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2011 british gt season
https://en.wikipedia.org/wiki/2011_British_GT_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30062172-3.html.csv
count
there were twelve occasions where the length was sixty minutes .
{'scope': 'all', 'criterion': 'equal', 'value': '60 mins', 'result': '12', 'col': '4', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'length', '60 mins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose length record fuzzily matches to 60 mins .', 'tostr': 'filter_eq { all_rows ; length ; 60 mins }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; length ; 60 mins } }', 'tointer': 'select the rows whose length record fuzzily matches to 60 mins . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; length ; 60 mins } } ; 12 } = true', 'tointer': 'select the rows whose length record fuzzily matches to 60 mins . the number of such rows is 12 .'}
eq { count { filter_eq { all_rows ; length ; 60 mins } } ; 12 } = true
select the rows whose length record fuzzily matches to 60 mins . the number of such rows is 12 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'length_5': 5, '60 mins_6': 6, '12_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'length_5': 'length', '60 mins_6': '60 mins', '12_7': '12'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'length_5': [0], '60 mins_6': [0], '12_7': [2]}
['round', 'circuit', 'date', 'length', 'pole position', 'gt3 winner', 'gt4 winner']
[['1', 'oulton park', '25 april', '60 mins', 'no 5 scuderia vittoria', 'no 1 trackspeed', 'no 44 abg motorsport'], ['1', 'oulton park', '25 april', '60 mins', 'charles bateman michael lyons', 'david ashburn richard westbrook', 'peter belshaw marcus clutton'], ['2', 'oulton park', '25 april', '60 mins', 'no 1 trackspeed', 'no 5 scuderia vittoria', 'no 42 century motorsport'], ['2', 'oulton park', '25 april', '60 mins', 'david ashburn richard westbrook', 'charles bateman michael lyons', 'jake rattenbury josh wakefield'], ['3', 'snetterton 300', '15 may', '120 mins', 'no 10 crs racing', 'no 23 united autosports', 'no 44 abg motorsport'], ['3', 'snetterton 300', '15 may', '120 mins', 'glynn geddie jim geddie', 'matt bell michael guasch', 'peter belshaw marcus clutton'], ['4', 'brands hatch', '19 june', '120 mins', 'no 21 mtech', 'no 2 trackspeed', 'no 44 abg motorsport'], ['4', 'brands hatch', '19 june', '120 mins', 'duncan cameron matt griffin', 'tim bridgman gregor fisken', 'peter belshaw marcus clutton'], ['5', 'spa - francorchamps', '9 july', '60 mins', 'no 59 mclaren gt', 'no 1 trackspeed', 'no 50 scuderia vittoria'], ['5', 'spa - francorchamps', '9 july', '60 mins', 'chris goodwin andrew kirkaldy', 'david ashburn richard westbrook', 'dan denis david mcdonald'], ['6', 'spa - francorchamps', '9 july', '60 mins', 'no 1 trackspeed', 'no 21 mtech', 'no 48 lotus sport uk'], ['6', 'spa - francorchamps', '9 july', '60 mins', 'david ashburn richard westbrook', 'duncan cameron matt griffin', 'phil glew ollie jackson'], ['7', 'rockingham', '4 september', '60 mins', 'no 23 united autosports', 'no 7 beechdean motorsport', 'no 50 scuderia vittoria'], ['7', 'rockingham', '4 september', '60 mins', 'matt bell michael guasch', 'jonathan adam andrew howard', 'dan denis david mcdonald'], ['8', 'rockingham', '4 september', '60 mins', 'no 2 trackspeed', 'no 11 crs racing', 'no 50 scuderia vittoria'], ['8', 'rockingham', '4 september', '60 mins', 'tim bridgman gregor fisken', 'alex mortimer andrew tate', 'dan denis david mcdonald'], ['9', 'donington park', '25 september', '180 mins', 'no 1 trackspeed', 'no 5 scuderia vittoria', 'no 48 lotus sport uk'], ['9', 'donington park', '25 september', '180 mins', 'david ashburn stephen jelley', 'charles bateman michael lyons', 'phil glew james nash'], ['10', 'silverstone arena', '8 october', '120 mins', 'no 7 beechdean motorsport', 'no 7 beechdean motorsport', 'no 48 lotus sport uk']]
list of cities , towns and villages in vojvodina
https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-12.html.csv
unique
pivnice is the only settlement in vojvodina with slovaks as the largest ethnic group .
{'scope': 'all', 'row': '11', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'slovaks', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'largest ethnic group ( 2002 )', 'slovaks'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks .', 'tostr': 'filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } }', 'tointer': 'select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'largest ethnic group ( 2002 )', 'slovaks'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks .', 'tostr': 'filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks }'}, 'settlement'], 'result': 'pivnice', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } ; settlement }'}, 'pivnice'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } ; settlement } ; pivnice }', 'tointer': 'the settlement record of this unqiue row is pivnice .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } } ; eq { hop { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } ; settlement } ; pivnice } } = true', 'tointer': 'select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks . there is only one such row in the table . the settlement record of this unqiue row is pivnice .'}
and { only { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } } ; eq { hop { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } ; settlement } ; pivnice } } = true
select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks . there is only one such row in the table . the settlement record of this unqiue row is pivnice .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'largest ethnic group (2002)_7': 7, 'slovaks_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'settlement_9': 9, 'pivnice_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'largest ethnic group (2002)_7': 'largest ethnic group ( 2002 )', 'slovaks_8': 'slovaks', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'settlement_9': 'settlement', 'pivnice_10': 'pivnice'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'largest ethnic group (2002)_7': [0], 'slovaks_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'settlement_9': [2], 'pivnice_10': [3]}
['settlement', 'cyrillic name other names', 'type', 'population ( 2011 )', 'largest ethnic group ( 2002 )', 'dominant religion ( 2002 )']
[['bačka palanka', 'бачка паланка', 'town', '28239', 'serbs', 'orthodox christianity'], ['čelarevo', 'челарево', 'village', '4831', 'serbs', 'orthodox christianity'], ['despotovo', 'деспотово', 'village', '1853', 'serbs', 'orthodox christianity'], ['gajdobra', 'гајдобра', 'village', '2578', 'serbs', 'orthodox christianity'], ['karađorđevo', 'карађорђево', 'village', '738', 'serbs', 'orthodox christianity'], ['mladenovo', 'младеново', 'village', '2679', 'serbs', 'orthodox christianity'], ['neštin', 'нештин', 'village', '794', 'serbs', 'orthodox christianity'], ['nova gajdobra', 'нова гајдобра', 'village', '1220', 'serbs', 'orthodox christianity'], ['obrovac', 'обровац', 'village', '2944', 'serbs', 'orthodox christianity'], ['parage', 'параге', 'village', '921', 'serbs', 'orthodox christianity'], ['pivnice', 'пивнице ( slovak : pivnice )', 'village', '3337', 'slovaks', 'protestantism'], ['silbaš', 'силбаш', 'village', '2467', 'serbs', 'orthodox christianity'], ['tovariševo', 'товаришево', 'village', '2657', 'serbs', 'orthodox christianity']]
mannar district
https://en.wikipedia.org/wiki/Mannar_District
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24574438-1.html.csv
ordinal
chilawathurai had the 2nd lowest population density among main towns in the mannar district .
{'row': '4', 'col': '11', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'population density ( / km 2 )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; population density ( / km 2 ) ; 2 }'}, 'main town'], 'result': 'chilawathurai', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; population density ( / km 2 ) ; 2 } ; main town }'}, 'chilawathurai'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; population density ( / km 2 ) ; 2 } ; main town } ; chilawathurai } = true', 'tointer': 'select the row whose population density ( / km 2 ) record of all rows is 2nd minimum . the main town record of this row is chilawathurai .'}
eq { hop { nth_argmin { all_rows ; population density ( / km 2 ) ; 2 } ; main town } ; chilawathurai } = true
select the row whose population density ( / km 2 ) record of all rows is 2nd minimum . the main town record of this row is chilawathurai .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'population density ( / km 2 )_5': 5, '2_6': 6, 'main town_7': 7, 'chilawathurai_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', 'population density ( / km 2 )_5': 'population density ( / km 2 )', '2_6': '2', 'main town_7': 'main town', 'chilawathurai_8': 'chilawathurai'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'population density ( / km 2 )_5': [0], '2_6': [0], 'main town_7': [1], 'chilawathurai_8': [2]}
['ds division', 'main town', 'gn divisions', 'area ( km 2 )', 'sri lankan tamil', 'sri lankan moors', 'sinhalese', 'indian tamil', 'other', 'total', 'population density ( / km 2 )']
[['madhu', 'madhu', '17', '553', '6793', '559', '273', '5', '1', '7631', '14'], ['mannar', 'mannar', '49', '212', '40865', '8982', '953', '131', '6', '50937', '240'], ['manthai west', 'adampan', '36', '608', '12993', '1123', '337', '177', '0', '14630', '24'], ['musali', 'chilawathurai', '20', '475', '3042', '4818', '147', '2', '0', '8009', '17'], ['nanaddan', 'nanaddan', '31', '148', '16875', '605', '251', '79', '34', '17844', '121']]
fiba eurobasket 2007 squads
https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-16.html.csv
superlative
the oldest player in the fiba eurobasket 2007 squads was adam wójcik .
