason gunn . there is only one such row in the table . the channel record of this unqiue row is tvnz .'} | and { only { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } } ; eq { hop { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } ; channel } ; tvnz } } = true | select the rows whose top prize record is greater than or equal to 10000 . among these rows , select the rows whose host record fuzzily matches to jason gunn . there is only one such row in the table . the channel record of this unqiue row is tvnz . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_7': 7, 'top prize_8': 8, '10000_9': 9, 'host_10': 10, 'jason gunn_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'channel_12': 12, 'tvnz_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_7': 'all_rows', 'top prize_8': 'top prize', '10000_9': '10000', 'host_10': 'host', 'jason gunn_11': 'jason gunn', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'channel_12': 'channel', 'tvnz_13': 'tvnz'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_greater_eq_0': [1], 'all_rows_7': [0], 'top prize_8': [0], '10000_9': [0], 'host_10': [1], 'jason gunn_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'channel_12': [3], 'tvnz_13': [4]} | ['country', 'local name', 'host', 'channel', 'year aired', 'top prize'] | [['australia', 'the rich list', "andrew o'keefe", 'seven network', '2007 - 2009', '250000'], ['france', 'la liste gagnante', 'patrice laffont', 'france 3', '2009', '5000'], ['germany', 'rich list', 'kai pflaume', 'sat1', '2007 - present', '100000'], ['new zealand', 'the rich list', 'jason gunn', 'tvnz', '2007 - present', '50000'], ['united kingdom', 'who dares wins', 'nick knowles', 'bbc one', '2007 - present', '50000'], ['united states', 'the rich list', 'eamonn holmes', 'fox', '2006', '250000']] |
thrust specific fuel consumption | https://en.wikipedia.org/wiki/Thrust_specific_fuel_consumption | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-172348-2.html.csv | aggregation | the thrust engines have an average effective exhaust velocity of 33869 meters per second . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '33869', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'effective exhaust velocity ( m / s )'], 'result': '33869', 'ind': 0, 'tostr': 'avg { all_rows ; effective exhaust velocity ( m / s ) }'}, '33869'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; effective exhaust velocity ( m / s ) } ; 33869 } = true', 'tointer': 'the average of the effective exhaust velocity ( m / s ) record of all rows is 33869 .'} | round_eq { avg { all_rows ; effective exhaust velocity ( m / s ) } ; 33869 } = true | the average of the effective exhaust velocity ( m / s ) record of all rows is 33869 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'effective exhaust velocity (m / s)_4': 4, '33869_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'effective exhaust velocity (m / s)_4': 'effective exhaust velocity ( m / s )', '33869_5': '33869'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'effective exhaust velocity (m / s)_4': [0], '33869_5': [1]} | ['engine type', 'scenario', 'sfc in lb / ( lbf h )', 'sfc in g / ( kn s )', 'specific impulse ( s )', 'effective exhaust velocity ( m / s )'] | [['nk - 33 rocket engine', 'vacuum', '10.9', '309', '331', '3240'], ['ssme rocket engine', 'space shuttle vacuum', '7.95', '225', '453', '4423'], ['ramjet', 'mach 1', '4.5', '127', '800', '7877'], ['j - 58 turbojet', 'sr - 71 at mach 3.2 ( wet )', '1.9', '53.8', '1900', '18587'], ['rolls - royce / snecma olympus 593', 'concorde mach 2 cruise ( dry )', '1.195', '33.8', '3012', '29553'], ['cf6 - 80c2b1f turbofan', 'boeing 747 - 400 cruise', '0.605', '17.1', '5950', '58400'], ['general electric cf6 turbofan', 'sea level', '0.307', '8.696', '11700', '115000']] |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17596418-4.html.csv | unique | burke was the only player transfered to cardiff city f.c. during the 2008 - 09 winter trade window . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'winter', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'transfer window', 'winter'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose transfer window record fuzzily matches to winter .', 'tostr': 'filter_eq { all_rows ; transfer window ; winter }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; transfer window ; winter } }', 'tointer': 'select the rows whose transfer window record fuzzily matches to winter . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'transfer window', 'winter'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose transfer window record fuzzily matches to winter .', 'tostr': 'filter_eq { all_rows ; transfer window ; winter }'}, 'name'], 'result': 'burke', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; transfer window ; winter } ; name }'}, 'burke'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; transfer window ; winter } ; name } ; burke }', 'tointer': 'the name record of this unqiue row is burke .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; transfer window ; winter } } ; eq { hop { filter_eq { all_rows ; transfer window ; winter } ; name } ; burke } } = true', 'tointer': 'select the rows whose transfer window record fuzzily matches to winter . there is only one such row in the table . the name record of this unqiue row is burke .'} | and { only { filter_eq { all_rows ; transfer window ; winter } } ; eq { hop { filter_eq { all_rows ; transfer window ; winter } ; name } ; burke } } = true | select the rows whose transfer window record fuzzily matches to winter . there is only one such row in the table . the name record of this unqiue row is burke . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'transfer window_7': 7, 'winter_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'burke_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'transfer window_7': 'transfer window', 'winter_8': 'winter', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'burke_10': 'burke'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'transfer window_7': [0], 'winter_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'burke_10': [3]} | ['name', 'country', 'type', 'moving from', 'transfer window', 'ends', 'transfer fee', 'source'] | [['comminges', 'gpe', 'free transfer', 'swindon town', 'summer', '2010', 'free', 'bbc sport'], ['kennedy', 'irl', 'free transfer', 'crystal palace', 'summer', '2010', 'free', 'bbc sport'], ['enckelman', 'fin', 'free transfer', 'blackburn rovers', 'summer', '2010', 'free', 'bbc sport'], ['dennehy', 'irl', 'free transfer', 'everton', 'summer', '2010', 'free', 'bbc sport'], ['mccormack', 'sco', 'transfer', 'motherwell', 'summer', '2010', '120000', 'bbc sport'], ['bothroyd', 'eng', 'transfer', 'wolverhampton wanderers', 'summer', '2011', '350000', 'bbc sport'], ['gyepes', 'hun', 'transfer', 'northampton town', 'summer', '2010', '200000', 'bbc sport'], ['burke', 'sco', 'free transfer', 'rangers', 'winter', '2011', 'free', 'bbc sport']] |
darya pchelnik | https://en.wikipedia.org/wiki/Darya_Pchelnik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12583435-1.html.csv | unique | the world athletics final was the only event that took place in greece . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'greece', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'greece'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to greece .', 'tostr': 'filter_eq { all_rows ; venue ; greece }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; greece } }', 'tointer': 'select the rows whose venue record fuzzily matches to greece . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'greece'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to greece .', 'tostr': 'filter_eq { all_rows ; venue ; greece }'}, 'competition'], 'result': 'world athletics final', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; greece } ; competition }'}, 'world athletics final'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; greece } ; competition } ; world athletics final }', 'tointer': 'the competition record of this unqiue row is world athletics final .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; greece } } ; eq { hop { filter_eq { all_rows ; venue ; greece } ; competition } ; world athletics final } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to greece . there is only one such row in the table . the competition record of this unqiue row is world athletics final .'} | and { only { filter_eq { all_rows ; venue ; greece } } ; eq { hop { filter_eq { all_rows ; venue ; greece } ; competition } ; world athletics final } } = true | select the rows whose venue record fuzzily matches to greece . there is only one such row in the table . the competition record of this unqiue row is world athletics final . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'greece_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'competition_9': 9, 'world athletics final_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'greece_8': 'greece', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'competition_9': 'competition', 'world athletics final_10': 'world athletics final'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'greece_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'competition_9': [2], 'world athletics final_10': [3]} | ['year', 'competition', 'venue', 'position', 'notes'] | [['2005', 'world championships', 'helsinki , finland', '15th ( q )', '65.54 m'], ['2005', 'universiade', 'izmir , turkey', '10th', '63.89 m'], ['2007', 'universiade', 'bangkok , thailand', '1st', '68.74 m'], ['2008', 'olympic games', 'beijing , china', '4th', '73.65 m'], ['2009', 'world championships', 'berlin , germany', '15th ( q )', '69.30 m'], ['2009', 'world athletics final', 'thessaloniki , greece', '5th', '69.00 m'], ['2010', 'european championships', 'barcelona , spain', '-', 'nm']] |
christian dailly | https://en.wikipedia.org/wiki/Christian_Dailly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1317736-1.html.csv | superlative | christian dailly scored the highest number of international goals on may 23 , 2002 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', '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', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'date'], 'result': '23 may 2002', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; date }'}, '23 may 2002'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; date } ; 23 may 2002 } = true', 'tointer': 'select the row whose score record of all rows is maximum . the date record of this row is 23 may 2002 .'} | eq { hop { argmax { all_rows ; score } ; date } ; 23 may 2002 } = true | select the row whose score record of all rows is maximum . the date record of this row is 23 may 2002 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'date_6': 6, '23 may 2002_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'date_6': 'date', '23 may 2002_7': '23 may 2002'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'date_6': [1], '23 may 2002_7': [2]} | ['goal', 'date', 'venue', 'score', 'result', 'competition'] | [['1', '1 june 1997', "ta ' qali , malta", '1 - 0', '3 - 2', 'friendly'], ['2', '17 april 2002', 'aberdeen , scotland', '1 - 0', '1 - 2', 'friendly'], ['3', '23 may 2002', 'hong kong , china', '3 - 0', '4 - 0', 'friendly'], ['4', '12 october 2002', 'reykjavík , iceland', '1 - 0', '2 - 0', 'uefa euro 2004 qualifying'], ['5', '4 june 2005', 'glasgow , scotland', '1 - 0', '2 - 0', 'fifa world cup 2006 qualifying'], ['6', '6 september 2006', 'kaunas , lithuania', '1 - 0', '2 - 1', 'uefa euro 2008 qualifying']] |
1990 major league baseball draft | https://en.wikipedia.org/wiki/1990_Major_League_Baseball_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18132662-2.html.csv | count | during the 1990 mlb draft , 6 players were selected for the rhp position . | {'scope': 'all', 'criterion': 'equal', 'value': 'rhp', 'result': '6', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'rhp'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to rhp .', 'tostr': 'filter_eq { all_rows ; position ; rhp }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; rhp } }', 'tointer': 'select the rows whose position record fuzzily matches to rhp . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; rhp } } ; 6 } = true', 'tointer': 'select the rows whose position record fuzzily matches to rhp . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; position ; rhp } } ; 6 } = true | select the rows whose position record fuzzily matches to rhp . 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, 'position_5': 5, 'rhp_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', 'position_5': 'position', 'rhp_6': 'rhp', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'rhp_6': [0], '6_7': [2]} | ['pick', 'player', 'team', 'position', 'hometown / school'] | [['27', 'mike zimmerman', 'pittsburgh pirates', 'rhp', 'university of south alabama'], ['28', 'gabe white', 'montreal expos', 'rhp', 'sebring , florida'], ['29', 'midre cummings', 'minnesota twins', 'of', 'miami , florida'], ['30', 'paul ellis', 'st louis cardinals', 'c', 'university of california , los angeles'], ['31', 'brian williams', 'houston astros', 'rhp', 'university of south carolina'], ['32', 'scott sanders', 'san diego padres', 'rhp', 'nicholls state university'], ['33', 'marcus jensen', 'san francisco giants', 'c', 'oakland , california'], ['34', 'dave zancanaro', 'oakland athletics', 'lhp', 'university of california , los angeles'], ['35', 'stan spencer', 'montreal expos', 'rhp', 'stanford university'], ['36', 'kirk dressendorfer', 'oakland athletics', 'rhp', 'university of texas at austin'], ['37', 'ben van ryn', 'montreal expos', 'lhp', 'kendallville , indiana'], ['38', 'tony manahan', 'seattle mariners', 'ss', 'arizona state university'], ['39', 'samuel hence', 'cleveland indians', 'of', 'wiggins , mississippi'], ['40', 'stan robertson', 'montreal expos', 'of', 'plainview , texas']] |