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'year born'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; year born }'}, 'player'], 'result': 'adam wójcik', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; year born } ; player }'}, 'adam wójcik'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; year born } ; player } ; adam wójcik } = true', 'tointer': 'select the row whose year born record of all rows is minimum . the player record of this row is adam wójcik .'}
eq { hop { argmin { all_rows ; year born } ; player } ; adam wójcik } = true
select the row whose year born record of all rows is minimum . the player record of this row is adam wójcik .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'year born_5': 5, 'player_6': 6, 'adam wójcik_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'year born_5': 'year born', 'player_6': 'player', 'adam wójcik_7': 'adam wójcik'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'year born_5': [0], 'player_6': [1], 'adam wójcik_7': [2]}
['player', 'height', 'position', 'year born', 'current club']
[['bartłomiej wołoszyn', '1.97', 'forward', '1986', 'anwil wloclawek'], ['andrzej pluta', '1.81', 'guard', '1974', 'anwil wloclawek'], ['robert skibniewski', '1.82', 'guard', '1983', 'bot turów'], ['robert witka', '2.06', 'forward', '1981', 'bot turów'], ['filip dylewicz', '2.02', 'forward', '1980', 'prokom trefl sopot'], ['radosław hyży', '2.00', 'forward', '1977', 'śląsk wrocław'], ['adam wójcik', '2.08', 'forward', '1970', "upea capo d'orlando"], ['kamil pietras', '2.04', 'forward', '1988', 'olimpija ljubljana'], ['szymon szewczyk', '2.09', 'center', '1982', 'lokomotiv rostov'], ['iwo kitzinger', '1.88', 'guard', '1985', 'bot turów'], ['przemysław frasunkiewicz', '2.01', 'forward', '1979', 'energa czarni'], ['łukasz koszarek', '1.87', 'guard', '1984', 'anwil wloclawek']]
bwf super series masters finals
https://en.wikipedia.org/wiki/BWF_Super_Series_Masters_Finals
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20361783-1.html.csv
unique
zhou mi only played in one bwf super series masters finals tournament .
{'scope': 'all', 'row': '5', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'zhou mi', 'subset': None}
{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'womens singles', 'zhou mi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose womens singles record fuzzily matches to zhou mi .', 'tostr': 'filter_eq { all_rows ; womens singles ; zhou mi }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; womens singles ; zhou mi } } = true', 'tointer': 'select the rows whose womens singles record fuzzily matches to zhou mi . there is only one such row in the table .'}
only { filter_eq { all_rows ; womens singles ; zhou mi } } = true
select the rows whose womens singles record fuzzily matches to zhou mi . 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, 'womens singles_4': 4, 'zhou mi_5': 5}
{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'womens singles_4': 'womens singles', 'zhou mi_5': 'zhou mi'}
{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'womens singles_4': [0], 'zhou mi_5': [0]}
['year', 'mens singles', 'womens singles', 'mens doubles', 'womens doubles', 'mixed doubles']
[['2012', 'chen long', 'li xuerui', 'mathias boe carsten mogensen', 'wang xiaoli yu yang', 'joachim fischer nielsen christinna pedersen'], ['2011', 'lin dan', 'wang yihan', 'mathias boe carsten mogensen', 'wang xiaoli yu yang', 'zhang nan zhao yunlei'], ['2010', 'lee chong wei', 'wang shixian', 'mathias boe carsten mogensen', 'wang xiaoli yu yang', 'zhang nan zhao yunlei'], ['2009', 'lee chong wei', 'wong mew choo', 'jung jae - sung lee yong - dae', 'wong pei tty chin eei hui', 'joachim fischer nielsen christinna pedersen'], ['2008', 'lee chong wei', 'zhou mi', 'koo kien keat tan boon heong', 'wong pei tty chin eei hui', 'thomas laybourn kamilla rytter juhl']]
2007 - 08 rangers f.c. season
https://en.wikipedia.org/wiki/2007%E2%80%9308_Rangers_F.C._season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11221038-3.html.csv
unique
filip šebo was the only player of slovakian nationality that left rangers f.c. during the 2007 - 08 season .
{'scope': 'all', 'row': '14', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'slovakia', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nat', 'slovakia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nat record fuzzily matches to slovakia .', 'tostr': 'filter_eq { all_rows ; nat ; slovakia }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nat ; slovakia } }', 'tointer': 'select the rows whose nat record fuzzily matches to slovakia . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nat', 'slovakia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nat record fuzzily matches to slovakia .', 'tostr': 'filter_eq { all_rows ; nat ; slovakia }'}, 'name'], 'result': 'filip šebo', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nat ; slovakia } ; name }'}, 'filip šebo'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nat ; slovakia } ; name } ; filip šebo }', 'tointer': 'the name record of this unqiue row is filip šebo .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nat ; slovakia } } ; eq { hop { filter_eq { all_rows ; nat ; slovakia } ; name } ; filip šebo } } = true', 'tointer': 'select the rows whose nat record fuzzily matches to slovakia . there is only one such row in the table . the name record of this unqiue row is filip šebo .'}
and { only { filter_eq { all_rows ; nat ; slovakia } } ; eq { hop { filter_eq { all_rows ; nat ; slovakia } ; name } ; filip šebo } } = true
select the rows whose nat record fuzzily matches to slovakia . there is only one such row in the table . the name record of this unqiue row is filip šebo .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nat_7': 7, 'slovakia_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'filip šebo_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nat_7': 'nat', 'slovakia_8': 'slovakia', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'filip šebo_10': 'filip šebo'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nat_7': [0], 'slovakia_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'filip šebo_10': [3]}
['nat', 'name', 'moving to', 'type', 'transfer window', 'transfer fee']
[['sco', 'martin ure', "queen 's park", 'end of contract', 'summer', 'n / a'], ['sco', 'scott hadden', 'ross county', 'end of contract', 'summer', 'n / a'], ['sco', 'steven campbell', 'free agent', 'end of contract', 'summer', 'n / a'], ['england', 'joe sagar', 'free agent', 'end of contract', 'summer', 'n / a'], ['sen', "makhtar n'diaye", 'free agent', 'end of contract', 'summer', 'n / a'], ['fra', 'antoine ponroy', 'free agent', 'end of contract', 'summer', 'n / a'], ['ger', 'stefan klos', 'retired', 'end of contract', 'summer', 'n / a'], ['croatia', 'dado pršo', 'retired', 'end of contract', 'summer', 'n / a'], ['sco', 'gavin rae', 'cardiff city', 'end of contract', 'summer', 'n / a'], ['sco', 'brian gilmour', 'queen of the south', 'end of contract', 'summer', 'n / a'], ['swe', 'karl svensson', 'caen', 'transfer', 'summer', '0.7 m'], ['eng', 'lee robinson', 'greenock morton', 'loan', 'summer', 'n / a'], ['cze', 'libor sionko', 'copenhagen', 'transfer', 'summer', '0.09 m'], ['slovakia', 'filip šebo', 'valenciennes', 'loan', 'summer', 'n / a'], ['sco', 'ian murray', 'norwich city', 'transfer', 'summer', 'free'], ['eng', 'ugo ehiogu', 'sheffield united', 'transfer', 'winter', 'free'], ['sco', 'alan hutton', 'tottenham hotspur', 'transfer', 'winter', '9 m'], ['nir', 'roy carroll', 'derby county', 'transfer', 'winter', 'free']]
élie bayol
https://en.wikipedia.org/wiki/%C3%89lie_Bayol
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1228323-1.html.csv
aggregation
between 1952 and 1956 , elie bayol scored a total of 2 points .
{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '2', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '2', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 2 } = true', 'tointer': 'the sum of the points record of all rows is 2 .'}
round_eq { sum { all_rows ; points } ; 2 } = true
the sum of the points record of all rows is 2 .
2
2
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '2_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '2_5': '2'}
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '2_5': [1]}
['year', 'entrant', 'chassis', 'engine', 'points']
[['1952', 'élie bayol', 'osca 20', 'osca straight - 6', '0'], ['1953', 'élie bayol', 'osca 20', 'osca straight - 6', '0'], ['1953', 'osca', 'osca 20', 'osca straight - 6', '0'], ['1954', 'equipe gordini', 'gordini type 16', 'gordini straight - 6', '2'], ['1955', 'equipe gordini', 'gordini type 16', 'gordini straight - 6', '0'], ['1956', 'gordini', 'gordini type 32', 'gordini straight - 8', '0']]
raman vasilyuk
https://en.wikipedia.org/wiki/Raman_Vasilyuk
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17373851-1.html.csv
majority
raman vasilyuk scored most of his international goals at the 2002 world cup qualifier .
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '2002 world cup qualifier', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'competition', '2002 world cup qualifier'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to 2002 world cup qualifier .', 'tostr': 'most_eq { all_rows ; competition ; 2002 world cup qualifier } = true'}
most_eq { all_rows ; competition ; 2002 world cup qualifier } = true
for the competition records of all rows , most of them fuzzily match to 2002 world cup qualifier .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, '2002 world cup qualifier_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', '2002 world cup qualifier_4': '2002 world cup qualifier'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], '2002 world cup qualifier_4': [0]}
['date', 'venue', 'score', 'result', 'competition']
[['16 august 2000', 'skonto stadium , riga , latvia', '1 - 0', '1 - 0', 'friendly'], ['28 march 2001', 'dynama stadium ( minsk ) , belarus', '2 - 1', '2 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '1 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '2 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '3 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '4 - 0', '4 - 1', '2002 world cup qualifier'], ['10 september 2003', 'sheriff stadium , tiraspol , moldova', '1 - 2', '1 - 2', 'euro 2004 qualifier'], ['6 june 2007', 'vasil levski national stadium , sofia , bulgaria', '1 - 0', '1 - 2', 'euro 2008 qualifier'], ['22 august 2007', 'dynama stadium ( minsk ) , belarus', '1 - 0', '2 - 1', 'friendly'], ['2 february 2008', "ta ' qali national stadium , attard , malta", '1 - 0', '2 - 0', 'malta international football tournament']]
slovak national badminton championships
https://en.wikipedia.org/wiki/Slovak_National_Badminton_Championships
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15740721-1.html.csv
ordinal
1994 was the second year that juraj brestovský won the men 's singles in the slovak national badminton championships .