2008 - 09 denver nuggets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Denver_Nuggets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17355408-6.html.csv | majority | the 2008-09 denver nuggets won most of their matches in the month of january . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; score ; w } = true'} | most_eq { all_rows ; score ; w } = true | for the score 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, 'score_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], 'w_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['34', 'january 2', 'oklahoma city', 'w 122 - 120 ( ot )', 'carmelo anthony ( 31 )', 'chauncey billups , anthony carter ( 7 )', 'ford center 18613', '22 - 12'], ['35', 'january 3', 'new orleans', 'w 105 - 100 ( ot )', 'carmelo anthony ( 22 )', 'chauncey billups ( 6 )', 'pepsi center 19614', '23 - 12'], ['36', 'january 5', 'indiana', 'w 135 - 115 ( ot )', 'kenyon martin ( 25 )', 'chauncey billups ( 11 )', 'pepsi center 14255', '24 - 12'], ['37', 'january 7', 'miami', 'w 108 - 97 ( ot )', 'chauncey billups , j r smith , linas kleiza ( 21 )', 'anthony carter ( 9 )', 'pepsi center 15459', '25 - 12'], ['38', 'january 9', 'detroit', 'l 90 - 93 ( ot )', 'chauncey billups ( 30 )', 'chauncey billups , j r smith ( 4 )', 'pepsi center 19682', '25 - 13'], ['39', 'january 13', 'dallas', 'w 99 - 97 ( ot )', 'chauncey billups ( 23 )', 'j r smith ( 7 )', 'pepsi center 14158', '26 - 13'], ['40', 'january 15', 'phoenix', 'w 119 - 113 ( ot )', 'chauncey billups ( 26 )', 'chauncey billups ( 8 )', 'pepsi center 18073', '27 - 13'], ['41', 'january 17', 'orlando', 'l 88 - 106 ( ot )', 'linas kleiza ( 26 )', 'anthony carter ( 7 )', 'pepsi center 19749', '27 - 14'], ['42', 'january 19', 'houston', 'l 113 - 115 ( ot )', 'j r smith ( 24 )', 'chauncey billups ( 12 )', 'toyota center 18199', '27 - 15'], ['43', 'january 20', 'sacramento', 'w 118 - 99 ( ot )', 'linas kleiza ( 27 )', 'anthony carter ( 10 )', 'pepsi center 15164', '28 - 15'], ['44', 'january 25', 'utah', 'w 117 - 97 ( ot )', 'nenê ( 28 )', 'anthony carter ( 10 )', 'pepsi center 17895', '29 - 15'], ['45', 'january 27', 'memphis', 'w 100 - 85 ( ot )', 'chauncey billups ( 29 )', 'kenyon martin ( 4 )', 'fedexforum 11338', '30 - 15'], ['46', 'january 28', 'new orleans', 'l 81 - 94 ( ot )', 'kenyon martin ( 22 )', 'anthony carter ( 6 )', 'new orleans arena 15792', '30 - 16'], ['47', 'january 30', 'charlotte', 'w 110 - 99 ( ot )', 'nenê ( 22 )', 'anthony carter , chauncey billups ( 6 )', 'pepsi center 18463', '31 - 16']] |
jhalak dikhhla jaa ( indian dance series ) | https://en.wikipedia.org/wiki/Jhalak_Dikhhla_Jaa_%28Indian_Dance_Series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13133962-1.html.csv | majority | all of the seasons of the indian dance series premiered after the year 2000 . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '20', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'season premiere date', '20'], 'result': True, 'ind': 0, 'tointer': 'for the season premiere date records of all rows , all of them fuzzily match to 20 .', 'tostr': 'all_eq { all_rows ; season premiere date ; 20 } = true'} | all_eq { all_rows ; season premiere date ; 20 } = true | for the season premiere date records of all rows , all of them fuzzily match to 20 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'season premiere date_3': 3, '20_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'season premiere date_3': 'season premiere date', '20_4': '20'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'season premiere date_3': [0], '20_4': [0]} | ['season', 'season premiere date', 'season finale date', 'winner', '1st runner up', '2nd runner up'] | [['1', '8 september 2006', '4 november 2006', 'mona singh', 'shweta salve', 'mahesh manjrekar'], ['2', '28 september 2007', '15 december 2007', 'prachi desai', 'sandhya mridul', 'jay bhanushali'], ['3', '27 february 2009', '31 may 2009', 'baichung bhutia', 'gauhar khan', 'karan singh grover'], ['4', '12 december 2010', '8 march 2011', 'meiyang chang', 'sushant singh rajput', 'yana gupta'], ['5', '16 june 2012', '30 september 2012', 'gurmeet choudhary', 'rashmi desai', 'rithvik dhanjani']] |
cruizer - class brig - sloop | https://en.wikipedia.org/wiki/Cruizer-class_brig-sloop | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16304334-5.html.csv | comparative | the eclair cruizer-class brig-sloop was launched at a later date than the derwent cruizer-class brig-sloop . | {'row_1': '2', 'row_2': '1', 'col': '4', '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', 'eclair'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to eclair .', 'tostr': 'filter_eq { all_rows ; name ; eclair }'}, 'launched'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; eclair } ; launched }', 'tointer': 'select the rows whose name record fuzzily matches to eclair . take the launched record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'derwent'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to derwent .', 'tostr': 'filter_eq { all_rows ; name ; derwent }'}, 'launched'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; derwent } ; launched }', 'tointer': 'select the rows whose name record fuzzily matches to derwent . take the launched record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; eclair } ; launched } ; hop { filter_eq { all_rows ; name ; derwent } ; launched } } = true', 'tointer': 'select the rows whose name record fuzzily matches to eclair . take the launched record of this row . select the rows whose name record fuzzily matches to derwent . take the launched record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; eclair } ; launched } ; hop { filter_eq { all_rows ; name ; derwent } ; launched } } = true | select the rows whose name record fuzzily matches to eclair . take the launched record of this row . select the rows whose name record fuzzily matches to derwent . take the launched 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, 'eclair_8': 8, 'launched_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'derwent_12': 12, 'launched_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', 'eclair_8': 'eclair', 'launched_9': 'launched', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'derwent_12': 'derwent', 'launched_13': 'launched'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'eclair_8': [0], 'launched_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'derwent_12': [1], 'launched_13': [3]} | ['name', 'ordered', 'builder', 'launched', 'fate'] | [['derwent', '1 october 1806', 'isaac blackburn , turnchapel , plymouth', '23 may 1807', 'sold 1817'], ['eclair', '1 october 1806', 'matthew warren , brightlingsea , essex', '8 july 1807', 'broken up 1831'], ['eclipse', '1 october 1806', 'john king , dover', '4 august 1807', 'sold for mercantile use 1815'], ['barracouta', '1 october 1806', 'jabez bailey , ipswich', '6 july 1807', 'sold 1815'], ['nautilus', '1 october 1806', 'james betts , mistleythorn', '5 august 1807', 'broken up 1823'], ['pilot', '1 october 1806', 'robert guillaume , northam , southampton', '6 august 1807', 'sold 1828'], ['sparrowhawk', '1 october 1806', 'matthew warren , brightlingsea , essex', '20 august 1807', 'sold 1841'], ['zenobia', '1 october 1806', "josiah & thomas brindley , king 's lynn", '7 october 1807', 'sold 1835'], ['magnet', '1 october 1806', 'robert guillaume , northam , southampton', '19 october 1807', 'wrecked 1809'], ['peruvian', '1 october 1806', 'george parsons , warsash', '26 april 1808', 'broken up 1830']] |
1981 denver broncos season | https://en.wikipedia.org/wiki/1981_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17972136-1.html.csv | count | the denver broncos won 10 games during the 1981 season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '10', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; result ; w }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; w } }', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; w } } ; 10 } = true', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 10 .'} | eq { count { filter_eq { all_rows ; result ; w } } ; 10 } = true | select the rows whose result record fuzzily matches to w . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'w_6': 6, '10_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'w_6': 'w', '10_7': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'w_6': [0], '10_7': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 6', 'oakland raiders', 'w 9 - 7', 'mile high stadium', '1 - 0', '74796'], ['2', 'september 13', 'seattle seahawks', 'l 10 - 13', 'kingdome', '1 - 1', '58513'], ['3', 'september 20', 'baltimore colts', 'w 28 - 10', 'mile high stadium', '2 - 1', '74804'], ['4', 'september 27', 'san diego chargers', 'w 42 - 24', 'mile high stadium', '3 - 1', '74822'], ['5', 'october 4', 'oakland raiders', 'w 17 - 0', 'oakland - alameda county coliseum', '4 - 1', '51035'], ['6', 'october 11', 'detroit lions', 'w 27 - 21', 'mile high stadium', '5 - 1', '74816'], ['7', 'october 18', 'kansas city chiefs', 'l 14 - 28', 'arrowhead stadium', '5 - 2', '74672'], ['8', 'october 25', 'buffalo bills', 'l 7 - 9', 'rich stadium', '5 - 3', '77757'], ['9', 'november 2', 'minnesota vikings', 'w 19 - 17', 'mile high stadium', '6 - 3', '74834'], ['10', 'november 8', 'cleveland browns', 'w 23 - 20 ( ot )', 'mile high stadium', '7 - 3', '74859'], ['11', 'november 15', 'tampa bay buccaneers', 'w 24 - 7', 'tampa stadium', '8 - 3', '64518'], ['12', 'november 22', 'cincinnati bengals', 'l 21 - 38', 'riverfront stadium', '8 - 4', '57207'], ['13', 'november 29', 'san diego chargers', 'l 17 - 34', 'jack murphy stadium', '8 - 5', '51533'], ['14', 'december 6', 'kansas city chiefs', 'w 16 - 13', 'mile high stadium', '9 - 5', '74744'], ['15', 'december 13', 'seattle seahawks', 'w 23 - 13', 'mile high stadium', '10 - 5', '74527']] |
1994 - 95 philadelphia flyers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14022127-5.html.csv | ordinal | the philadelphia flyers game on april 23 had the 3rd lowest attendance of all games during the 1994 - 95 season . | {'row': '11', 'col': '6', 'order': '3', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; attendance ; 3 }'}, 'date'], 'result': 'april 23', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; attendance ; 3 } ; date }'}, 'april 23'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; attendance ; 3 } ; date } ; april 23 } = true', 'tointer': 'select the row whose attendance record of all rows is 3rd minimum . the date record of this row is april 23 .'} | eq { hop { nth_argmin { all_rows ; attendance ; 3 } ; date } ; april 23 } = true | select the row whose attendance record of all rows is 3rd minimum . the date record of this row is april 23 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'date_7': 7, 'april 23_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '3_6': '3', 'date_7': 'date', 'april 23_8': 'april 23'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'date_7': [1], 'april 23_8': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['april 1', 'philadelphia', '2 - 3', 'pittsburgh', 'hextall', '17181', '17 - 13 - 4'], ['april 2', 'ny rangers', '2 - 4', 'philadelphia', 'hextall', '17380', '18 - 13 - 4'], ['april 6', 'tampa bay', '4 - 5', 'philadelphia', 'hextall', '17245', '19 - 13 - 4'], ['april 8', 'philadelphia', '3 - 1', 'washington', 'hextall', '18130', '20 - 13 - 4'], ['april 12', 'montreal', '2 - 3', 'philadelphia', 'hextall', '17380', '21 - 13 - 4'], ['april 14', 'tampa bay', '2 - 3', 'philadelphia', 'roussel', '17380', '22 - 13 - 4'], ['april 16', 'pittsburgh', '3 - 4', 'philadelphia', 'hextall', '17380', '23 - 13 - 4'], ['april 18', 'philadelphia', '3 - 1', 'florida', 'hextall', '14703', '24 - 13 - 4'], ['april 20', 'ny islanders', '1 - 2', 'philadelphia', 'hextall', '17380', '25 - 13 - 4'], ['april 22', 'philadelphia', '4 - 3', 'new jersey', 'roussel', '19040', '26 - 13 - 4'], ['april 23', 'philadelphia', '2 - 4', 'buffalo', 'hextall', '16230', '26 - 14 - 4'], ['april 26', 'ottawa', '5 - 2', 'philadelphia', 'hextall', '17380', '26 - 15 - 4'], ['april 28', 'philadelphia', '4 - 3', 'hartford', 'hextall', '15550', '27 - 15 - 4'], ['april 30', 'ny rangers', '2 - 0', 'philadelphia', 'roussel', '17380', '27 - 16 - 4']] |
2006 japanese television dramas | https://en.wikipedia.org/wiki/2006_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18540022-2.html.csv | aggregation | 2006 japanese television dramas have an average of 10.72 episodes . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '10.72', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'episodes'], 'result': '10.72', 'ind': 0, 'tostr': 'avg { all_rows ; episodes }'}, '10.72'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; episodes } ; 10.72 } = true', 'tointer': 'the average of the episodes record of all rows is 10.72 .'} | round_eq { avg { all_rows ; episodes } ; 10.72 } = true | the average of the episodes record of all rows is 10.72 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'episodes_4': 4, '10.72_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'episodes_4': 'episodes', '10.72_5': '10.72'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'episodes_4': [0], '10.72_5': [1]} | ['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings'] | [['アテンションプリーズ', 'attention please', 'fuji tv', '11', '16.37 %'], ['医龍 - team medical dragon -', 'iryuu - team medical dragon -', 'fuji tv', '11', '14.8 %'], ['弁護士のくず', 'bengoshi no kuzu', 'tbs', '11', '12.74 %'], ['クロサギ', 'kurosagi', 'tbs', '11', '15.67 %'], ['おいしいプロポーズ', 'oishii propose', 'tbs', '10', '12.0 %'], ['トップキャスター', 'top caster', 'tbs', '11', '18.3 %'], ['富豪刑事2', 'fugou keiji 2', 'tv asahi', '10', '12.0 %'], ['７人の女弁護士', 'shichinin no onna bengoshi', 'tv asahi', '9', '12.05 %'], ['ギャルサー', 'gyarusa - , gal circle', 'ntv', '11', '12.9 %'], ['プリマダム', 'primadem', 'ntv', '11', '11.2 %'], ['ブスの瞳に恋してる', 'busu no hitomi ni koishiteru', 'fuji tv', '12', '15.9 %']] |