{'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'year', '2'], 'result': '1994', 'ind': 0, 'tostr': 'nth_min { all_rows ; year ; 2 }', 'tointer': 'the 2nd minimum year record of all rows is 1994 .'}, '1994'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; year ; 2 } ; 1994 }', 'tointer': 'the 2nd minimum year record of all rows is 1994 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, "men 's singles"], 'result': 'juraj brestovský', 'ind': 3, 'tostr': "hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles }"}, 'juraj brestovský'], 'result': True, 'ind': 4, 'tostr': "eq { hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles } ; juraj brestovský }", 'tointer': "the men 's singles record of the row with 2nd minimum year record is juraj brestovský ."}], 'result': True, 'ind': 5, 'tostr': "and { eq { nth_min { all_rows ; year ; 2 } ; 1994 } ; eq { hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles } ; juraj brestovský } } = true", 'tointer': "the 2nd minimum year record of all rows is 1994 . the men 's singles record of the row with 2nd minimum year record is juraj brestovský ."}
and { eq { nth_min { all_rows ; year ; 2 } ; 1994 } ; eq { hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles } ; juraj brestovský } } = true
the 2nd minimum year record of all rows is 1994 . the men 's singles record of the row with 2nd minimum year record is juraj brestovský .
6
6
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'year_8': 8, '2_9': 9, '1994_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'year_12': 12, '2_13': 13, "men 's singles_14": 14, 'juraj brestovský_15': 15}
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'year_8': 'year', '2_9': '2', '1994_10': '1994', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'year_12': 'year', '2_13': '2', "men 's singles_14": "men 's singles", 'juraj brestovský_15': 'juraj brestovský'}
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'year_8': [0], '2_9': [0], '1994_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'year_12': [2], '2_13': [2], "men 's singles_14": [3], 'juraj brestovský_15': [4]}
['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles']
[['1993', 'juraj brestovský', 'ľuba hanzušová', 'juraj brestovský igor novák', 'ľuba hanzušová aurita hirková', 'peter púdela martina švecová'], ['1994', 'juraj brestovský', 'ľuba hanzušová', 'róbert cyprian peter púdela', 'ľuba hanzušová daniela tomášová', 'peter púdela martina švecová'], ['1995', 'igor novák', 'ľuba hanzušová', 'róbert cyprian peter púdela', 'katarína pokorná alexandra felgrová', 'peter púdela alexandra felgrová'], ['1996', 'marián šulko', 'alexandra felgrová', 'juraj brestovský igor novák', 'radka majorská barbora bobrovská', 'jaroslav heleš katarína pokorná'], ['1997', 'pavel mečár', 'kvetoslava orlovská', 'marián šulko marek navrátil', 'barbora bobrovská radka majorská', 'juraj brestovský zuzana kenížová'], ['1998', 'pavel mečár', 'kvetoslava orlovská', 'pavel mečár jaroslav marek', 'kvetoslava orlovská gabriela zabavníková', 'pavel mečár barbora bobrovská'], ['1999', 'marián šulko', 'kvetoslava orlovská', 'pavel mečár marián šulko', 'barbora bobrovská alexandra felgrová', 'pavel mečár barbora bobrovská'], ['2000', 'marián šulko', 'gabriela zabavníková', 'marián šulko pavel mečár', 'kvetoslava orlovská gabriela zabavníková', 'pavel mečár barbora bobrovská'], ['2001', 'marián šulko', 'gabriela zabavníková', 'marián šulko pavel mečár', 'barbora bobrovská eva sládeková', 'pavel mečár barbora bobrovská'], ['2002', 'lukáš klačanský', 'kvetoslava orlovská', 'marián šulko pavel mečár', 'kvetoslava orlovská gabriela zabavníková', 'pavel mečár barbora bobrovská'], ['2003', 'marián šulko', 'gabriela zabavníková', 'marián šulko pavel mečár', 'zuzana orlovská gabriela zabavníková', 'pavel mečár barbora bobrovská'], ['2004', 'marián šulko', 'kvetoslava orlovská', 'marián šulko pavel mečár', 'barbora bobrovská eva sládeková', 'pavel mečár barbora bobrovská'], ['2005', 'michal matejka', 'eva sládeková', 'marián šulko pavel mečár', 'alexandra felgrová kristína ludíková', 'pavel mečár barbora bobrovská'], ['2006', 'marián šulko', 'kristína ludíková', 'michal matejka marián šulko', 'alexandra felgrová kristína ludíková', 'ladislav tomčko kvetoslava orlovská'], ['2007', 'marián šulko', 'eva sládeková', 'vladimír závada marián smrek', 'kvetoslava orlovská zuzana orlovská', 'vladimír turlík gabriela zabavníková'], ['2008', 'marián šulko', 'kvetoslava orlovská', 'vladimír závada marián smrek', 'júlia turzáková gabriela zabavníková', 'marián smrek kvetoslava orlovská'], ['2009', 'michal matejka', 'monika fašungová', 'vladimír závada marián smrek', 'barbora bobrovská zuzana orlovská', 'vladimír závada zuzana orlovská'], ['2010', 'michal matejka', 'ivana kubíková', 'marián šulko pavel mečár', 'barbora bobrovská zuzana orlovská', 'vladimír závada zuzana orlovská']]
little league world series ( mid - atlantic region )
https://en.wikipedia.org/wiki/Little_League_World_Series_%28Mid-Atlantic_Region%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13012165-1.html.csv
ordinal
the 2nd to last year for the little league world series ( mid - atlantic region ) was when the new jersey team was paramus ll paramus .
{'row': '11', 'col': '1', 'order': '2', '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', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year ; 2 }'}, 'new jersey'], 'result': 'paramus ll paramus', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year ; 2 } ; new jersey }'}, 'paramus ll paramus'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; year ; 2 } ; new jersey } ; paramus ll paramus } = true', 'tointer': 'select the row whose year record of all rows is 2nd maximum . the new jersey record of this row is paramus ll paramus .'}
eq { hop { nth_argmax { all_rows ; year ; 2 } ; new jersey } ; paramus ll paramus } = true
select the row whose year record of all rows is 2nd maximum . the new jersey record of this row is paramus ll paramus .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'new jersey_7': 7, 'paramus ll paramus_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', 'year_5': 'year', '2_6': '2', 'new jersey_7': 'new jersey', 'paramus ll paramus_8': 'paramus ll paramus'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'new jersey_7': [1], 'paramus ll paramus_8': [2]}
['year', 'delaware', 'maryland', 'new jersey', 'new york', 'pennsylvania', 'washington , dc']
[['2001', 'midway ll wilmington', 'easton ll easton', 'randolph west ll randolph', 'rolando paulino ll bronx', 'state college american ll state college', 'capitol city ll'], ['2002', 'lower sussex ll frankford', 'south caroline ll preston', 'nottingham ll hamilton square', 'harlem ll manhattan', 'lehigh ll bethlehem', 'capitol city ll'], ['2003', 'naamans ll wilmington', 'west salisbury ll salisbury', 'freehold township american ll freehold', 'ramapo ll ramapo', 'lower perkiomen ll collegeville', 'capitol city ll'], ['2004', 'capitol ll wilmington', 'south caroline ll preston', 'htrba ll hamilton', 'colonie ll colonie', 'deep run valley ll hilltown', 'capitol city ll'], ['2005', 'canal ll bear', 'thurmont ll thurmont', 'toms river american ll toms river', 'merrick - north merrick ll merrick', 'council rock newtown ll newtown', 'no tournament'], ['2006', 'naamans ll wilmington', 'south caroline ll preston', 'livingston american ll livingston', 'mid - island ll staten island', 'butler township ll butler township', 'capitol city ll'], ['2007', 'mot ll middletown', 'west salisbury ll salisbury', 'randolph east ll randolph', 'maine - endwell ll endwell', 'council rock northampton ll northampton township', 'capitol city ll'], ['2008', 'mot ll middletown', 'hagerstown federal ll hagerstown', 'bordentown ll bordentown', 'haverstraw ll haverstraw', 'devon strafford ll devon', 'capitol city ll'], ['2009', 'mot ll middletown', 'conococheague ll williamsport', 'somerset hills ll bernardsville', 'south shore national ll staten island', 'moon township ll moon township', 'northwest washington ll'], ['2010', 'brandywine ll wilmington', 'railroaders ll brunswick', 'toms river national ll toms river', 'stony point ll stony point', 'council rock newtown ll newtown', 'capitol city ll'], ['2011', 'newark national ll newark', 'conocoheague ll williamsport', 'paramus ll paramus', 'great kills american ll staten island', 'keystone ll beech creek', 'northwest washington ll'], ['2012', 'newark national ll newark', 'west salisbury ll salisbury', 'par - troy east ll parsippany', 'stony point ll stony point', 'collier township athletic association collier', 'northwest washington ll']]
list of people in playboy 2000 - 09
https://en.wikipedia.org/wiki/List_of_people_in_Playboy_2000%E2%80%9309
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1566852-4.html.csv
comparative
tobey maguire appeared in playboy later than mike piazza in 2003 .