tiffany joh | https://en.wikipedia.org/wiki/Tiffany_Joh | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15870501-2.html.csv | aggregation | from 2007 - 2012 , tiffany joh played in a total of 38 tournaments . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '38', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'tournaments played'], 'result': '38', 'ind': 0, 'tostr': 'sum { all_rows ; tournaments played }'}, '38'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; tournaments played } ; 38 } = true', 'tointer': 'the sum of the tournaments played record of all rows is 38 .'} | round_eq { sum { all_rows ; tournaments played } ; 38 } = true | the sum of the tournaments played record of all rows is 38 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'tournaments played_4': 4, '38_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'tournaments played_4': 'tournaments played', '38_5': '38'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'tournaments played_4': [0], '38_5': [1]} | ['year', 'tournaments played', 'cuts made', 'wins', 'best finish', 'earnings', 'scoring average'] | [['2007', '1', '1', '0', 't22', 'n / a', '71.66'], ['2009', '1', '1', '0', 't21', 'n / a', '72.50'], ['2010', '2', '0', '0', 'mc', '0', '79.00'], ['2011', '14', '12', '0', '2', '237365', '72.75'], ['2012', '20', '10', '0', 't33', '48695', '74.09']] |
christian heritage party of canada candidates , 2008 canadian federal election | https://en.wikipedia.org/wiki/Christian_Heritage_Party_of_Canada_candidates%2C_2008_Canadian_federal_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12890254-6.html.csv | ordinal | micheal mackay received the 3rd highest amount of votes out of all the candidate 's . | {'row': '1', 'col': '6', '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', 'votes', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; votes ; 3 }'}, "candidate 's name"], 'result': 'michael mackay', 'ind': 1, 'tostr': "hop { nth_argmax { all_rows ; votes ; 3 } ; candidate 's name }"}, 'michael mackay'], 'result': True, 'ind': 2, 'tostr': "eq { hop { nth_argmax { all_rows ; votes ; 3 } ; candidate 's name } ; michael mackay } = true", 'tointer': "select the row whose votes record of all rows is 3rd maximum . the candidate 's name record of this row is michael mackay ."} | eq { hop { nth_argmax { all_rows ; votes ; 3 } ; candidate 's name } ; michael mackay } = true | select the row whose votes record of all rows is 3rd maximum . the candidate 's name record of this row is michael mackay . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'votes_5': 5, '3_6': 6, "candidate 's name_7": 7, 'michael mackay_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', 'votes_5': 'votes', '3_6': '3', "candidate 's name_7": "candidate 's name", 'michael mackay_8': 'michael mackay'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'votes_5': [0], '3_6': [0], "candidate 's name_7": [1], 'michael mackay_8': [2]} | ['riding', "candidate 's name", 'gender', 'residence', 'occupation', 'votes', 'rank'] | [['central nova', 'michael mackay', 'm', 'west river station', 'retail', '427', '4th'], ['dartmouth-cole harbour', 'george campbell', 'm', 'dartmouth', 'minister', '219', '5th'], ['halifax west', 'trevor ennis', 'm', 'halifax', 'swimming pool salesman', '257', '5th'], ['kings-hants', 'jim hnatiuk', 'm', 'enfield', 'combat systems technician', '528', '5th'], ["south shore-st margaret 's", 'joe larkin', 'm', 'shag harbour', 'retired', '513', '5th']] |
circuit trois - rivières | https://en.wikipedia.org/wiki/Circuit_Trois-Rivi%C3%A8res | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11095234-7.html.csv | majority | at the circuit trois - rivières , all of the drivers drove over forty laps . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '40 laps', 'subset': None} | {'func': 'all_greater', 'args': ['all_rows', 'distance / duration', '40 laps'], 'result': True, 'ind': 0, 'tointer': 'for the distance / duration records of all rows , all of them are greater than 40 laps .', 'tostr': 'all_greater { all_rows ; distance / duration ; 40 laps } = true'} | all_greater { all_rows ; distance / duration ; 40 laps } = true | for the distance / duration records of all rows , all of them are greater than 40 laps . | 1 | 1 | {'all_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'distance / duration_3': 3, '40 laps_4': 4} | {'all_greater_0': 'all_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'distance / duration_3': 'distance / duration', '40 laps_4': '40 laps'} | {'all_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'distance / duration_3': [0], '40 laps_4': [0]} | ['year', 'date', 'driver', 'team', 'distance / duration'] | [['2007', 'sept 4', 'kerry micks', 'beyond digital imaging', '41 laps'], ['2008', 'aug 17', 'andrew ranger', 'wal - mart / tide', '46 laps'], ['2009', 'aug 17', 'andrew ranger', 'wal - mart / tide', '43 laps'], ['2010', 'aug 15', 'andrew ranger', 'dodge dealers of quebec', '42 laps'], ['2011', 'aug 7', 'robin buck', 'quaker state / durabody', '44 laps'], ['2012', 'aug 7', 'andrew ranger', 'dodge / gc motorsports', '44 laps']] |
1926 vfl season | https://en.wikipedia.org/wiki/1926_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-7.html.csv | majority | most of the games for the vfl on 7 june 1926 had crowds of 20,000 or larger . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '20,000', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'crowd', '20,000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than or equal to 20,000 .', 'tostr': 'most_greater_eq { all_rows ; crowd ; 20,000 } = true'} | most_greater_eq { all_rows ; crowd ; 20,000 } = true | for the crowd records of all rows , most of them are greater than or equal to 20,000 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '20,000_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '20,000_4': '20,000'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '20,000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '10.13 ( 73 )', 'richmond', '10.14 ( 74 )', 'arden street oval', '12000', '7 june 1926'], ['melbourne', '12.16 ( 88 )', 'south melbourne', '8.17 ( 65 )', 'mcg', '20974', '7 june 1926'], ['fitzroy', '11.15 ( 81 )', 'hawthorn', '14.12 ( 96 )', 'brunswick street oval', '8000', '7 june 1926'], ['geelong', '13.11 ( 89 )', 'essendon', '7.9 ( 51 )', 'corio oval', '25600', '7 june 1926'], ['st kilda', '9.12 ( 66 )', 'collingwood', '10.16 ( 76 )', 'junction oval', '24000', '7 june 1926'], ['footscray', '10.11 ( 71 )', 'carlton', '14.9 ( 93 )', 'western oval', '20000', '7 june 1926']] |
scottish parliament general election , 2007 | https://en.wikipedia.org/wiki/Scottish_Parliament_general_election%2C_2007 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11105214-1.html.csv | ordinal | ayr had the 3rd largest swing to gain among constituencies in the scottish parliament general election of 2007 . | {'row': '8', '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', 'swing to gain', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; swing to gain ; 3 }'}, 'constituency'], 'result': 'ayr', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; swing to gain ; 3 } ; constituency }'}, 'ayr'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; swing to gain ; 3 } ; constituency } ; ayr } = true', 'tointer': 'select the row whose swing to gain record of all rows is 3rd maximum . the constituency record of this row is ayr .'} | eq { hop { nth_argmax { all_rows ; swing to gain ; 3 } ; constituency } ; ayr } = true | select the row whose swing to gain record of all rows is 3rd maximum . the constituency record of this row is ayr . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'swing to gain_5': 5, '3_6': 6, 'constituency_7': 7, 'ayr_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', 'swing to gain_5': 'swing to gain', '3_6': '3', 'constituency_7': 'constituency', 'ayr_8': 'ayr'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'swing to gain_5': [0], '3_6': [0], 'constituency_7': [1], 'ayr_8': [2]} | ['rank', 'constituency', 'winning party 2003', 'swing to gain', "labour 's place 2003", 'result'] | [['1', 'dundee east', 'snp', '0.17', '2nd', 'snp hold'], ['2', 'edinburgh south', 'liberal democrats', '0.26', '2nd', 'ld hold'], ['3', 'ochil', 'snp', '0.49', '2nd', 'snp hold'], ['4', 'strathkelvin and bearsden', 'independent', '0.62', '2nd', 'lab gain'], ['5', 'aberdeen north', 'snp', '0.92', '2nd', 'snp hold'], ['6', 'inverness east , nairn and lochaber', 'snp', '1.51', '2nd', 'snp hold'], ['7', 'tweeddale , ettrick and lauderdale', 'liberal democrats', '2.70', '3rd', 'ld hold'], ['8', 'ayr', 'conservative', '2.99', '2nd', 'con hold'], ['9', 'edinburgh pentlands', 'conservative', '3.16', '2nd', 'con hold'], ['10', 'caithness , sutherland and easter ross', 'liberal democrats', '4.96', '2nd', 'ld hold']] |
1951 world wrestling championships | https://en.wikipedia.org/wiki/1951_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16853558-1.html.csv | ordinal | sweden recorded the highest number of bronze in the 1951 world wrestling championships . | {'row': '2', 'col': '5', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'bronze', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; bronze ; 1 }'}, 'nation'], 'result': 'sweden', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 1 } ; nation }'}, 'sweden'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; bronze ; 1 } ; nation } ; sweden } = true', 'tointer': 'select the row whose bronze record of all rows is 1st maximum . the nation record of this row is sweden .'} | eq { hop { nth_argmax { all_rows ; bronze ; 1 } ; nation } ; sweden } = true | select the row whose bronze record of all rows is 1st maximum . the nation record of this row is sweden . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '1_6': 6, 'nation_7': 7, 'sweden_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', 'bronze_5': 'bronze', '1_6': '1', 'nation_7': 'nation', 'sweden_8': 'sweden'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '1_6': [0], 'nation_7': [1], 'sweden_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'turkey', '6', '0', '1', '7'], ['2', 'sweden', '2', '1', '3', '6'], ['3', 'finland', '0', '4', '0', '4'], ['4', 'iran', '0', '2', '2', '4'], ['5', 'italy', '0', '1', '1', '2'], ['6', 'west germany', '0', '0', '1', '1'], ['total', 'total', '8', '8', '8', '24']] |
porphyrin | https://en.wikipedia.org/wiki/Porphyrin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-182499-1.html.csv | superlative | the highest omim number of porphyrin belongs to uroporphyrinogen iii synthase . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'omim'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; omim }'}, 'enzyme'], 'result': 'uroporphyrinogen iii synthase', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; omim } ; enzyme }'}, 'uroporphyrinogen iii synthase'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; omim } ; enzyme } ; uroporphyrinogen iii synthase } = true', 'tointer': 'select the row whose omim record of all rows is maximum . the enzyme record of this row is uroporphyrinogen iii synthase .'} | eq { hop { argmax { all_rows ; omim } ; enzyme } ; uroporphyrinogen iii synthase } = true | select the row whose omim record of all rows is maximum . the enzyme record of this row is uroporphyrinogen iii synthase . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'omim_5': 5, 'enzyme_6': 6, 'uroporphyrinogen iii synthase_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'omim_5': 'omim', 'enzyme_6': 'enzyme', 'uroporphyrinogen iii synthase_7': 'uroporphyrinogen iii synthase'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'omim_5': [0], 'enzyme_6': [1], 'uroporphyrinogen iii synthase_7': [2]} | ['enzyme', 'location', 'substrate', 'product', 'chromosome', 'ec', 'omim', 'porphyria'] | [['ala synthase', 'mitochondrion', 'glycine , succinyl coa', 'δ - aminolevulinic acid', '3p21 .1', '2.3.1.37', '125290', 'none'], ['ala dehydratase', 'cytosol', 'δ - aminolevulinic acid', 'porphobilinogen', '9q34', '4.2.1.24', '125270', 'ala - dehydratase deficiency'], ['pbg deaminase', 'cytosol', 'porphobilinogen', 'hydroxymethyl bilane', '11q23 .3', '2.5.1.61', '176000', 'acute intermittent porphyria'], ['uroporphyrinogen iii synthase', 'cytosol', 'hydroxymethyl bilane', 'uroporphyrinogen iii', '10q25 .2 - q26 .3', '4.2.1.75', '606938', 'congenital erythropoietic porphyria'], ['uroporphyrinogen iii decarboxylase', 'cytosol', 'uroporphyrinogen iii', 'coproporphyrinogen iii', '1p34', '4.1.1.37', '176100', 'porphyria cutanea tarda'], ['coproporphyrinogen iii oxidase', 'mitochondrion', 'coproporphyrinogen iii', 'protoporphyrinogen ix', '3q12', '1.3.3.3', '121300', 'coproporphyria'], ['protoporphyrinogen oxidase', 'mitochondrion', 'protoporphyrinogen ix', 'protoporphyrin ix', '1q22', '1.3.3.4', '600923', 'variegate porphyria']] |
1954 vfl season | https://en.wikipedia.org/wiki/1954_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-12.html.csv | majority | all games of the 1954 vfl season was played on the 10th of july . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '10 july 1954', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '10 july 1954'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 10 july 1954 .', 'tostr': 'all_eq { all_rows ; date ; 10 july 1954 } = true'} | all_eq { all_rows ; date ; 10 july 1954 } = true | for the date records of all rows , all of them fuzzily match to 10 july 1954 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '10 july 1954_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '10 july 1954_4': '10 july 1954'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '10 july 1954_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '13.16 ( 94 )', 'hawthorn', '9.9 ( 63 )', 'windy hill', '20000', '10 july 1954'], ['collingwood', '8.6 ( 54 )', 'melbourne', '5.16 ( 46 )', 'victoria park', '29000', '10 july 1954'], ['carlton', '11.10 ( 76 )', 'south melbourne', '10.10 ( 70 )', 'princes park', '17000', '10 july 1954'], ['richmond', '14.14 ( 98 )', 'north melbourne', '6.15 ( 51 )', 'punt road oval', '27000', '10 july 1954'], ['st kilda', '9.8 ( 62 )', 'footscray', '13.14 ( 92 )', 'junction oval', '22500', '10 july 1954'], ['geelong', '10.8 ( 68 )', 'fitzroy', '6.6 ( 42 )', 'kardinia park', '15000', '10 july 1954']] |
2007 gran premio tecate | https://en.wikipedia.org/wiki/2007_Gran_Premio_Tecate | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14171191-2.html.csv | unique | at the 2007 gran premio tecate the only driver to complete 64 laps and score more than 30 points was sébastien bourdais . | {'scope': 'subset', 'row': '1', 'col': '6', 'col_other': '1', 'criterion': 'greater_than', 'value': '30', 'subset': {'col': '3', 'criterion': 'equal', 'value': '64'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '64'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; laps ; 64 }', 'tointer': 'select the rows whose laps record is equal to 64 .'}, 'points', '30'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose laps record is equal to 64 . among these rows , select the rows whose points record is greater than 30 .', 'tostr': 'filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } }', 'tointer': 'select the rows whose laps record is equal to 64 . among these rows , select the rows whose points record is greater than 30 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '64'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; laps ; 64 }', 'tointer': 'select the rows whose laps record is equal to 64 .'}, 'points', '30'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose laps record is equal to 64 . among these rows , select the rows whose points record is greater than 30 .', 'tostr': 'filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 }'}, 'driver'], 'result': 'sébastien bourdais', 'ind': 3, 'tostr': 'hop { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } ; driver }'}, 'sébastien bourdais'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } ; driver } ; sébastien bourdais }', 'tointer': 'the driver record of this unqiue row is sébastien bourdais .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } } ; eq { hop { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } ; driver } ; sébastien bourdais } } = true', 'tointer': 'select the rows whose laps record is equal to 64 . among these rows , select the rows whose points record is greater than 30 . there is only one such row in the table . the driver record of this unqiue row is sébastien bourdais .'} | and { only { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } } ; eq { hop { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } ; driver } ; sébastien bourdais } } = true | select the rows whose laps record is equal to 64 . among these rows , select the rows whose points record is greater than 30 . there is only one such row in the table . the driver record of this unqiue row is sébastien bourdais . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'laps_8': 8, '64_9': 9, 'points_10': 10, '30_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'driver_12': 12, 'sébastien bourdais_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'laps_8': 'laps', '64_9': '64', 'points_10': 'points', '30_11': '30', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'driver_12': 'driver', 'sébastien bourdais_13': 'sébastien bourdais'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'laps_8': [0], '64_9': [0], 'points_10': [1], '30_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'driver_12': [3], 'sébastien bourdais_13': [4]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['sébastien bourdais', 'n / h / l racing', '64', '1:45:02.885', '2', '32'], ['will power', 'team australia', '64', '+ 1.906', '1', '29'], ['oriol servià', 'pkv racing', '64', '+ 3.364', '4', '25'], ['graham rahal', 'n / h / l racing', '64', '+ 7.346', '7', '23'], ['paul tracy', 'forsythe racing', '64', '+ 8.593', '8', '21'], ['simon pagenaud', 'team australia', '64', '+ 9.638', '6', '19'], ['bruno junqueira', 'dale coyne racing', '64', '+ 15.823', '12', '17'], ['mario domínguez', 'pacific coast motorsports', '64', '+ 16.077', '15', '16'], ['neel jani', 'pkv racing', '64', '+ 16.199', '11', '13'], ['justin wilson', 'rusport', '64', '+ 16.954', '5', '11'], ['alex figge', 'pacific coast motorsports', '63', '+ 1 lap', '17', '10'], ['nelson philippe', 'conquest racing', '63', '+ 1 lap', '13', '9'], ['alex tagliani', 'rocketsports racing', '62', '+ 2 laps', '14', '8'], ['david martínez', 'forsythe racing', '58', '+ 6 laps', '10', '7'], ['katherine legge', 'dale coyne racing', '56', 'mechanical', '16', '6'], ['robert doornbos', 'minardi team usa', '12', 'mechanical', '3', '6'], ['dan clarke', 'minardi team usa', '0', 'mechanical', '9', '4']] |
1978 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1978_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245471-4.html.csv | majority | at the 1978 u.s. open golf championships most the the players from the united states scores more than 142 . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '142', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'score', '142'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . for the score records of these rows , most of them are greater than 142 .', 'tostr': 'most_greater { filter_eq { all_rows ; country ; united states } ; score ; 142 } = true'} | most_greater { filter_eq { all_rows ; country ; united states } ; score ; 142 } = true | select the rows whose country record fuzzily matches to united states . for the score records of these rows , most of them are greater than 142 . | 2 | 2 | {'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'united states_5': 5, 'score_6': 6, '142_7': 7} | {'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'united states_5': 'united states', 'score_6': 'score', '142_7': '142'} | {'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'united states_5': [0], 'score_6': [1], '142_7': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'andy north', 'united states', '70 + 70 = 140', '2'], ['t2', 'jack nicklaus', 'united states', '73 + 69 = 142', 'e'], ['t2', 'gary player', 'south africa', '71 + 71 = 142', 'e'], ['t2', 'j c snead', 'united states', '70 + 72 = 142', 'e'], ['t5', 'bobby clampett ( a )', 'united states', '70 + 73 = 143', '+ 1'], ['t5', 'mark hayes', 'united states', '73 + 70 = 143', '+ 1'], ['t5', 'hale irwin', 'united states', '69 + 74 = 143', '+ 1'], ['t5', 'lee trevino', 'united states', '72 + 71 = 143', '+ 1'], ['t9', 'seve ballesteros', 'spain', '75 + 69 = 144', '+ 2'], ['t9', 'andy bean', 'united states', '72 + 72 = 144', '+ 2'], ['t9', 'phil hancock', 'united states', '71 + 73 = 144', '+ 2'], ['t9', 'joe inman', 'united states', '72 + 72 = 144', '+ 2'], ['t9', 'peter oosterhuis', 'england', '72 + 72 = 144', '+ 2'], ['t9', 'dave stockton', 'united states', '71 + 73 = 144', '+ 2']] |
sports in charlotte , north carolina | https://en.wikipedia.org/wiki/Sports_in_Charlotte%2C_North_Carolina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15720079-4.html.csv | majority | most of the venue environments in charlotte , north carolina are open air . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'open air', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'environment', 'open air'], 'result': True, 'ind': 0, 'tointer': 'for the environment records of all rows , most of them fuzzily match to open air .', 'tostr': 'most_eq { all_rows ; environment ; open air } = true'} | most_eq { all_rows ; environment ; open air } = true | for the environment records of all rows , most of them fuzzily match to open air . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'environment_3': 3, 'open air_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'environment_3': 'environment', 'open air_4': 'open air'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'environment_3': [0], 'open air_4': [0]} | ['venue', 'location', 'capacity', 'owner', 'environment', 'year built'] | [['bank of america stadium', 'uptown charlotte', '73778', 'carolina panthers', 'open air , natural grass', '1996'], ['time warner cable arena', 'uptown charlotte', '20200', 'city of charlotte', 'indoor arena', '2005'], ['american legion memorial stadium', 'elizabeth , charlotte', '16000', 'mecklenburg parks & rec', 'open air , natural grass', '1936'], ["bojangles ' coliseum", 'coliseum drive , charlotte', '9605', 'city of charlotte', 'indoor arena', '1955'], ['jerry richardson stadium', 'university city , charlotte', '15314', 'unc charlotte', 'open air , artificial turf', '2012'], ['charlotte motor speedway', 'concord , nc', '140000 +', 'speedway motorsports', 'open air , asphalt', '1960'], ['dale f halton arena', 'university city , charlotte', '9105', 'unc charlotte', 'indoor arena', '1996'], ['john m belk arena', 'davidson , nc', '5223', 'davidson college', 'indoor arena', '1989'], ['transamerica field', 'university city , charlotte', '4000', 'unc charlotte', 'open air , natural grass', '1996'], ['richardson stadium', 'davidson , nc', '6000', 'davidson college', 'open air , artificial turf', '1923'], ['irwin belk complex', 'biddleville , charlotte', '4500', 'johnson c smith university', 'open air , natural grass', '2003'], ['winthrop coliseum', 'rock hill , sc', '6100', 'winthrop university', 'indoor arena', '1982'], ['knights stadium', 'fort mill , sc', '10002', 'york county , sc', 'open air , natural grass', '1990'], ['concord speedway', 'midland , nc', '8000', 'concord speedway', 'open air , asphalt', '1956']] |
fiba eurobasket 2009 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2009_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23670057-1.html.csv | unique | ioannis kalampokis was the only player on fiba eurobasket 2009 squads that was born in the 1970s . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '1978', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year born', '1978'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year born record is equal to 1978 .', 'tostr': 'filter_eq { all_rows ; year born ; 1978 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; year born ; 1978 } }', 'tointer': 'select the rows whose year born record is equal to 1978 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year born', '1978'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year born record is equal to 1978 .', 'tostr': 'filter_eq { all_rows ; year born ; 1978 }'}, 'player'], 'result': 'ioannis kalampokis', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year born ; 1978 } ; player }'}, 'ioannis kalampokis'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; year born ; 1978 } ; player } ; ioannis kalampokis }', 'tointer': 'the player record of this unqiue row is ioannis kalampokis .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; year born ; 1978 } } ; eq { hop { filter_eq { all_rows ; year born ; 1978 } ; player } ; ioannis kalampokis } } = true', 'tointer': 'select the rows whose year born record is equal to 1978 . there is only one such row in the table . the player record of this unqiue row is ioannis kalampokis .'} | and { only { filter_eq { all_rows ; year born ; 1978 } } ; eq { hop { filter_eq { all_rows ; year born ; 1978 } ; player } ; ioannis kalampokis } } = true | select the rows whose year born record is equal to 1978 . there is only one such row in the table . the player record of this unqiue row is ioannis kalampokis . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'year born_7': 7, '1978_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'ioannis kalampokis_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'year born_7': 'year born', '1978_8': '1978', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'ioannis kalampokis_10': 'ioannis kalampokis'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'year born_7': [0], '1978_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'ioannis kalampokis_10': [3]} | ['no', 'player', 'height ( m )', 'height ( f )', 'position', 'year born', 'current club'] | [['4', 'ioannis kalampokis', '1.96', "6 ' 05 ″", 'guard', '1978', 'alba berlin'], ['5', 'ioannis bourousis', '2.13', "7 ' 00 ″", 'center', '1983', 'olimpia milano'], ['6', 'nikolaos zisis', '1.97', "6 ' 06 ″", 'guard', '1983', 'bilbao basket'], ['7', 'vasileios spanoulis', '1.93', "6 ' 04 ″", 'guard', '1982', 'olympiacos'], ['8', 'nicholas calathes', '1.98', "6 ' 06 ″", 'guard', '1989', 'lokomotiv kuban'], ['9', 'antonios fotsis', '2.09', "6 ' 10 ″", 'forward', '1981', 'olimpia milano'], ['10', 'georgios printezis', '2.06', "6 ' 09 ″", 'forward', '1985', 'olympiacos'], ['11', 'andreas glyniadakis', '2.16', "7 ' 01 ″", 'center', '1981', 'astana'], ['12', 'konstantinos kaimakoglou', '2.05', "6 ' 09 ″", 'forward', '1983', 'unics kazan'], ['13', 'konstantinos koufos', '2.13', "7 ' 00 ″", 'forward', '1989', 'denver nuggets'], ['14', 'efstratios perperoglou', '2.03', "6 ' 08 ″", 'forward', '1984', 'olympiacos']] |
queens county , new brunswick | https://en.wikipedia.org/wiki/Queens_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-171356-2.html.csv | count | there are 9 official locations in the queens county of new brunswick . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'official name'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose official name record is arbitrary .', 'tostr': 'filter_all { all_rows ; official name }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; official name } }', 'tointer': 'select the rows whose official name record is arbitrary . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; official name } } ; 9 } = true', 'tointer': 'select the rows whose official name record is arbitrary . the number of such rows is 9 .'} | eq { count { filter_all { all_rows ; official name } } ; 9 } = true | select the rows whose official name record is arbitrary . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'official name_5': 5, '9_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'official name_5': 'official name', '9_6': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'official name_5': [0], '9_6': [2]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['chipman', 'parish', '482.81', '962', '2135 of 5008'], ['canning', 'parish', '173.40', '952', '2145 of 5008'], ['waterborough', 'parish', '444.87', '851', '2290 of 5008'], ['petersville', 'parish', '588.42', '723', '2520 of 5008'], ['johnston', 'parish', '359.18', '660', '2649 of 5008'], ['cambridge', 'parish', '113.97', '651', '2662 of 5008'], ['wickham', 'parish', '159.78', '426', '3211 of 5008'], ['gagetown', 'parish', '234.89', '316', '3574 of 5008'], ['hampstead', 'parish', '212.63', '294', '3665 of 5008']] |