{'row_1': '8', 'row_2': '6', 'col': '1', 'col_other': '4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'interview subject', 'tobey maguire'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose interview subject record fuzzily matches to tobey maguire .', 'tostr': 'filter_eq { all_rows ; interview subject ; tobey maguire }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; interview subject ; tobey maguire } ; date }', 'tointer': 'select the rows whose interview subject record fuzzily matches to tobey maguire . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'interview subject', 'mike piazza'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose interview subject record fuzzily matches to mike piazza .', 'tostr': 'filter_eq { all_rows ; interview subject ; mike piazza }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; interview subject ; mike piazza } ; date }', 'tointer': 'select the rows whose interview subject record fuzzily matches to mike piazza . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; interview subject ; tobey maguire } ; date } ; hop { filter_eq { all_rows ; interview subject ; mike piazza } ; date } } = true', 'tointer': 'select the rows whose interview subject record fuzzily matches to tobey maguire . take the date record of this row . select the rows whose interview subject record fuzzily matches to mike piazza . take the date record of this row . the first record is greater than the second record .'}
greater { hop { filter_eq { all_rows ; interview subject ; tobey maguire } ; date } ; hop { filter_eq { all_rows ; interview subject ; mike piazza } ; date } } = true
select the rows whose interview subject record fuzzily matches to tobey maguire . take the date record of this row . select the rows whose interview subject record fuzzily matches to mike piazza . take the date 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, 'interview subject_7': 7, 'tobey maguire_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'interview subject_11': 11, 'mike piazza_12': 12, 'date_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', 'interview subject_7': 'interview subject', 'tobey maguire_8': 'tobey maguire', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'interview subject_11': 'interview subject', 'mike piazza_12': 'mike piazza', 'date_13': 'date'}
{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'interview subject_7': [0], 'tobey maguire_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'interview subject_11': [1], 'mike piazza_12': [1], 'date_13': [3]}
['date', 'cover model', 'centerfold model', 'interview subject', '20 questions']
[['1 - 03', 'tia carrere', 'rebecca anne ramos', 'halle berry', 'ron insana'], ['2 - 03', 'alison eastwood', 'charis boyle', 'jimmy kimmel', 'bernie mac'], ['3 - 03', 'dorismar', 'pennelope jimenez', 'colin farrell', 'juliette lewis'], ['4 - 03', 'carmen electra', 'carmella decesare', 'jay - z', 'andy richter'], ['5 - 03', 'torrie wilson', 'laurie fetter', 'billy bob thornton', 'jorja fox'], ['6 - 03', 'sarah kozer', 'tailor james', 'mike piazza', 'nelly'], ['7 - 03', 'nikki ziering', 'marketa janska', 'lisa marie presley', 'rachel weisz'], ['8 - 03', 'jenna morasca , heidi strobel', 'colleen marie', 'tobey maguire', 'charles rangel'], ['9 - 03', 'signe nordli', 'luci victoria', 'jon gruden', 'nicolas cage'], ['10 - 03', 'lauren hill', 'audra lynn', 'oj simpson', 'joe rogan'], ['11 - 03', 'daryl hannah', 'divini rae', 'quentin tarantino', 'bill murray'], ['12 - 03', 'shannen doherty', 'deisy teles and sarah teles', 'john cusack', 'william h macy']]
1972 miami dolphins season
https://en.wikipedia.org/wiki/1972_Miami_Dolphins_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14202514-1.html.csv
ordinal
the miami dolphins ' match against detroit lions was the earliest of the 1972 season games .
{'row': '1', 'col': '1', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'week', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; week ; 1 }'}, 'opponent'], 'result': 'detroit lions', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; week ; 1 } ; opponent }'}, 'detroit lions'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; week ; 1 } ; opponent } ; detroit lions } = true', 'tointer': 'select the row whose week record of all rows is 1st minimum . the opponent record of this row is detroit lions .'}
eq { hop { nth_argmin { all_rows ; week ; 1 } ; opponent } ; detroit lions } = true
select the row whose week record of all rows is 1st minimum . the opponent record of this row is detroit lions .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'week_5': 5, '1_6': 6, 'opponent_7': 7, 'detroit lions_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', 'week_5': 'week', '1_6': '1', 'opponent_7': 'opponent', 'detroit lions_8': 'detroit lions'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'week_5': [0], '1_6': [0], 'opponent_7': [1], 'detroit lions_8': [2]}
['week', 'date', 'opponent', 'result', 'record']
[['1', 'august 5 , 1972', 'detroit lions', 'l 23 - 31', '0 - 1'], ['2', 'august 12 , 1972', 'green bay packers', 'l 13 - 14', '0 - 2'], ['3', 'august 19 , 1972', 'cincinnati bengals', 'w 35 - 17', '1 - 2'], ['4', 'august 25 , 1972', 'atlanta falcons', 'w 24 - 10', '2 - 2'], ['5', 'august 31 , 1972', 'washington redskins', 'l 24 - 27', '2 - 3'], ['6', 'september 10 , 1972', 'minnesota vikings', 'w 21 - 19', '3 - 3']]
1943 vfl season
https://en.wikipedia.org/wiki/1943_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808346-13.html.csv
count
of the games in the 1943 vfl season that had a crowd over 10000 people , two of the away teams had a final score in the double digits .
{'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '10', 'result': '2', 'col': '4', 'subset': {'col': '6', 'criterion': 'greater_than', 'value': '10000'}}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; crowd ; 10000 }', 'tointer': 'select the rows whose crowd record is greater than 10000 .'}, 'away team score', '10'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose crowd record is greater than 10000 . among these rows , select the rows whose away team score record is greater than or equal to 10 .', 'tostr': 'filter_greater_eq { filter_greater { all_rows ; crowd ; 10000 } ; away team score ; 10 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater_eq { filter_greater { all_rows ; crowd ; 10000 } ; away team score ; 10 } }', 'tointer': 'select the rows whose crowd record is greater than 10000 . among these rows , select the rows whose away team score record is greater than or equal to 10 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater_eq { filter_greater { all_rows ; crowd ; 10000 } ; away team score ; 10 } } ; 2 } = true', 'tointer': 'select the rows whose crowd record is greater than 10000 . among these rows , select the rows whose away team score record is greater than or equal to 10 . the number of such rows is 2 .'}
eq { count { filter_greater_eq { filter_greater { all_rows ; crowd ; 10000 } ; away team score ; 10 } } ; 2 } = true
select the rows whose crowd record is greater than 10000 . among these rows , select the rows whose away team score record is greater than or equal to 10 . the number of such rows is 2 .
4
4
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'crowd_6': 6, '10000_7': 7, 'away team score_8': 8, '10_9': 9, '2_10': 10}
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'crowd_6': 'crowd', '10000_7': '10000', 'away team score_8': 'away team score', '10_9': '10', '2_10': '2'}
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'crowd_6': [0], '10000_7': [0], 'away team score_8': [1], '10_9': [1], '2_10': [3]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['melbourne', '9.6 ( 60 )', 'south melbourne', '21.13 ( 139 )', 'punt road oval', '14000', '7 august 1943'], ['footscray', '7.17 ( 59 )', 'richmond', '19.19 ( 133 )', 'western oval', '9000', '7 august 1943'], ['essendon', '11.24 ( 90 )', 'fitzroy', '8.8 ( 56 )', 'windy hill', '14000', '7 august 1943'], ['collingwood', '14.24 ( 108 )', 'north melbourne', '7.8 ( 50 )', 'victoria park', '5250', '7 august 1943'], ['carlton', '13.19 ( 97 )', 'hawthorn', '10.15 ( 75 )', 'princes park', '15000', '7 august 1943']]
2007 eneco tour
https://en.wikipedia.org/wiki/2007_Eneco_Tour
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12608303-1.html.csv
superlative
the longest distance of the 2007 eneco tour was stage two .
{'scope': 'all', 'col_superlative': '3', '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', 'distance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; distance }'}, 'stage'], 'result': '2', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; distance } ; stage }'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; distance } ; stage } ; 2 } = true', 'tointer': 'select the row whose distance record of all rows is maximum . the stage record of this row is 2 .'}
eq { hop { argmax { all_rows ; distance } ; stage } ; 2 } = true
select the row whose distance record of all rows is maximum . the stage record of this row is 2 .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'distance_5': 5, 'stage_6': 6, '2_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'distance_5': 'distance', 'stage_6': 'stage', '2_7': '2'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'distance_5': [0], 'stage_6': [1], '2_7': [2]}
['stage', 'route', 'distance', 'date', 'winner']
[['p', 'hasselt - hasselt', '5.1 km', 'wednesday , august 22', 'michiel elijzen'], ['1', 'waremme - eupen', '189.5 km', 'thursday , august 23', 'nick nuyens'], ['2', 'antwerp - knokke - heist', '199.1 km', 'friday , august 24', 'mark cavendish'], ['3', 'knokke - heist - putte', '170.8 km', 'saturday , august 25', 'robbie mcewen'], ['4', 'maldegem - terneuzen', '182.7 km', 'sunday , august 26', 'wouter weylandt'], ['5', 'terneuzen - nieuwegein', '179.9 km', 'monday , august 27', 'luciano pagliarini'], ['6', 'beek - landgraaf', '177.4 km', 'tuesday , august 28', 'pablo lastras'], ['7 ( itt )', 'sittard - geleen', '29.6 km', 'wednesday , august 29', 'sébastien rosseler']]
2004 amsterdam admirals season
https://en.wikipedia.org/wiki/2004_Amsterdam_Admirals_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24951872-2.html.csv
superlative
the waldstadion was the first game site used by the amsterdam admirals in the 2004 season .
{'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '7', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'game site'], 'result': 'waldstadion', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; game site }'}, 'waldstadion'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; game site } ; waldstadion } = true', 'tointer': 'select the row whose date record of all rows is minimum . the game site record of this row is waldstadion .'}
eq { hop { argmin { all_rows ; date } ; game site } ; waldstadion } = true
select the row whose date record of all rows is minimum . the game site record of this row is waldstadion .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'game site_6': 6, 'waldstadion_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'game site_6': 'game site', 'waldstadion_7': 'waldstadion'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'game site_6': [1], 'waldstadion_7': [2]}
['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance']
[['1', 'saturday , april 3', '7:00 pm', 'frankfurt galaxy', 'l 11 - 34', '0 - 1', 'waldstadion', '21269'], ['2', 'saturday , april 10', '7:00 pm', 'berlin thunder', 'l 17 - 28', '0 - 2', 'amsterdam arena', '10763'], ['3', 'sunday , april 18', '2:00 pm', 'scottish claymores', 'w 3 - 0', '1 - 2', 'hampden park', '10971'], ['4', 'sunday , april 25', '3:00 pm', 'frankfurt galaxy', 'w 21 - 17 ot', '2 - 2', 'amsterdam arena', '10684'], ['5', 'sunday , may 2', '4:00 pm', 'berlin thunder', 'l 29 - 33', '2 - 3', 'olympic stadium', '12909'], ['6', 'sunday , may 9', '4:00 pm', 'rhein fire', 'l 13 - 20', '2 - 4', 'arena aufschalke', '18790'], ['7', 'saturday , may 15', '7:00 pm', 'cologne centurions', 'w 17 - 10', '3 - 4', 'amsterdam arena', '14437'], ['8', 'friday , may 21', '8:00 pm', 'scottish claymores', 'l 17 - 19', '3 - 5', 'amsterdam arena', '10738'], ['9', 'sunday , may 30', '4:00 pm', 'cologne centurions', 'w 23 - 18', '4 - 5', 'rheinenergiestadion', '9056']]
list of nascar teams
https://en.wikipedia.org/wiki/List_of_NASCAR_teams
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1266602-2.html.csv
ordinal
the team that participated in the highest number of rounds was phil parsons racing .
{'row': '6', 'col': '7', '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', 'rounds', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; rounds ; 1 }'}, 'team'], 'result': 'phil parsons racing', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; rounds ; 1 } ; team }'}, 'phil parsons racing'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; rounds ; 1 } ; team } ; phil parsons racing } = true', 'tointer': 'select the row whose rounds record of all rows is 1st maximum . the team record of this row is phil parsons racing .'}
eq { hop { nth_argmax { all_rows ; rounds ; 1 } ; team } ; phil parsons racing } = true
select the row whose rounds record of all rows is 1st maximum . the team record of this row is phil parsons racing .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'rounds_5': 5, '1_6': 6, 'team_7': 7, 'phil parsons racing_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', 'rounds_5': 'rounds', '1_6': '1', 'team_7': 'team', 'phil parsons racing_8': 'phil parsons racing'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'rounds_5': [0], '1_6': [0], 'team_7': [1], 'phil parsons racing_8': [2]}
['team', 'car ( s )', 'driver ( s )', 'primary sponsor ( s )', 'owner ( s )', 'crew chief', 'rounds']
[['circle sport', 'chevrolet ss', 'tony raines', "little joe 's auto", 'joe falk', 'john rahlf', '25'], ['go green racing', 'ford fusion', 'brian keselowski', 'my 3 sons vending', 'bob keselowski', 'ben leslie', '7'], ['hillman racing', 'chevrolet ss', 'landon cassill', 'crc brakleen', 'mike hillman', 'mike abner', '9'], ['humphrey smith racing', 'chevrolet ss', 'mike bliss', 'n / a', 'randy humphrey', 'peter sospenzo', '22'], ['leavine family racing', 'ford fusion', 'reed sorenson', 'n / a', 'bob leavine', 'wally rogers', '16'], ['phil parsons racing', 'ford fusion', 'michael mcdowell', 'k - love / curb records', 'mike curb', 'gene nead', '26'], ['richard childress racing', 'chevrolet ss', 'austin dillon', 'advocare', 'richard childress', 'scott naset', '4'], ['wood brothers racing', 'ford fusion', 'trevor bayne', 'motorcraft / quick lane', 'glen wood', 'donnie wingo', '8'], ['xxxtreme motorsport', 'ford fusion', 'scott riggs', 'no label watches', 'john cohen', 'walter giles', '10']]
colts - patriots rivalry
https://en.wikipedia.org/wiki/Colts%E2%80%93Patriots_rivalry
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13342861-3.html.csv
majority
in the majority of games between new england patriots and the baltimore colts both teams score .
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '0', 'subset': None}
{'func': 'most_greater', 'args': ['all_rows', 'result', '0'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them are greater than 0 .', 'tostr': 'most_greater { all_rows ; result ; 0 } = true'}
most_greater { all_rows ; result ; 0 } = true
for the result records of all rows , most of them are greater than 0 .
1
1
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, '0_4': 4}
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', '0_4': '0'}
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], '0_4': [0]}
['year', 'date', 'winner', 'result', 'loser', 'location']
[['1970', 'october 4', 'baltimore colts', '14 - 6', 'boston patriots', 'harvard stadium'], ['1970', 'october 25', 'baltimore colts', '27 - 3', 'boston patriots', 'memorial stadium ( baltimore )'], ['1971', 'october 3', 'baltimore colts', '23 - 3', 'new england patriots', 'schaefer stadium'], ['1971', 'december 19', 'new england patriots', '21 - 17', 'baltimore colts', 'memorial stadium ( baltimore )'], ['1972', 'november 6', 'baltimore colts', '24 - 17', 'new england patriots', 'schaefer stadium'], ['1972', 'november 26', 'baltimore colts', '31 - 0', 'new england patriots', 'memorial stadium ( baltimore )'], ['1973', 'october 7', 'new england patriots', '24 - 16', 'baltimore colts', 'schaefer stadium'], ['1973', 'december 16', 'baltimore colts', '18 - 13', 'new england patriots', 'memorial stadium ( baltimore )'], ['1974', 'october 6', 'new england patriots', '42 - 3', 'baltimore colts', 'schaefer stadium'], ['1974', 'november 24', 'new england patriots', '27 - 17', 'baltimore colts', 'memorial stadium ( baltimore )'], ['1975', 'october 19', 'new england patriots', '21 - 10', 'baltimore colts', 'schaefer stadium'], ['1975', 'december 21', 'baltimore colts', '34 - 21', 'new england patriots', 'memorial stadium ( baltimore )'], ['1976', 'september 12', 'baltimore colts', '27 - 13', 'new england patriots', 'schaefer stadium'], ['1976', 'november 14', 'new england patriots', '21 - 14', 'baltimore colts', 'memorial stadium ( baltimore )'], ['1977', 'october 23', 'new england patriots', '17 - 3', 'baltimore colts', 'schaefer stadium'], ['1977', 'december 18', 'baltimore colts', '30 - 24', 'new england patriots', 'memorial stadium ( baltimore )'], ['1978', 'september 18', 'baltimore colts', '34 - 27', 'new england patriots', 'schaefer stadium'], ['1978', 'november 26', 'new england patriots', '35 - 14', 'baltimore colts', 'memorial stadium ( baltimore )'], ['1979', 'october 28', 'baltimore colts', '31 - 26', 'new england patriots', 'memorial stadium ( baltimore )'], ['1979', 'november 18', 'new england patriots', '50 - 21', 'baltimore colts', 'schaefer stadium']]
list of garfield and friends episodes
https://en.wikipedia.org/wiki/List_of_Garfield_and_Friends_episodes
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1852270-8.html.csv
comparative
the episode daydream doctor aired before the episode deja vu did .
{'row_1': '8', 'row_2': '14', 'col': '5', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'us acres episode', 'daydream doctor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us acres episode record fuzzily matches to daydream doctor .', 'tostr': 'filter_eq { all_rows ; us acres episode ; daydream doctor }'}, 'original airdate'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; us acres episode ; daydream doctor } ; original airdate }', 'tointer': 'select the rows whose us acres episode record fuzzily matches to daydream doctor . take the original airdate record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'us acres episode', 'deja vu'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose us acres episode record fuzzily matches to deja vu .', 'tostr': 'filter_eq { all_rows ; us acres episode ; deja vu }'}, 'original airdate'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; us acres episode ; deja vu } ; original airdate }', 'tointer': 'select the rows whose us acres episode record fuzzily matches to deja vu . take the original airdate record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; us acres episode ; daydream doctor } ; original airdate } ; hop { filter_eq { all_rows ; us acres episode ; deja vu } ; original airdate } } = true', 'tointer': 'select the rows whose us acres episode record fuzzily matches to daydream doctor . take the original airdate record of this row . select the rows whose us acres episode record fuzzily matches to deja vu . take the original airdate record of this row . the first record is less than the second record .'}
less { hop { filter_eq { all_rows ; us acres episode ; daydream doctor } ; original airdate } ; hop { filter_eq { all_rows ; us acres episode ; deja vu } ; original airdate } } = true
select the rows whose us acres episode record fuzzily matches to daydream doctor . take the original airdate record of this row . select the rows whose us acres episode record fuzzily matches to deja vu . take the original airdate record of this row . the first record is less than the second record .
5
5
{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'us acres episode_7': 7, 'daydream doctor_8': 8, 'original airdate_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'us acres episode_11': 11, 'deja vu_12': 12, 'original airdate_13': 13}
{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'us acres episode_7': 'us acres episode', 'daydream doctor_8': 'daydream doctor', 'original airdate_9': 'original airdate', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'us acres episode_11': 'us acres episode', 'deja vu_12': 'deja vu', 'original airdate_13': 'original airdate'}
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'us acres episode_7': [0], 'daydream doctor_8': [0], 'original airdate_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'us acres episode_11': [1], 'deja vu_12': [1], 'original airdate_13': [3]}
['episode', 'garfield episode 1', 'us acres episode', 'garfield episode 2', 'original airdate']
[['show 106', 'the legend of johnny ragweedseed', 'grape expectations ( part 1 )', "catch as cats ca n't", 'september 17 , 1994'], ['show 107', 'a matter of conscience', 'grape expectations ( part 2 )', 'top ten', 'september 17 , 1994'], ['show 108', 'change of mind', 'temp trouble', 'the perfect match', 'september 24 , 1994'], ['show 109', 'my fair feline', 'double trouble talk', 'half - baked alaska', 'september 24 , 1994'], ['show 110', 'puss in high - tops', 'egg over easy ( part 1 )', 'the beast from beyond', 'october 1 , 1994'], ['show 111', 'model behavior', 'egg over easy ( part 2 )', 'another ant episode', 'october 1 , 1994'], ['show 112', 'the guy of her dreams', 'the discount of monte cristo', 'the fairy dogmother', 'october 8 , 1994'], ['show 113', 'the stand - up mouse', 'daydream doctor', 'happy garfield day', 'october 8 , 1994'], ['show 114', 'sit on it', 'kiddy korner', 'brainware broadcast', 'october 15 , 1994'], ['show 115', 'suburban jungle', 'the thing in the box', 'the feline philosopher', 'october 22 , 1994'], ['show 116', 'thoroughly mixed - up mouse', 'the old man of the mountain', 'food fighter', 'october 29 , 1994'], ['show 117', 'the jelly roger', 'the farmyard feline philosopher', 'dogmother 2', 'november 5 , 1994'], ['show 118', 'alley katta and the 40 thieves', "if it 's tuesday this must be alpha centauri", 'clash of the titans', 'november 19 , 1994'], ['show 119', 'canned laughter', 'deja vu', 'the man who hated cats', 'november 26 , 1994'], ['show 120', 'the horror hostess ( part 1 )', 'newsworthy wade', 'the horror hostess ( part 2 )', 'december 3 , 1994']]
united states house of representatives elections , 1822
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1822
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668298-19.html.csv
comparative
weldon n edwards has a first elected year which is earlier than that of romulus m saunders ' .