list of awards and nominations received by grey 's anatomy | https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_Grey%27s_Anatomy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12372406-1.html.csv | comparative | of the awards and nominations received by grey 's anatomy , the one for outstanding actress - television series came 5 years before the one for favorite tv actress - supporting role . | {'row_1': '1', 'row_2': '5', 'col': '1', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'outstanding actress - television series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to outstanding actress - television series .', 'tostr': 'filter_eq { all_rows ; category ; outstanding actress - television series }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year }', 'tointer': 'select the rows whose category record fuzzily matches to outstanding actress - television series . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'favorite tv actress - supporting role'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose category record fuzzily matches to favorite tv actress - supporting role .', 'tostr': 'filter_eq { all_rows ; category ; favorite tv actress - supporting role }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year }', 'tointer': 'select the rows whose category record fuzzily matches to favorite tv actress - supporting role . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year } }', 'tointer': 'select the rows whose category record fuzzily matches to outstanding actress - television series . take the year record of this row . select the rows whose category record fuzzily matches to favorite tv actress - supporting role . take the year record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'outstanding actress - television series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to outstanding actress - television series .', 'tostr': 'filter_eq { all_rows ; category ; outstanding actress - television series }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year }', 'tointer': 'select the rows whose category record fuzzily matches to outstanding actress - television series . take the year record of this row .'}, '2007'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; 2007 }', 'tointer': 'the year record of the first row is 2007 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'favorite tv actress - supporting role'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose category record fuzzily matches to favorite tv actress - supporting role .', 'tostr': 'filter_eq { all_rows ; category ; favorite tv actress - supporting role }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year }', 'tointer': 'select the rows whose category record fuzzily matches to favorite tv actress - supporting role . take the year record of this row .'}, '2012'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year } ; 2012 }', 'tointer': 'the year record of the second row is 2012 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; 2007 } ; eq { hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year } ; 2012 } }', 'tointer': 'the year record of the first row is 2007 . the year record of the second row is 2012 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year } } ; and { eq { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; 2007 } ; eq { hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year } ; 2012 } } } = true', 'tointer': 'select the rows whose category record fuzzily matches to outstanding actress - television series . take the year record of this row . select the rows whose category record fuzzily matches to favorite tv actress - supporting role . take the year record of this row . the first record is less than the second record . the year record of the first row is 2007 . the year record of the second row is 2012 .'} | and { less { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year } } ; and { eq { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; 2007 } ; eq { hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year } ; 2012 } } } = true | select the rows whose category record fuzzily matches to outstanding actress - television series . take the year record of this row . select the rows whose category record fuzzily matches to favorite tv actress - supporting role . take the year record of this row . the first record is less than the second record . the year record of the first row is 2007 . the year record of the second row is 2012 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'category_11': 11, 'outstanding actress - television series_12': 12, 'year_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'category_15': 15, 'favorite tv actress - supporting role_16': 16, 'year_17': 17, 'and_7': 7, 'eq_5': 5, '2007_18': 18, 'eq_6': 6, '2012_19': 19} | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'category_11': 'category', 'outstanding actress - television series_12': 'outstanding actress - television series', 'year_13': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'category_15': 'category', 'favorite tv actress - supporting role_16': 'favorite tv actress - supporting role', 'year_17': 'year', 'and_7': 'and', 'eq_5': 'eq', '2007_18': '2007', 'eq_6': 'eq', '2012_19': '2012'} | {'and_8': [9], 'result_9': [], 'less_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'category_11': [0], 'outstanding actress - television series_12': [0], 'year_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'category_15': [1], 'favorite tv actress - supporting role_16': [1], 'year_17': [3], 'and_7': [8], 'eq_5': [7], '2007_18': [5], 'eq_6': [7], '2012_19': [6]} | ['year', 'recipient', 'role', 'category', 'result'] | [['2007', 'sara ramirez', 'callie torres', 'outstanding actress - television series', 'nominated'], ['2008', 'sara ramirez', 'callie torres', 'outstanding actress - drama television series', 'nominated'], ['2009', 'sara ramirez', 'callie torres', 'outstanding actress - drama television series', 'nominated'], ['2011', 'sara ramirez', 'callie torres', 'favorite tv actress - leading role in a drama', 'nominated'], ['2012', 'sara ramirez', 'callie torres', 'favorite tv actress - supporting role', 'nominated']] |
test matches ( 1991 - 2000 ) | https://en.wikipedia.org/wiki/Test_matches_%281991%E2%80%932000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12410929-70.html.csv | comparative | the west indies team ( wi ) won the february 1997 test match with 4 more wickets than they did in the december 1996 match . | {'row_1': '5', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '4', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1 , 2 , 3 february 1997'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 1 , 2 , 3 february 1997 .', 'tostr': 'filter_eq { all_rows ; date ; 1 , 2 , 3 february 1997 }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 1 , 2 , 3 february 1997 } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to 1 , 2 , 3 february 1997 . take the result record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '26 , 27 , 28 december 1996'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 26 , 27 , 28 december 1996 .', 'tostr': 'filter_eq { all_rows ; date ; 26 , 27 , 28 december 1996 }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 26 , 27 , 28 december 1996 } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to 26 , 27 , 28 december 1996 . take the result record of this row .'}], 'result': '4', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; date ; 1 , 2 , 3 february 1997 } ; result } ; hop { filter_eq { all_rows ; date ; 26 , 27 , 28 december 1996 } ; result } }'}, '4'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; date ; 1 , 2 , 3 february 1997 } ; result } ; hop { filter_eq { all_rows ; date ; 26 , 27 , 28 december 1996 } ; result } } ; 4 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 1 , 2 , 3 february 1997 . take the result record of this row . select the rows whose date record fuzzily matches to 26 , 27 , 28 december 1996 . take the result record of this row . the first record is 4 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; date ; 1 , 2 , 3 february 1997 } ; result } ; hop { filter_eq { all_rows ; date ; 26 , 27 , 28 december 1996 } ; result } } ; 4 } = true | select the rows whose date record fuzzily matches to 1 , 2 , 3 february 1997 . take the result record of this row . select the rows whose date record fuzzily matches to 26 , 27 , 28 december 1996 . take the result record of this row . the first record is 4 larger than the second 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, 'date_8': 8, '1 , 2 , 3 february 1997_9': 9, 'result_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'date_12': 12, '26 , 27 , 28 december 1996_13': 13, 'result_14': 14, '4_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', 'date_8': 'date', '1 , 2 , 3 february 1997_9': '1 , 2 , 3 february 1997', 'result_10': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'date_12': 'date', '26 , 27 , 28 december 1996_13': '26 , 27 , 28 december 1996', 'result_14': 'result', '4_15': '4'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'date_8': [0], '1 , 2 , 3 february 1997_9': [0], 'result_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'date_12': [1], '26 , 27 , 28 december 1996_13': [1], 'result_14': [3], '4_15': [5]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['22 , 23 , 24 , 25 , 26 november 1996', 'mark taylor', 'courtney walsh', 'brisbane cricket ground', 'aus by 123 runs'], ['29 , 30 november , 1 , 2 , 3 december 1996', 'mark taylor', 'courtney walsh', 'sydney cricket ground', 'aus by 124 runs'], ['26 , 27 , 28 december 1996', 'mark taylor', 'courtney walsh', 'melbourne cricket ground', 'wi by 6 wkts'], ['25 , 26 , 27 , 28 january 1997', 'mark taylor', 'courtney walsh', 'adelaide oval', 'aus by inns & 183 runs'], ['1 , 2 , 3 february 1997', 'mark taylor', 'courtney walsh', 'waca ground', 'wi by 10 wkts']] |
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 | ordinal | kpix was the third earliest tv channel to be owned by the westinghouse broadcasting company . | {'row': '1', 'col': '4', 'order': '3', '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', 'years owned', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; years owned ; 3 }'}, 'station'], 'result': 'kpix', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; years owned ; 3 } ; station }'}, 'kpix'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; years owned ; 3 } ; station } ; kpix } = true', 'tointer': 'select the row whose years owned record of all rows is 3rd minimum . the station record of this row is kpix .'} | eq { hop { nth_argmin { all_rows ; years owned ; 3 } ; station } ; kpix } = true | select the row whose years owned record of all rows is 3rd minimum . the station record of this row is kpix . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'years owned_5': 5, '3_6': 6, 'station_7': 7, 'kpix_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', 'years owned_5': 'years owned', '3_6': '3', 'station_7': 'station', 'kpix_8': 'kpix'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'years owned_5': [0], '3_6': [0], 'station_7': [1], 'kpix_8': [2]} | ['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 )']] |
2008 san francisco 49ers season | https://en.wikipedia.org/wiki/2008_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15623820-1.html.csv | aggregation | in the 2008 san francisco 49ers season , the average contract time for a quarterback was 2 years . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '2', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'qb'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', 'qb'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; pos ; qb }', 'tointer': 'select the rows whose pos record fuzzily matches to qb .'}, 'contract'], 'result': '2', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; pos ; qb } ; contract }'}, '2'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; pos ; qb } ; contract } ; 2 } = true', 'tointer': 'select the rows whose pos record fuzzily matches to qb . the average of the contract record of these rows is 2 .'} | round_eq { avg { filter_eq { all_rows ; pos ; qb } ; contract } ; 2 } = true | select the rows whose pos record fuzzily matches to qb . the average of the contract record of these rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'pos_5': 5, 'qb_6': 6, 'contract_7': 7, '2_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'pos_5': 'pos', 'qb_6': 'qb', 'contract_7': 'contract', '2_8': '2'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'pos_5': [0], 'qb_6': [0], 'contract_7': [1], '2_8': [2]} | ['pos', 'player', 'free agent type', '2007 team', 'contract'] | [['wr', 'isaac bruce', 'released', 'st louis rams', '2 years , 6 million'], ['rb', 'deshaun foster', 'released', 'carolina panthers', '2 years , 1.8 million'], ['lb', 'roderick green', 'ufa', 'san francisco 49ers', '1 year'], ['qb', 'shaun hill', 'ufa', 'san francisco 49ers', '3 years , 6 million'], ['wr', 'bryant johnson', 'ufa', 'arizona cardinals', '1 year'], ['qb', "j t o ' sullivan", 'ufa', 'detroit lions', '1 year , 645000'], ['cb', 'allen rossum', 'released', 'pittsburgh steelers', '1 year , 870000'], ['de', 'justin smith', 'ufa', 'cincinnati bengals', '6 years , 45 million'], ['dt', 'isaac sopoaga', 'ufa', 'san francisco 49ers', '5 years , 20 million'], ['cb', 'donald strickland', 'ufa', 'san francisco 49ers', '1 year , 800000'], ['lb', 'dontarrious thomas', 'ufa', 'minnesota vikings', '2 years']] |