{'row_1': '4', 'row_2': '6', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'weldon n edwards'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to weldon n edwards .', 'tostr': 'filter_eq { all_rows ; incumbent ; weldon n edwards }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; weldon n edwards } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to weldon n edwards . take the first elected record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'romulus m saunders'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to romulus m saunders .', 'tostr': 'filter_eq { all_rows ; incumbent ; romulus m saunders }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; romulus m saunders } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to romulus m saunders . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; weldon n edwards } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; romulus m saunders } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to weldon n edwards . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to romulus m saunders . take the first elected record of this row . the first record is less than the second record .'}
less { hop { filter_eq { all_rows ; incumbent ; weldon n edwards } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; romulus m saunders } ; first elected } } = true
select the rows whose incumbent record fuzzily matches to weldon n edwards . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to romulus m saunders . take the first elected record of this row . the first record is less than the second record .
5
5
{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'weldon n edwards_8': 8, 'first elected_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'romulus m saunders_12': 12, 'first elected_13': 13}
{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'weldon n edwards_8': 'weldon n edwards', 'first elected_9': 'first elected', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'romulus m saunders_12': 'romulus m saunders', 'first elected_13': 'first elected'}
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'weldon n edwards_8': [0], 'first elected_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'romulus m saunders_12': [1], 'first elected_13': [3]}
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
[['north carolina 2', 'hutchins g burton', 'democratic - republican', '1819', 're - elected', 'hutchins g burton ( c - dr ) jesse a dawson'], ['north carolina 4', 'william s blackledge', 'democratic - republican', '1821', 'retired democratic - republican hold', 'richard dobbs spaight , jr ( c - dr )'], ['north carolina 5', 'charles hooks', 'democratic - republican', '1816 ( special ) 1819', 're - elected', 'charles hooks ( c - dr ) john d jones'], ['north carolina 6', 'weldon n edwards', 'democratic - republican', '1816 ( special )', 're - elected', 'weldon n edwards ( c - dr ) 100 %'], ['north carolina 7', 'archibald mcneill', 'federalist', '1821', 'retired federalist hold', 'john culpepper ( a - f ) 50.9 % alexander mcneill 49.1 %'], ['north carolina 9', 'romulus m saunders', 'democratic - republican', '1821', 're - elected', 'romulus m saunders ( c - dr ) 100 %'], ['north carolina 10', 'john long', 'democratic - republican', '1821', 're - elected', 'john long ( c - dr ) 66.9 % john macclelland 33.1 %']]
portuguese legislative election , 2005
https://en.wikipedia.org/wiki/Portuguese_legislative_election%2C_2005
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1463383-1.html.csv
aggregation
the socialist party had an average poll rating of about 45 % . in 2005 .
{'scope': 'all', 'col': '3', 'type': 'average', 'result': '45 %', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'socialist'], 'result': '45 %', 'ind': 0, 'tostr': 'avg { all_rows ; socialist }'}, '45 %'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; socialist } ; 45 % } = true', 'tointer': 'the average of the socialist record of all rows is 45 % .'}
round_eq { avg { all_rows ; socialist } ; 45 % } = true
the average of the socialist record of all rows is 45 % .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'socialist_4': 4, '45%_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'socialist_4': 'socialist', '45%_5': '45 %'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'socialist_4': [0], '45%_5': [1]}
['date released', 'polling institute', 'socialist', 'social democratic', 'peoples party', 'green - communist', 'left bloc', 'lead']
[['february 20 , 2005', 'election results', '45.0 % 121 seats', '28.8 % 75 seats', '7.2 % 12 seats', '7.5 % 14 seats', '6.4 % 8 seats', '16.2 %'], ['february 18 , 2005', 'aximage', '46.8 %', '29.6 %', '7.3 %', '7.0 %', '5.5 %', '17.2 %'], ['february 18 , 2005', 'marktest', '46.0 %', '26.8 %', '7.5 %', '8.9 %', '7.7 %', '19.2 %'], ['february 18 , 2005', 'eurosondagem', '45.0 %', '30.6 %', '7.7 %', '7.7 %', '5.7 %', '14.4 %'], ['february 18 , 2005', 'ipom', '46.0 %', '30.0 %', '8.0 %', '6.0 %', '7.0 %', '16.0 %'], ['february 18 , 2005', 'intercampus', '45.9 %', '30.3 %', '7.1 %', '7.6 %', '5.2 %', '15.6 %'], ['february 17 , 2005', 'tns / euroteste', '39.0 %', '28.0 %', '7.0 %', '6.0 %', '6.0 %', '11.0 %'], ['february 17 , 2005', 'universidade católica', '46.0 %', '31.0 %', '6.0 %', '7.0 %', '7.0 %', '15.0 %'], ['february 12 , 2005', 'eurosondagem', '44.4 %', '31.3 %', '7.4 %', '6.9 %', '6.4 %', '13.1 %'], ['february 11 , 2005', 'aximage', '44.7 %', '27.4 %', '6.4 %', '7.1 %', '4.8 %', '17.3 %'], ['february 4 , 2005', 'ipom', '49.0 %', '31.0 %', '8.0 %', '6.0 %', '5.0 %', '18.0 %'], ['february 4 , 2005', 'aximage', '43.5 %', '29.3 %', '7.0 %', '5.6 %', '3.5 %', '14.2 %'], ['february 3 , 2005', 'intercampus', '46.5 %', '31.6 %', '4.8 %', '8.1 %', '4.5 %', '14.9 %'], ['january 29 , 2005', 'eurosondagem', '46.1 %', '32.1 %', '7.0 %', '6.6 %', '4.6 %', '14.0 %'], ['january 28 , 2005', 'marktest', '45.1 %', '27.7 %', '6.3 %', '7.7 %', '8.1 %', '17.5 %'], ['january 28 , 2005', 'aximage', '43.3 %', '27.4 %', '6.3 %', '5.8 %', '5.0 %', '15.9 %'], ['january 28 , 2005', 'universidade católica', '46.0 %', '28.0 %', '6.0 %', '8.0 %', '8.0 %', '18.0 %'], ['january 27 , 2005', 'tns / euroteste', '40.0 %', '32.0 %', '6.0 %', '4.0 %', '5.0 %', '8.0 %'], ['january 21 , 2005', 'axiamge', '42.8 %', '28.7 %', '7.1 %', '6.2 %', '4.3 %', '14.1 %']]
1998 st. louis rams season
https://en.wikipedia.org/wiki/1998_St._Louis_Rams_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10689097-1.html.csv
aggregation
the 1998 st. louis rams season has a total of 881037 attendance .
{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '881037', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '881037', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '881037'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 881037 } = true', 'tointer': 'the sum of the attendance record of all rows is 881037 .'}
round_eq { sum { all_rows ; attendance } ; 881037 } = true
the sum of the attendance record of all rows is 881037 .
2
2
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '881037_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '881037_5': '881037'}
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '881037_5': [1]}
['week', 'opponent', 'result', 'record', 'attendance']
[['1', 'new orleans saints', 'l 17 - 24', '0 - 1', '56943'], ['2', 'minnesota vikings', 'l 31 - 38', '0 - 2', '56234'], ['3', 'buffalo bills', 'w 34 - 33', '1 - 2', '65199'], ['4', 'arizona cardinals', 'l 17 - 20', '1 - 3', '55832'], ['6', 'new york jets', 'w 30 - 10', '2 - 3', '55938'], ['7', 'miami dolphins', 'l 0 - 14', '2 - 4', '65418'], ['8', 'san francisco 49ers', 'l 10 - 28', '2 - 5', '58563'], ['9', 'atlanta falcons', 'l 15 - 37', '2 - 6', '37996'], ['10', 'chicago bears', 'w 20 - 12', '3 - 6', '50263'], ['11', 'new orleans saints', 'l 3 - 24', '3 - 7', '46430'], ['12', 'carolina panthers', 'l 20 - 24', '3 - 8', '50716'], ['13', 'atlanta falcons', 'l 10 - 21', '3 - 9', '47971'], ['14', 'philadelphia eagles', 'l 14 - 17', '3 - 10', '66155'], ['15', 'new england patriots', 'w 32 - 18', '4 - 10', '48946'], ['16', 'carolina panthers', 'l 13 - 20', '4 - 11', '50047'], ['17', 'san francisco 49ers', 'l 19 - 38', '4 - 12', '68386']]
athletics at the 1986 central american and caribbean games
https://en.wikipedia.org/wiki/Athletics_at_the_1986_Central_American_and_Caribbean_Games
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10258265-3.html.csv
ordinal
colombia was the country that recorded the second most bronze medals in athletics at the 1986 central american and caribbean games .
{'row': '3', 'col': '5', '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', 'bronze', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; bronze ; 2 }'}, 'nation'], 'result': 'colombia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 2 } ; nation }'}, 'colombia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; colombia } = true', 'tointer': 'select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is colombia .'}
eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; colombia } = true
select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is colombia .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '2_6': 6, 'nation_7': 7, 'colombia_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', '2_6': '2', 'nation_7': 'nation', 'colombia_8': 'colombia'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '2_6': [0], 'nation_7': [1], 'colombia_8': [2]}
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
[['1', 'cuba', '27', '16', '8', '51'], ['2', 'mexico', '6', '9', '6', '21'], ['3', 'colombia', '3', '1', '7', '11'], ['4', 'bahamas', '2', '4', '3', '9'], ['5', 'puerto rico', '2', '3', '6', '11'], ['6', 'jamaica', '1', '3', '3', '7'], ['7', 'us virgin islands', '1', '0', '1', '2'], ['8', 'guyana', '1', '0', '0', '1'], ['9', 'dominican republic', '0', '4', '2', '6'], ['10', 'trinidad and tobago', '0', '2', '1', '3'], ['10', 'venezuela', '0', '2', '1', '3'], ['12', 'barbados', '0', '0', '2', '2'], ['13', 'haiti', '0', '0', '1', '1'], ['13', 'panama', '0', '0', '1', '1']]
list of la femme nikita episodes
https://en.wikipedia.org/wiki/List_of_La_Femme_Nikita_episodes
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10910712-5.html.csv
count
there were two episodes of la femme nikita that were written by david wolkove .