irrigation in bolivia | https://en.wikipedia.org/wiki/Irrigation_in_Bolivia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17118006-1.html.csv | aggregation | these departments in bolivia have an average total amount of irrigation approximately equal to 32366 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '32366', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '32366', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '32366'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 32366 } = true', 'tointer': 'the average of the total record of all rows is 32366 .'} | round_eq { avg { all_rows ; total } ; 32366 } = true | the average of the total record of all rows is 32366 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '32366_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '32366_5': '32366'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '32366_5': [1]} | ['department', 'micro ( 10ha )', 'small ( 100ha )', 'medium ( 500ha )', 'big ( > 500ha )', 'total'] | [['chuquisaca', '1653', '11370', '4261', '3884', '21168'], ['cochabamba', '1938', '22225', '27403', '35968', '81925'], ['la paz', '1703', '21047', '6052', '7192', '35994'], ['oruro', '940', '3638', '440', '9021', '14039'], ['potosã\xad', '3240', '10146', '2254', '600', '16240'], ['santa cruz', '269', '5456', '8434', '1080', '15239'], ['tarija', '785', '12755', '17101', '5710', '36351'], ['total', '10528', '86638', '65944', '63454', '226564']] |
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 | ordinal | in the midlands , england , the stadium ranked the third highest capacity is franklin 's gardens . | {'row': '2', 'col': '5', 'order': '3', 'col_other': '4', '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', 'capacity', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; capacity ; 3 }'}, 'stadium'], 'result': "franklin 's gardens", 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; capacity ; 3 } ; stadium }'}, "franklin 's gardens"], 'result': True, 'ind': 2, 'tostr': "eq { hop { nth_argmax { all_rows ; capacity ; 3 } ; stadium } ; franklin 's gardens } = true", 'tointer': "select the row whose capacity record of all rows is 3rd maximum . the stadium record of this row is franklin 's gardens ."} | eq { hop { nth_argmax { all_rows ; capacity ; 3 } ; stadium } ; franklin 's gardens } = true | select the row whose capacity record of all rows is 3rd maximum . the stadium record of this row is franklin 's gardens . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, '3_6': 6, 'stadium_7': 7, "franklin 's gardens_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', 'capacity_5': 'capacity', '3_6': '3', 'stadium_7': 'stadium', "franklin 's gardens_8": "franklin 's gardens"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], '3_6': [0], 'stadium_7': [1], "franklin 's gardens_8": [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']] |
galicia , spain | https://en.wikipedia.org/wiki/Galicia%2C_Spain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12837-1.html.csv | unique | in galicia , spain , the only town with 2043 hours of sunlight is ourense . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '2043', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'sunlight hours', '2043'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sunlight hours record is equal to 2043 .', 'tostr': 'filter_eq { all_rows ; sunlight hours ; 2043 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; sunlight hours ; 2043 } }', 'tointer': 'select the rows whose sunlight hours record is equal to 2043 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'sunlight hours', '2043'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sunlight hours record is equal to 2043 .', 'tostr': 'filter_eq { all_rows ; sunlight hours ; 2043 }'}, 'city / town'], 'result': 'ourense', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; sunlight hours ; 2043 } ; city / town }'}, 'ourense'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; sunlight hours ; 2043 } ; city / town } ; ourense }', 'tointer': 'the city / town record of this unqiue row is ourense .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; sunlight hours ; 2043 } } ; eq { hop { filter_eq { all_rows ; sunlight hours ; 2043 } ; city / town } ; ourense } } = true', 'tointer': 'select the rows whose sunlight hours record is equal to 2043 . there is only one such row in the table . the city / town record of this unqiue row is ourense .'} | and { only { filter_eq { all_rows ; sunlight hours ; 2043 } } ; eq { hop { filter_eq { all_rows ; sunlight hours ; 2043 } ; city / town } ; ourense } } = true | select the rows whose sunlight hours record is equal to 2043 . there is only one such row in the table . the city / town record of this unqiue row is ourense . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'sunlight hours_7': 7, '2043_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'city / town_9': 9, 'ourense_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'sunlight hours_7': 'sunlight hours', '2043_8': '2043', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'city / town_9': 'city / town', 'ourense_10': 'ourense'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'sunlight hours_7': [0], '2043_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'city / town_9': [2], 'ourense_10': [3]} | ['city / town', 'july av t', 'rain', 'days with rain ( year / summer )', 'days with frost', 'sunlight hours'] | [['santiago de compostela', 'degree', 'mm ( in )', '141 / 19', '15', '1998'], ['a coruña', 'degree', 'mm ( in )', '131 / 19', '0', '1966'], ['lugo', 'degree', 'mm ( in )', '131 / 18', '42', '1821'], ['vigo', 'degree', 'mm ( in )', '130 / 18', '5', '2212'], ['ourense', 'degree', 'mm ( in )', '97 / 12', '30', '2043'], ['pontevedra', 'degree', 'mm ( in )', '133 / 18', '2', '2223']] |
2005 - 06 primeira liga | https://en.wikipedia.org/wiki/2005%E2%80%9306_Primeira_Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17933603-1.html.csv | comparative | of the two teams bases in the city of funchal , maritimo finished in better standing overall . | {'row_1': '10', 'row_2': '11', 'col': '5', 'col_other': '1,3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'marítimo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to marítimo .', 'tostr': 'filter_eq { all_rows ; club ; marítimo }'}, '2004 - 2005 season'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; marítimo } ; 2004 - 2005 season }', 'tointer': 'select the rows whose club record fuzzily matches to marítimo . take the 2004 - 2005 season record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'nacional'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to nacional .', 'tostr': 'filter_eq { all_rows ; club ; nacional }'}, '2004 - 2005 season'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; nacional } ; 2004 - 2005 season }', 'tointer': 'select the rows whose club record fuzzily matches to nacional . take the 2004 - 2005 season record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; club ; marítimo } ; 2004 - 2005 season } ; hop { filter_eq { all_rows ; club ; nacional } ; 2004 - 2005 season } }', 'tointer': 'select the rows whose club record fuzzily matches to marítimo . take the 2004 - 2005 season record of this row . select the rows whose club record fuzzily matches to nacional . take the 2004 - 2005 season record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'marítimo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to marítimo .', 'tostr': 'filter_eq { all_rows ; club ; marítimo }'}, 'city'], 'result': 'funchal', 'ind': 5, 'tostr': 'hop { filter_eq { all_rows ; club ; marítimo } ; city }'}, 'funchal'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; club ; marítimo } ; city } ; funchal }', 'tointer': 'the city record of the first row is funchal .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'nacional'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to nacional .', 'tostr': 'filter_eq { all_rows ; club ; nacional }'}, 'city'], 'result': 'funchal', 'ind': 7, 'tostr': 'hop { filter_eq { all_rows ; club ; nacional } ; city }'}, 'funchal'], 'result': True, 'ind': 8, 'tostr': 'eq { hop { filter_eq { all_rows ; club ; nacional } ; city } ; funchal }', 'tointer': 'the city record of the second row is funchal .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { hop { filter_eq { all_rows ; club ; marítimo } ; city } ; funchal } ; eq { hop { filter_eq { all_rows ; club ; nacional } ; city } ; funchal } }', 'tointer': 'the city record of the first row is funchal . the city record of the second row is funchal .'}], 'result': True, 'ind': 10, 'tostr': 'and { less { hop { filter_eq { all_rows ; club ; marítimo } ; 2004 - 2005 season } ; hop { filter_eq { all_rows ; club ; nacional } ; 2004 - 2005 season } } ; and { eq { hop { filter_eq { all_rows ; club ; marítimo } ; city } ; funchal } ; eq { hop { filter_eq { all_rows ; club ; nacional } ; city } ; funchal } } } = true', 'tointer': 'select the rows whose club record fuzzily matches to marítimo . take the 2004 - 2005 season record of this row . select the rows whose club record fuzzily matches to nacional . take the 2004 - 2005 season record of this row . the first record is less than the second record . the city record of the first row is funchal . the city record of the second row is funchal .'} | and { less { hop { filter_eq { all_rows ; club ; marítimo } ; 2004 - 2005 season } ; hop { filter_eq { all_rows ; club ; nacional } ; 2004 - 2005 season } } ; and { eq { hop { filter_eq { all_rows ; club ; marítimo } ; city } ; funchal } ; eq { hop { filter_eq { all_rows ; club ; nacional } ; city } ; funchal } } } = true | select the rows whose club record fuzzily matches to marítimo . take the 2004 - 2005 season record of this row . select the rows whose club record fuzzily matches to nacional . take the 2004 - 2005 season record of this row . the first record is less than the second record . the city record of the first row is funchal . the city record of the second row is funchal . | 13 | 11 | {'and_10': 10, 'result_11': 11, 'less_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_12': 12, 'club_13': 13, 'marítimo_14': 14, '2004 - 2005 season_15': 15, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_16': 16, 'club_17': 17, 'nacional_18': 18, '2004 - 2005 season_19': 19, 'and_9': 9, 'str_eq_6': 6, 'str_hop_5': 5, 'city_20': 20, 'funchal_21': 21, 'str_eq_8': 8, 'str_hop_7': 7, 'city_22': 22, 'funchal_23': 23} | {'and_10': 'and', 'result_11': 'true', 'less_4': 'less', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_12': 'all_rows', 'club_13': 'club', 'marítimo_14': 'marítimo', '2004 - 2005 season_15': '2004 - 2005 season', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_16': 'all_rows', 'club_17': 'club', 'nacional_18': 'nacional', '2004 - 2005 season_19': '2004 - 2005 season', 'and_9': 'and', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'city_20': 'city', 'funchal_21': 'funchal', 'str_eq_8': 'str_eq', 'str_hop_7': 'str_hop', 'city_22': 'city', 'funchal_23': 'funchal'} | {'and_10': [11], 'result_11': [], 'less_4': [10], 'str_hop_2': [4], 'filter_str_eq_0': [2, 5], 'all_rows_12': [0], 'club_13': [0], 'marítimo_14': [0], '2004 - 2005 season_15': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3, 7], 'all_rows_16': [1], 'club_17': [1], 'nacional_18': [1], '2004 - 2005 season_19': [3], 'and_9': [10], 'str_eq_6': [9], 'str_hop_5': [6], 'city_20': [5], 'funchal_21': [6], 'str_eq_8': [9], 'str_hop_7': [8], 'city_22': [7], 'funchal_23': [8]} | ['club', "season 's last head coach", 'city', 'stadium', '2004 - 2005 season'] | [['académica de coimbra', 'nelo vingada', 'coimbra', 'estádio cidade de coimbra', '14th in the liga'], ['belenenses', 'carlos carvalhal', 'lisbon', 'estádio do restelo', '9th in the liga'], ['benfica', 'ronald koeman', 'lisbon', 'estádio da luz', '1st in the liga'], ['boavista', 'carlos brito', 'porto', 'estádio do bessa - século xxi', '6th in the liga'], ['braga', 'jesualdo ferreira', 'braga', 'estádio municipal de braga - axa', '4th in the liga'], ['estrela da amadora', 'toni', 'amadora', 'estádio josé gomes', '3rd in the liga de honra'], ['gil vicente', 'paulo alves', 'barcelos', 'estádio cidade de barcelos', '13th in the liga'], ['união de leiria', 'jorge jesus', 'leiria', 'estádio dr magalhães pessoa', '15th in the liga'], ['penafiel', 'luís castro', 'penafiel', 'estádio municipal 25 de abril', '11th in the liga'], ['marítimo', 'ulisses morais', 'funchal', 'estádio dos barreiros', '7th in the liga'], ['nacional', 'manuel machado', 'funchal', 'estádio da madeira', '12th in the liga'], ['naval 1 degree de maio', 'rogério gonçalves', 'figueira da foz', 'estádio municipal josé bento pessoa', '2nd in the liga de honra'], ['paços de ferreira', 'josé mota', 'paços de ferreira', 'estádio da mata real', '1st in the liga de honra'], ['porto', 'co adriaanse', 'porto', 'estádio do dragão', '2nd in the liga'], ['sporting cp', 'paulo bento', 'lisbon', 'estádio josé alvalade - século xxi', '3rd in the liga'], ['rio ave', 'joão eusébio', 'vila do conde', 'estádio dos arcos', '8th in the liga'], ['vitória de guimarães', 'vítor pontes', 'guimarães', 'estádio d afonso henriques', '5th in the liga'], ['vitória de setúbal', 'hélio sousa', 'setúbal', 'estádio do bonfim', '10th in the liga']] |