{'scope': 'all', 'criterion': 'equal', 'value': 'david wolkove', 'result': '2', 'col': '4', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'david wolkove'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to david wolkove .', 'tostr': 'filter_eq { all_rows ; written by ; david wolkove }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; written by ; david wolkove } }', 'tointer': 'select the rows whose written by record fuzzily matches to david wolkove . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; written by ; david wolkove } } ; 2 } = true', 'tointer': 'select the rows whose written by record fuzzily matches to david wolkove . the number of such rows is 2 .'}
eq { count { filter_eq { all_rows ; written by ; david wolkove } } ; 2 } = true
select the rows whose written by record fuzzily matches to david wolkove . the number of such rows is 2 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'written by_5': 5, 'david wolkove_6': 6, '2_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'written by_5': 'written by', 'david wolkove_6': 'david wolkove', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'david wolkove_6': [0], '2_7': [2]}
['episode', 'title', 'directed by', 'written by', 'original airdate']
[['89 ( 1 )', 'déjà vu all over again', 'jon cassar', 'robert cochran', 'january 7 , 2001'], ['90 ( 2 )', "a girl who was n't there", 'terry ingram', 'lawrence hertzog', 'january 14 , 2001'], ['91 ( 3 )', 'in through the out door', 'rené bonnière', 'david wolkove', 'january 21 , 2001'], ['92 ( 4 )', "all the world 's a stage", 'joel surnow', 'david wolkove', 'february 4 , 2001'], ['93 ( 5 )', 'the man behind the curtain', 'rené bonnière', 'lawrence hertzog', 'february 11 , 2001'], ['94 ( 6 )', 'the evil that men do', 'roy dupuis', 'andy horne & katherine tomlinson', 'february 18 , 2001'], ['95 ( 7 )', 'let no man put asunder', 'rené bonnière', 'lawrence hertzog', 'february 25 , 2001'], ['96 ( 8 )', 'a time for every purpose', 'brad turner', 'michael loceff', 'march 4 , 2001']]
patty schnyder
https://en.wikipedia.org/wiki/Patty_Schnyder
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1547798-2.html.csv
majority
most of patty schnyder 's matches were played 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]}
['date', 'tournament', 'surface', 'opponent in the final', 'score']
[['18 january 1998', 'hobart , australia', 'hard', 'dominique van roost', '6 - 3 , 6 - 2'], ['22 february 1998', 'hannover , germany', 'carpet ( i )', 'jana novotná', '6 - 0 , 3 - 6 , 7 - 5'], ['24 may 1998', 'madrid , spain', 'clay', 'dominique van roost', '3 - 6 , 6 - 4 , 6 - 0'], ['12 july 1998', 'maria lankowitz , austria', 'clay', 'gala león garcía', '6 - 2 , 4 - 6 , 6 - 3'], ['19 july 1998', 'palermo , italy', 'clay', 'barbara schett', '6 - 1 , 5 - 7 , 6 - 2'], ['10 january 1999', 'gold coast , australia', 'hard', 'mary pierce', '4 - 6 , 7 - 6 ( 5 ) , 6 - 2'], ['11 november 2001', 'pattaya city , thailand', 'hard', 'henrieta nagyová', '6 - 0 , 6 - 4'], ['20 october 2002', 'zürich , switzerland', 'carpet ( i )', 'lindsay davenport', '6 - 7 ( 5 ) , 7 - 6 ( 8 ) , 6 - 3'], ['8 january 2005', 'gold coast , australia', 'hard', 'samantha stosur', '1 - 6 , 6 - 3 , 7 - 5'], ['24 july 2005', 'cincinnati , usa', 'hard', 'akiko morigami', '6 - 4 , 6 - 0'], ['8 september 2008', 'bali , indonesia', 'hard', 'tamira paszek', '6 - 3 , 6 - 0']]
2008 - 09 portland trail blazers season
https://en.wikipedia.org/wiki/2008%E2%80%9309_Portland_Trail_Blazers_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17058178-11.html.csv
unique
the portland trailblazers only loss came was on april 5 .
{'scope': 'all', 'row': '2', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'l', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to l .', 'tostr': 'filter_eq { all_rows ; score ; l }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; l } }', 'tointer': 'select the rows whose score record fuzzily matches to l . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to l .', 'tostr': 'filter_eq { all_rows ; score ; l }'}, 'date'], 'result': 'april 5', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; l } ; date }'}, 'april 5'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; l } ; date } ; april 5 }', 'tointer': 'the date record of this unqiue row is april 5 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; l } } ; eq { hop { filter_eq { all_rows ; score ; l } ; date } ; april 5 } } = true', 'tointer': 'select the rows whose score record fuzzily matches to l . there is only one such row in the table . the date record of this unqiue row is april 5 .'}
and { only { filter_eq { all_rows ; score ; l } } ; eq { hop { filter_eq { all_rows ; score ; l } ; date } ; april 5 } } = true
select the rows whose score record fuzzily matches to l . there is only one such row in the table . the date record of this unqiue row is april 5 .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, 'l_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'april 5_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', 'l_8': 'l', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'april 5_10': 'april 5'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], 'l_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'april 5_10': [3]}
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
[['75', 'april 3', 'oklahoma city', 'w 107 - 72 ( ot )', 'lamarcus aldridge ( 35 )', 'lamarcus aldridge ( 18 )', 'steve blake ( 10 )', 'ford center 19136', '48 - 27'], ['76', 'april 5', 'houston', 'l 88 - 102 ( ot )', 'lamarcus aldridge , brandon roy ( 22 )', 'lamarcus aldridge ( 9 )', 'brandon roy ( 6 )', 'toyota center 18214', '48 - 28'], ['77', 'april 7', 'memphis', 'w 96 - 93 ( ot )', 'brandon roy ( 24 )', 'lamarcus aldridge ( 8 )', 'brandon roy ( 4 )', 'fedexforum 10089', '49 - 28'], ['78', 'april 8', 'san antonio', 'w 95 - 83 ( ot )', 'brandon roy ( 26 )', 'joel przybilla ( 17 )', 'steve blake ( 7 )', 'at & t center 18797', '50 - 28'], ['79', 'april 10', 'la lakers', 'w 106 - 98 ( ot )', 'brandon roy ( 24 )', 'joel przybilla ( 13 )', 'brandon roy ( 8 )', 'rose garden 20681', '51 - 28'], ['80', 'april 11', 'la clippers', 'w 87 - 72 ( ot )', 'lamarcus aldridge ( 21 )', 'joel przybilla ( 14 )', 'steve blake ( 5 )', 'staples center 18321', '52 - 28'], ['81', 'april 13', 'oklahoma city', 'w 113 - 83 ( ot )', 'travis outlaw ( 21 )', 'joel przybilla ( 12 )', 'sergio rodríguez ( 8 )', 'rose garden 20655', '53 - 28']]
list of england national rugby union team results 1970 - 79
https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1970%E2%80%9379
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178924-2.html.csv
count
england played against scotland in rugby tournaments in 1971 two times .
{'scope': 'all', 'criterion': 'equal', 'value': 'scotland', 'result': '2', 'col': '1', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opposing teams', 'scotland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opposing teams record fuzzily matches to scotland .', 'tostr': 'filter_eq { all_rows ; opposing teams ; scotland }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opposing teams ; scotland } }', 'tointer': 'select the rows whose opposing teams record fuzzily matches to scotland . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opposing teams ; scotland } } ; 2 } = true', 'tointer': 'select the rows whose opposing teams record fuzzily matches to scotland . the number of such rows is 2 .'}
eq { count { filter_eq { all_rows ; opposing teams ; scotland } } ; 2 } = true
select the rows whose opposing teams record fuzzily matches to scotland . 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, 'opposing teams_5': 5, 'scotland_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', 'opposing teams_5': 'opposing teams', 'scotland_6': 'scotland', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opposing teams_5': [0], 'scotland_6': [0], '2_7': [2]}
['opposing teams', 'against', 'date', 'venue', 'status']
[['wales', '3', '16 / 01 / 1971', 'cardiff arms park , cardiff', 'five nations'], ['ireland', '6', '13 / 02 / 1971', 'lansdowne road , dublin', 'five nations'], ['france', '14', '27 / 02 / 1971', 'twickenham , london', 'five nations'], ['scotland', '16', '20 / 03 / 1971', 'twickenham , london', 'five nations'], ['scotland', '26', '27 / 03 / 1971', 'murrayfield , edinburgh', 'rfu centenary match'], ["rfu president 's xv", '28', '17 / 04 / 1971', 'twickenham , london', 'rfu centenary match']]
1990 - 91 atlanta hawks season
https://en.wikipedia.org/wiki/1990%E2%80%9391_Atlanta_Hawks_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27882867-6.html.csv
unique
in the 1990-91 atlanta hawks season , the only game that took place at chicago stadium was on january 11 .