2007 - 08 atlanta hawks season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11961582-10.html.csv | comparative | the game with a score of 81-104 took place three days before the game with a score of 77-96 . | {'row_1': '1', 'row_2': '2', 'col': '2', 'col_other': '4', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '3 days', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '81 - 104'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 81 - 104 .', 'tostr': 'filter_eq { all_rows ; score ; 81 - 104 }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; 81 - 104 } ; date }', 'tointer': 'select the rows whose score record fuzzily matches to 81 - 104 . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '77 - 96'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record fuzzily matches to 77 - 96 .', 'tostr': 'filter_eq { all_rows ; score ; 77 - 96 }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; score ; 77 - 96 } ; date }', 'tointer': 'select the rows whose score record fuzzily matches to 77 - 96 . take the date record of this row .'}], 'result': '-3 days', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; score ; 81 - 104 } ; date } ; hop { filter_eq { all_rows ; score ; 77 - 96 } ; date } }'}, '-3 days'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; score ; 81 - 104 } ; date } ; hop { filter_eq { all_rows ; score ; 77 - 96 } ; date } } ; -3 days } = true', 'tointer': 'select the rows whose score record fuzzily matches to 81 - 104 . take the date record of this row . select the rows whose score record fuzzily matches to 77 - 96 . take the date record of this row . the second record is 3 days larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; score ; 81 - 104 } ; date } ; hop { filter_eq { all_rows ; score ; 77 - 96 } ; date } } ; -3 days } = true | select the rows whose score record fuzzily matches to 81 - 104 . take the date record of this row . select the rows whose score record fuzzily matches to 77 - 96 . take the date record of this row . the second record is 3 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, 'score_8': 8, '81 - 104_9': 9, 'date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'score_12': 12, '77 - 96_13': 13, 'date_14': 14, '-3 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', 'score_8': 'score', '81 - 104_9': '81 - 104', 'date_10': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'score_12': 'score', '77 - 96_13': '77 - 96', 'date_14': 'date', '-3 days_15': '-3 days'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'score_8': [0], '81 - 104_9': [0], 'date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'score_12': [1], '77 - 96_13': [1], 'date_14': [3], '-3 days_15': [5]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 20', 'boston', '81 - 104', 'a horford ( 20 )', 'a horford ( 10 )', 'j johnson ( 7 )', 'td banknorth garden 18624', '0 - 1'], ['2', 'april 23', 'boston', '77 - 96', 'two - way tie ( 13 )', 'a horford ( 9 )', 'two - way tie ( 3 )', 'td banknorth garden 18624', '0 - 2'], ['3', 'april 26', 'boston', '102 - 93', 'j smith ( 27 )', 'a horford ( 10 )', 'm bibby ( 8 )', 'philips arena 19725', '1 - 2'], ['4', 'april 28', 'boston', '97 - 92', 'j johnson ( 35 )', 'a horford ( 13 )', 'j johnson ( 6 )', 'philips arena 20016', '2 - 2'], ['5', 'april 30', 'boston', '85 - 110', 'j johnson ( 21 )', 'a horford ( 10 )', 'a horford ( 5 )', 'td banknorth garden 18624', '2 - 3'], ['6', 'may 2', 'boston', '103 - 100', 'm williams ( 18 )', 'four - way tie ( 6 )', 'm bibby ( 7 )', 'philips arena 20425', '3 - 3'], ['7', 'may 4', 'boston', '99 - 65', 'j johnson ( 16 )', 'a horford ( 12 )', 'a horford ( 3 )', 'td banknorth garden 18624', '3 - 4']] |
list of dams and reservoirs in asturias | https://en.wikipedia.org/wiki/List_of_dams_and_reservoirs_in_Asturias | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28702208-1.html.csv | superlative | the tallest embankment type dam in asturias is 67 metres high . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'embankment'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'embankment'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; embankment }', 'tointer': 'select the rows whose type record fuzzily matches to embankment .'}, 'height ( m )'], 'result': '67.0', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; type ; embankment } ; height ( m ) }', 'tointer': 'select the rows whose type record fuzzily matches to embankment . the maximum height ( m ) record of these rows is 67.0 .'}, '67.0'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; type ; embankment } ; height ( m ) } ; 67.0 } = true', 'tointer': 'select the rows whose type record fuzzily matches to embankment . the maximum height ( m ) record of these rows is 67.0 .'} | eq { max { filter_eq { all_rows ; type ; embankment } ; height ( m ) } ; 67.0 } = true | select the rows whose type record fuzzily matches to embankment . the maximum height ( m ) record of these rows is 67.0 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'type_5': 5, 'embankment_6': 6, 'height (m)_7': 7, '67.0_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'type_5': 'type', 'embankment_6': 'embankment', 'height (m)_7': 'height ( m )', '67.0_8': '67.0'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'type_5': [0], 'embankment_6': [0], 'height (m)_7': [1], '67.0_8': [2]} | ['reservoir', 'basin', 'location', 'type', 'height ( m )', 'length along the top ( m )', 'drainage basin ( km square )', 'reservoir surface ( ha )', 'volume ( hm cubic )'] | [['alfilorios', 'barrea', 'ribera de arriba', 'embankment', '67.0', '171.7', '4.09', '52.0', '9.140'], ['arbón', 'navia', 'coaña , villayón', 'embankment', '35.0', '180.0', '2443.0', '270.0', '38.20'], ['barca , la', 'narcea', 'belmonte , tineo', 'arch', '73.5', '178.0', '1216.0', '194.0', '31.10'], ['doiras', 'navia', 'boal', 'arch - gravity', '90.0', '165.0', '2288.0', '347.0', '114.60'], ['florida , la', 'narcea', 'tineo', 'gravity', '19.0', '70.0', '1005.0', '18.40', '0.75'], ['furacón , el', 'nalón', 'trubia ( oviedo )', 'gravity', '14.0', '70.0', '2180.0', '19.0', '0.522'], ['granda , la', 'granda', 'gozón', 'embankment', '23.7', '270.0', '1.25', '32.50', '3.208'], ['jocica , la', 'dobra', 'amieva', 'arch', '87.0', '66.0', '39.0', '6.14', '0.4'], ['mortera , la', 'mortera', 'morcín', 'gravity', '8.0', '91.0', '0.0', '0.0', '0.017'], ['priañes', 'nora', 'oviedo , las regueras', 'gravity', '27.0', '50.0', '340.0', '35.17', '1.9'], ['saliencia', 'saliencia', 'somiedo', 'gravity', '20.0', '33.0', '48.0', '0.30', '0.02'], ['salime', 'navia', 'grandas de salime', 'gravity', '125.67', '250.0', '1806.0', '685.0', '266.30'], ['san andrés tacones', 'aboño', 'sa tacones ( gijón )', 'embankment', '22.0', '434.0', '37.5', '4.0', '71.0'], ['somiedo', 'somiedo', 'somiedo', 'gravity', '24.0', '18.0', '82.0', '0.29', '0.018'], ['tanes', 'nalón', 'caso , sobrescobio', 'gravity', '95.0', '195.0', '271.0', '159.0', '33.27'], ['trasona', 'alvares', 'trasona ( corvera )', 'gravity', '16.0', '332.0', '37.0', '61.0', '4.1'], ['valdemurio', 'trubia', 'quirós', 'gravity', '40.15', '119.0', '196.0', '1.43', '1.43'], ['valduno ii', 'nalón', 'las regueras', 'gravity', '9.9', '105.0', '2500.0', '34.36', '0.3'], ['valle', 'valle', 'somiedo', 'gravity', '12.5', '52.8', '39.0', '23.7', '3.7']] |
reinhold roth | https://en.wikipedia.org/wiki/Reinhold_Roth | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14860855-3.html.csv | majority | reinhold roth raced 250cc motorcyles the majority of his career . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '250cc', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'class', '250cc'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , most of them fuzzily match to 250cc .', 'tostr': 'most_eq { all_rows ; class ; 250cc } = true'} | most_eq { all_rows ; class ; 250cc } = true | for the class records of all rows , most of them fuzzily match to 250cc . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, '250cc_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', '250cc_4': '250cc'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], '250cc_4': [0]} | ['year', 'class', 'team', 'points', 'wins'] | [['1979', '350cc', 'yamaha', '3', '0'], ['1980', '250cc', 'yamaha', '4', '0'], ['1982', '250cc', 'yamaha', '4', '0'], ['1982', '500cc', 'suzuki', '0', '0'], ['1983', '250cc', 'yamaha', '14', '0'], ['1984', '500cc', 'honda', '14', '0'], ['1985', '250cc', 'romer - juchem', '29', '0'], ['1986', '250cc', 'hb - honda', '10', '0'], ['1987', '250cc', 'hb - honda', '108', '1'], ['1988', '250cc', 'hb - honda', '158', '0'], ['1989', '250cc', 'hb - honda', '190', '2'], ['1990', '250cc', 'hb - honda', '52', '0']] |
1926 vfl season | https://en.wikipedia.org/wiki/1926_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-12.html.csv | superlative | the match played at the punt road oval venue drew the largest crowd . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'crowd'], 'result': '27000', 'ind': 0, 'tostr': 'max { all_rows ; crowd }', 'tointer': 'the maximum crowd record of all rows is 27000 .'}, '27000'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; crowd } ; 27000 }', 'tointer': 'the maximum crowd record of all rows is 27000 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'punt road oval', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'punt road oval'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; punt road oval }', 'tointer': 'the venue record of the row with superlative crowd record is punt road oval .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; crowd } ; 27000 } ; eq { hop { argmax { all_rows ; crowd } ; venue } ; punt road oval } } = true', 'tointer': 'the maximum crowd record of all rows is 27000 . the venue record of the row with superlative crowd record is punt road oval .'} | and { eq { max { all_rows ; crowd } ; 27000 } ; eq { hop { argmax { all_rows ; crowd } ; venue } ; punt road oval } } = true | the maximum crowd record of all rows is 27000 . the venue record of the row with superlative crowd record is punt road oval . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '27000_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'crowd_11': 11, 'venue_12': 12, 'punt road oval_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '27000_9': '27000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'crowd_11': 'crowd', 'venue_12': 'venue', 'punt road oval_13': 'punt road oval'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'crowd_8': [0], '27000_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'crowd_11': [2], 'venue_12': [3], 'punt road oval_13': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '10.15 ( 75 )', 'south melbourne', '16.12 ( 108 )', 'punt road oval', '27000', '17 july 1926'], ['footscray', '7.14 ( 56 )', 'geelong', '15.17 ( 107 )', 'western oval', '17000', '17 july 1926'], ['collingwood', '18.16 ( 124 )', 'fitzroy', '11.16 ( 82 )', 'victoria park', '16000', '17 july 1926'], ['carlton', '8.17 ( 65 )', 'hawthorn', '8.9 ( 57 )', 'princes park', '12000', '17 july 1926'], ['st kilda', '3.11 ( 29 )', 'melbourne', '17.16 ( 118 )', 'junction oval', '14000', '17 july 1926'], ['north melbourne', '4.8 ( 32 )', 'essendon', '6.14 ( 50 )', 'arden street oval', '10000', '17 july 1926']] |
doug lewis ( skier ) | https://en.wikipedia.org/wiki/Doug_Lewis_%28skier%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10103807-2.html.csv | unique | doug lewis 's best downhill skiing performance was the only time he placed in the top ten in a competition in argentina . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '4', 'criterion': 'fuzzily_match', 'value': 'argentina', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'argentina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to argentina .', 'tostr': 'filter_eq { all_rows ; location ; argentina }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; argentina } }', 'tointer': 'select the rows whose location record fuzzily matches to argentina . 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', 'argentina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to argentina .', 'tostr': 'filter_eq { all_rows ; location ; argentina }'}, 'discipline'], 'result': 'downhill', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; argentina } ; discipline }'}, 'downhill'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; argentina } ; discipline } ; downhill }', 'tointer': 'the discipline record of this unqiue row is downhill .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; argentina } } ; eq { hop { filter_eq { all_rows ; location ; argentina } ; discipline } ; downhill } } = true', 'tointer': 'select the rows whose location record fuzzily matches to argentina . there is only one such row in the table . the discipline record of this unqiue row is downhill .'} | and { only { filter_eq { all_rows ; location ; argentina } } ; eq { hop { filter_eq { all_rows ; location ; argentina } ; discipline } ; downhill } } = true | select the rows whose location record fuzzily matches to argentina . there is only one such row in the table . the discipline record of this unqiue row is downhill . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'argentina_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'discipline_9': 9, 'downhill_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', 'argentina_8': 'argentina', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'discipline_9': 'discipline', 'downhill_10': 'downhill'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'argentina_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'discipline_9': [2], 'downhill_10': [3]} | ['season', 'date', 'location', 'discipline', 'place'] | [['1984', '11 mar 1984', 'whistler , bc , canada', 'downhill', '8th'], ['1985', '15 dec 1984', 'val gardena , italy', 'downhill', '9th'], ['1985', '11 jan 1985', 'kitzbühel , austria', 'downhill', '10th'], ['1985', '1985 world championships', '1985 world championships', '1985 world championships', '1985 world championships'], ['1986', '16 aug 1985', 'las leñas , argentina', 'downhill', '2nd'], ['1986', '17 jan 1986', 'kitzbühel , austria', 'downhill', '5th'], ['1986', '8 mar 1986', 'aspen , co , usa', 'downhill', '8th'], ['1987', '28 feb 1987', 'furano , japan', 'downhill', '7th'], ['1987', '7 mar 1987', 'aspen , co , usa', 'downhill', '9th']] |
1991 open championship | https://en.wikipedia.org/wiki/1991_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18131508-5.html.csv | aggregation | all the players in the 1991 open championship had an average score of around 140 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '140', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '140', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '140'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 140 } = true', 'tointer': 'the average of the score record of all rows is 140 .'} | round_eq { avg { all_rows ; score } ; 140 } = true | the average of the score record of all rows is 140 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '140_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '140_5': '140'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '140_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'gary hallberg', 'united states', '68 + 70 = 138', '- 2'], ['t1', 'mike harwood', 'australia', '68 + 70 = 138', '- 2'], ['t1', 'andrew oldcorn', 'scotland', '71 + 67 = 138', '- 2'], ['t4', 'seve ballesteros', 'spain', '66 + 73 = 139', '- 1'], ['t4', 'steve elkington', 'australia', '71 + 68 = 139', '- 1'], ['t4', 'david gilford', 'england', '72 + 67 = 139', '- 1'], ['t4', 'wayne grady', 'australia', '69 + 70 = 139', '- 1'], ['t4', "mark o'meara", 'united states', '71 + 68 = 139', '- 1'], ['t4', 'mike reid', 'united states', '68 + 71 = 139', '- 1'], ['t10', 'richard boxall', 'england', '71 + 69 = 140', 'e'], ['t10', 'roger chapman', 'england', '74 + 66 = 140', 'e'], ['t10', 'howard clark', 'england', '71 + 69 = 140', 'e'], ['t10', 'mark james', 'england', '72 + 68 = 140', 'e'], ['t10', 'barry lane', 'england', '68 + 72 = 140', 'e'], ['t10', 'colin montgomerie', 'scotland', '71 + 69 = 140', 'e'], ['t10', 'vijay singh', 'fiji', '71 + 69 = 140', 'e']] |
list of hewitts and nuttalls in england | https://en.wikipedia.org/wiki/List_of_Hewitts_and_Nuttalls_in_England | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10814429-1.html.csv | aggregation | for hewitts and nuttalls in england , the average height when the parent is the cheviot is 642 . | {'scope': 'subset', 'col': '2', 'type': 'average', 'result': '642', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'the cheviot'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'parent', 'the cheviot'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; parent ; the cheviot }', 'tointer': 'select the rows whose parent record fuzzily matches to the cheviot .'}, 'height ( m )'], 'result': '642', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; parent ; the cheviot } ; height ( m ) }'}, '642'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; parent ; the cheviot } ; height ( m ) } ; 642 } = true', 'tointer': 'select the rows whose parent record fuzzily matches to the cheviot . the average of the height ( m ) record of these rows is 642 .'} | round_eq { avg { filter_eq { all_rows ; parent ; the cheviot } ; height ( m ) } ; 642 } = true | select the rows whose parent record fuzzily matches to the cheviot . the average of the height ( m ) record of these rows is 642 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'parent_5': 5, 'the cheviot_6': 6, 'height (m)_7': 7, '642_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'parent_5': 'parent', 'the cheviot_6': 'the cheviot', 'height (m)_7': 'height ( m )', '642_8': '642'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'parent_5': [0], 'the cheviot_6': [0], 'height (m)_7': [1], '642_8': [2]} | ['peak', 'height ( m )', 'prom ( m )', 'class', 'parent'] | [['the cheviot', '815', '556', 'marilyn', 'broad law'], ['hedgehope hill', '714', '148', 'hewitt', 'the cheviot'], ['comb fell', '652', '69', 'hewitt', 'the cheviot'], ['windy gyle', '619', '113', 'hewitt', 'the cheviot'], ['cushat law', '615', '147', 'hewitt', 'the cheviot'], ['bloodybush edge', '610', '114', 'hewitt', 'the cheviot']] |
hit 'n run tour | https://en.wikipedia.org/wiki/Hit_%27n_Run_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12946465-1.html.csv | ordinal | the concert on july 21st recorded the highest attendance of the hit 'n run tour . | {'row': '2', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'date'], 'result': 'july 21 , 2007', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; date }'}, 'july 21 , 2007'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; july 21 , 2007 } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the date record of this row is july 21 , 2007 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; july 21 , 2007 } = true | select the row whose attendance record of all rows is 1st maximum . the date record of this row is july 21 , 2007 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'date_7': 7, 'july 21 , 2007_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'date_7': 'date', 'july 21 , 2007_8': 'july 21 , 2007'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'date_7': [1], 'july 21 , 2007_8': [2]} | ['date', 'city', 'country', 'venue', 'attendance'] | [['july 20 , 2007', 'sault ste marie , michigan', 'united states', 'kewadin casino', '10000'], ['july 21 , 2007', 'cadott , wisconsin', 'united states', 'cadott rock fest', '35000'], ['july 25 , 2007', 'anaheim , california', 'united states', 'cisco customer appreciation event', '1000'], ['july 27 , 2007', 'san jacinto , california', 'united states', 'soboba casino arena', '3500'], ['september 15 , 2007', 'whistler , british columbia', 'canada', 'blackcomb mountain', 'canceled'], ['october 26 , 2007', 'paradise , nevada', 'united states', 'mandalay bay resort', '1500']] |
greater dhaka area | https://en.wikipedia.org/wiki/Greater_Dhaka_Area | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24027047-1.html.csv | superlative | the 2011 population of dhaka district is larger than any other administrative division in the greater dhaka area . | {'scope': 'all', 'col_superlative': '4', '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', 'population 2011 census ( adjusted )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; population 2011 census ( adjusted ) }'}, 'administrative division'], 'result': 'dhaka district', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; population 2011 census ( adjusted ) } ; administrative division }'}, 'dhaka district'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; population 2011 census ( adjusted ) } ; administrative division } ; dhaka district } = true', 'tointer': 'select the row whose population 2011 census ( adjusted ) record of all rows is maximum . the administrative division record of this row is dhaka district .'} | eq { hop { argmax { all_rows ; population 2011 census ( adjusted ) } ; administrative division } ; dhaka district } = true | select the row whose population 2011 census ( adjusted ) record of all rows is maximum . the administrative division record of this row is dhaka district . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'population 2011 census (adjusted)_5': 5, 'administrative division_6': 6, 'dhaka district_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'population 2011 census (adjusted)_5': 'population 2011 census ( adjusted )', 'administrative division_6': 'administrative division', 'dhaka district_7': 'dhaka district'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'population 2011 census (adjusted)_5': [0], 'administrative division_6': [1], 'dhaka district_7': [2]} | ['administrative division', 'area ( km square ) 2011', 'population 2001 census ( adjusted )', 'population 2011 census ( adjusted )', 'population density ( / km square 2011 )'] | [['dhaka district', '1463.6', '9036647', '12517361', '8552.4'], ['savar upazila', '282.11', '629695', '1442885', '5114.6'], ['keraniganj upazila', '166.82', '649373', '824538', '4942.68'], ['narayanganj district', '684.37', '2300514', '3074078', '4491.8'], ['narayanganj sadar upazila', '100.74', '946205', '1381796', '13716.5'], ['bandar upazila', '54.39', '267021', '327149', '6014.8'], ['rupganj upazila', '176.48', '423135', '558192', '3162.9'], ['gazipur district', '1806.36', '2143200', '3548115', '1964.2'], ['gazipur sadar upazila', '457.67', '925454', '1899575', '4150.5'], ['kaliakair upazila', '314.13', '278967', '503976', '1604.3'], ['narsingdi district', '1150.14', '1983499', '2314899', '2012.7'], ['narsingdi sadar upazila', '213.43', '606474', '737362', '3454.8'], ['palash upazila', '94.43', '198106', '221979', '2350.7']] |
kharkov governorate | https://en.wikipedia.org/wiki/Kharkov_Governorate | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17051786-1.html.csv | ordinal | in the 1897 census of the kharkov governorate , yiddish has the third-highest number of speakers . | {'row': '3', 'col': '2', 'order': '3', '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', 'number', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; number ; 3 }'}, 'language'], 'result': 'yiddish', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; number ; 3 } ; language }'}, 'yiddish'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; number ; 3 } ; language } ; yiddish } = true', 'tointer': 'select the row whose number record of all rows is 3rd maximum . the language record of this row is yiddish .'} | eq { hop { nth_argmax { all_rows ; number ; 3 } ; language } ; yiddish } = true | select the row whose number record of all rows is 3rd maximum . the language record of this row is yiddish . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'number_5': 5, '3_6': 6, 'language_7': 7, 'yiddish_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', 'number_5': 'number', '3_6': '3', 'language_7': 'language', 'yiddish_8': 'yiddish'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'number_5': [0], '3_6': [0], 'language_7': [1], 'yiddish_8': [2]} | ['language', 'number', 'percentage ( % )', 'males', 'females'] | [['ukrainian', '2 009 411', '80.62', '1 004 372', '1 005 039'], ['russian', '440 936', '17.69', '225 803', '215 133'], ['yiddish', '12 650', '0.5', '7 007', '5 643'], ['belarusian', '10 258', '0.41', '4 936', '5 322'], ['german', '9 080', '0.36', '4 504', '4 576'], ['polish', '5 910', '0.23', '4 056', '1 854'], ['tatar', '1 358', '> 0.1', '1 221', '137'], ["persons that did n't name their native language", '44', '> 0.01', '23', '21'], ['other', '2 669', '0.1', '1 700', '969'], ['total', '2 492 316', '100', '1 253 759', '1 238 557']] |
newfoundland and labrador general election , 2011 | https://en.wikipedia.org/wiki/Newfoundland_and_Labrador_general_election%2C_2011 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24778847-2.html.csv | ordinal | the poll of the 2011 newfoundland and labrador general election taken from february 12 - march 4 , 2008 had the third highest amount of progressive conservatives . | {'row': '19', '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', 'progressive conservative', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; progressive conservative ; 3 }'}, 'date of polling'], 'result': 'february 12 - march 4 , 2008', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; progressive conservative ; 3 } ; date of polling }'}, 'february 12 - march 4 , 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; progressive conservative ; 3 } ; date of polling } ; february 12 - march 4 , 2008 } = true', 'tointer': 'select the row whose progressive conservative record of all rows is 3rd maximum . the date of polling record of this row is february 12 - march 4 , 2008 .'} | eq { hop { nth_argmax { all_rows ; progressive conservative ; 3 } ; date of polling } ; february 12 - march 4 , 2008 } = true | select the row whose progressive conservative record of all rows is 3rd maximum . the date of polling record of this row is february 12 - march 4 , 2008 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'progressive conservative_5': 5, '3_6': 6, 'date of polling_7': 7, 'february 12 - march 4 , 2008_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', 'progressive conservative_5': 'progressive conservative', '3_6': '3', 'date of polling_7': 'date of polling', 'february 12 - march 4 , 2008_8': 'february 12 - march 4 , 2008'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'progressive conservative_5': [0], '3_6': [0], 'date of polling_7': [1], 'february 12 - march 4 , 2008_8': [2]} | ['polling firm', 'date of polling', 'link', 'progressive conservative', 'liberal', 'new democratic'] | [['corporate research associates', 'september 29 - october 3 , 2011', 'html', '59', '16', '25'], ['environics', 'september 29 - october 4 , 2011', 'html', '54', '13', '33'], ['marketquest omnifacts research', 'september 28 - 30 , 2011', 'html', '54', '13', '33'], ['marketquest omnifacts research', 'september 16 - 19 , 2011', 'html', '53', '18', '29'], ['corporate research associates', 'august 15 - 31 , 2011', 'pdf', '54', '22', '24'], ['corporate research associates', 'may 11 - 28 , 2011', 'pdf', '57', '22', '20'], ['corporate research associates', 'february 10 - 28 , 2011', 'pdf', '73', '18', '8'], ['corporate research associates', 'november 9 - 30 , 2010', 'pdf', '75', '16', '8'], ['corporate research associates', 'august 10 - 30 , 2010', 'pdf', '76', '17', '7'], ['corporate research associates', 'may 11 - 31 , 2010', 'pdf', '75', '16', '8'], ['corporate research associates', 'february 9 - 25 , 2010', 'pdf', '80', '15', '5'], ['corporate research associates', 'november 5 - 22 , 2009', 'pdf', '77', '16', '7'], ['corporate research associates', 'august 11 - 29 , 2009', 'pdf', '77', '15', '8'], ['corporate research associates', 'may 12 - 30 , 2009', 'pdf', '72', '19', '8'], ['corporate research associates', 'february 11 - 28 , 2009', 'pdf', '71', '22', '7'], ['corporate research associates', 'november 5 - december 2 , 2008', 'pdf', '72', '19', '9'], ['corporate research associates', 'august 12 - 30 , 2008', 'pdf', '78', '14', '7'], ['corporate research associates', 'may 8 - june 1 , 2008', 'pdf', '77', '13', '8'], ['corporate research associates', 'february 12 - march 4 , 2008', 'pdf', '79', '14', '6'], ['corporate research associates', 'november 9 - december 3 , 2007', 'pdf', '82', '12', '7']] |
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