{'scope': 'all', 'row': '5', 'col': '8', 'col_other': '2', 'criterion': 'equal', 'value': 'chicago stadium', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'chicago stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to chicago stadium .', 'tostr': 'filter_eq { all_rows ; location attendance ; chicago stadium }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location attendance ; chicago stadium } }', 'tointer': 'select the rows whose location attendance record fuzzily matches to chicago stadium . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'chicago stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to chicago stadium .', 'tostr': 'filter_eq { all_rows ; location attendance ; chicago stadium }'}, 'date'], 'result': 'january 11', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location attendance ; chicago stadium } ; date }'}, 'january 11'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location attendance ; chicago stadium } ; date } ; january 11 }', 'tointer': 'the date record of this unqiue row is january 11 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location attendance ; chicago stadium } } ; eq { hop { filter_eq { all_rows ; location attendance ; chicago stadium } ; date } ; january 11 } } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to chicago stadium . there is only one such row in the table . the date record of this unqiue row is january 11 .'}
and { only { filter_eq { all_rows ; location attendance ; chicago stadium } } ; eq { hop { filter_eq { all_rows ; location attendance ; chicago stadium } ; date } ; january 11 } } = true
select the rows whose location attendance record fuzzily matches to chicago stadium . there is only one such row in the table . the date record of this unqiue row is january 11 .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location attendance_7': 7, 'chicago stadium_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'january 11_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location attendance_7': 'location attendance', 'chicago stadium_8': 'chicago stadium', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'january 11_10': 'january 11'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location attendance_7': [0], 'chicago stadium_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'january 11_10': [3]}
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
[['29', 'january 2', 'la clippers', 'w 120 - 107', 'd wilkins ( 35 )', 'd wilkins ( 16 )', 'g rivers ( 11 )', 'omni coliseum 8733', '16 - 13'], ['30', 'january 4', 'indiana', 'w 111 - 96', 'd wilkins ( 36 )', 'm malone ( 11 )', 'g rivers , r robinson ( 5 )', 'omni coliseum 10124', '17 - 13'], ['31', 'january 5', 'minnesota', 'w 117 - 112 ( ot )', 'j battle ( 27 )', 'k willis ( 19 )', 'j koncak ( 7 )', 'omni coliseum 10988', '18 - 13'], ['32', 'january 8', 'san antonio', 'w 109 - 98', 'd wilkins ( 40 )', 'k willis ( 9 )', 'g rivers ( 10 )', 'omni coliseum 12608', '19 - 13'], ['33', 'january 11', 'chicago', 'l 96 - 99', 'd wilkins ( 23 )', 'd wilkins ( 12 )', 'j battle ( 7 )', 'chicago stadium 18676', '19 - 14'], ['34', 'january 12', 'new york', 'l 92 - 99', 'd wilkins ( 22 )', 'g rivers ( 8 )', 'g rivers , r robinson ( 6 )', 'madison square garden 17457', '19 - 15'], ['35', 'january 14', 'new york', 'w 96 - 82', 'd wilkins ( 26 )', 'd wilkins ( 16 )', 'j battle , s moncrief ( 4 )', 'omni coliseum 12612', '20 - 15'], ['36', 'january 15', 'indiana', 'w 117 - 106', 'd wilkins ( 28 )', 'd wilkins ( 12 )', 'j battle ( 8 )', 'market square arena 9531', '21 - 15'], ['37', 'january 18', 'chicago', 'w 114 - 105', 'd wilkins ( 34 )', 'm malone ( 12 )', 'g rivers ( 5 )', 'omni coliseum 16390', '22 - 15'], ['38', 'january 19', 'new jersey', 'w 114 - 84', 'k willis ( 24 )', 'k willis ( 17 )', 'a webb ( 6 )', 'omni coliseum 15758', '23 - 15'], ['39', 'january 22', 'miami', 'w 118 - 107', 'k willis ( 29 )', 'k willis ( 10 )', 'g rivers , a webb , d wilkins ( 7 )', 'omni coliseum 10440', '24 - 15'], ['40', 'january 23', 'washington', 'l 99 - 104', 'd wilkins ( 27 )', 'd wilkins ( 13 )', 'g rivers ( 7 )', 'capital centre 9830', '24 - 16'], ['41', 'january 26', 'seattle', 'l 102 - 103', 'd wilkins ( 43 )', 'd wilkins ( 10 )', 'a webb ( 9 )', 'seattle center coliseum 12792', '24 - 17'], ['42', 'january 28', 'portland', 'l 111 - 116', 'd wilkins ( 34 )', 'k willis ( 10 )', 'a webb ( 11 )', 'memorial coliseum 12884', '24 - 18'], ['43', 'january 29', 'utah', 'l 105 - 116', 'd wilkins ( 24 )', 'd wilkins ( 14 )', 'a webb ( 4 )', 'salt palace 12616', '24 - 19']]
zorro ( musical )
https://en.wikipedia.org/wiki/Zorro_%28musical%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17143308-1.html.csv
count
zorro ( musical ) had a record result of been nominated 4 times .
{'scope': 'all', 'criterion': 'equal', 'value': 'nominated', 'result': '4', 'col': '5', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'nominated'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to nominated .', 'tostr': 'filter_eq { all_rows ; result ; nominated }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; nominated } }', 'tointer': 'select the rows whose result record fuzzily matches to nominated . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; nominated } } ; 4 } = true', 'tointer': 'select the rows whose result record fuzzily matches to nominated . the number of such rows is 4 .'}
eq { count { filter_eq { all_rows ; result ; nominated } } ; 4 } = true
select the rows whose result record fuzzily matches to nominated . the number of such rows is 4 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'nominated_6': 6, '4_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'nominated_6': 'nominated', '4_7': '4'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'nominated_6': [0], '4_7': [2]}
['year', 'award', 'category', 'nominee', 'result']
[['2009', 'laurence olivier award', 'best new musical', 'best new musical', 'nominated'], ['2009', 'laurence olivier award', 'best actor in a musical', 'matt rawle', 'nominated'], ['2009', 'laurence olivier award', 'best actress in a musical', 'emma williams', 'nominated'], ['2009', 'laurence olivier award', 'best performance in a supporting role in a musical', 'lesli margherita', 'won'], ['2009', 'laurence olivier award', 'best theatre choreographer', 'rafael amargo', 'nominated']]
1996 senior pga tour
https://en.wikipedia.org/wiki/1996_Senior_PGA_Tour
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11621873-4.html.csv
superlative
lee trevino had the highest earnings of any player in the 1996 senior pga tour .
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'earnings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; earnings }'}, 'player'], 'result': 'lee trevino', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; earnings } ; player }'}, 'lee trevino'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; earnings } ; player } ; lee trevino } = true', 'tointer': 'select the row whose earnings record of all rows is maximum . the player record of this row is lee trevino .'}
eq { hop { argmax { all_rows ; earnings } ; player } ; lee trevino } = true
select the row whose earnings record of all rows is maximum . the player record of this row is lee trevino .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'earnings_5': 5, 'player_6': 6, 'lee trevino_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'earnings_5': 'earnings', 'player_6': 'player', 'lee trevino_7': 'lee trevino'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'earnings_5': [0], 'player_6': [1], 'lee trevino_7': [2]}
['rank', 'player', 'country', 'earnings', 'wins']
[['1', 'lee trevino', 'united states', '6715649', '27'], ['2', 'bob charles', 'new zealand', '6621207', '23'], ['3', 'jim colbert', 'united states', '6570797', '18'], ['4', 'dave stockton', 'united states', '5781417', '13'], ['5', 'chi chi rodriguez', 'puerto rico', '5696544', '22']]
2008 - 09 phoenix suns season
https://en.wikipedia.org/wiki/2008%E2%80%9309_Phoenix_Suns_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-5.html.csv
count
during november of the 2008 - 09 season , the phoenix suns played 2 games against portland .
{'scope': 'all', 'criterion': 'equal', 'value': 'portland', 'result': '2', 'col': '3', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'portland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to portland .', 'tostr': 'filter_eq { all_rows ; team ; portland }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; portland } }', 'tointer': 'select the rows whose team record fuzzily matches to portland . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; portland } } ; 2 } = true', 'tointer': 'select the rows whose team record fuzzily matches to portland . the number of such rows is 2 .'}
eq { count { filter_eq { all_rows ; team ; portland } } ; 2 } = true
select the rows whose team record fuzzily matches to portland . 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, 'team_5': 5, 'portland_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', 'team_5': 'team', 'portland_6': 'portland', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'portland_6': [0], '2_7': [2]}
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
[['3', 'november 1', 'portland', 'w 107 - 96 ( ot )', "amar ' e stoudemire ( 23 )", "amar ' e stoudemire ( 13 )", 'steve nash ( 7 )', 'us airways center 18422', '2 - 1'], ['4', 'november 4', 'new jersey', 'w 114 - 86 ( ot )', 'raja bell ( 22 )', 'matt barnes ( 7 )', 'steve nash ( 11 )', 'izod center 15230', '3 - 1'], ['5', 'november 5', 'indiana', 'w 113 - 103 ( ot )', "amar ' e stoudemire ( 49 )", "amar ' e stoudemire ( 11 )", "amar ' e stoudemire , steve nash ( 6 )", 'conseco fieldhouse 11660', '4 - 1'], ['6', 'november 7', 'chicago', 'l 83 - 100 ( ot )', "amar ' e stoudemire ( 26 )", "robin lopez , amar ' e stoudemire ( 7 )", 'steve nash ( 5 )', 'united center 21967', '4 - 2'], ['7', 'november 8', 'milwaukee', 'w 104 - 96 ( ot )', "shaquille o'neal ( 29 )", "shaquille o'neal , grant hill ( 11 )", 'steve nash ( 7 )', 'bradley center 17935', '5 - 2'], ['8', 'november 10', 'memphis', 'w 107 - 102 ( ot )', 'leandro barbosa ( 27 )', 'matt barnes ( 8 )', 'steve nash ( 6 )', 'us airways center 18422', '6 - 2'], ['9', 'november 12', 'houston', 'l 82 - 94 ( ot )', "leandro barbosa , shaquille o'neal ( 18 )", "shaquille o'neal ( 13 )", "shaquille o'neal , steve nash ( 3 )", 'us airways center 18422', '6 - 3'], ['10', 'november 14', 'sacramento', 'w 97 - 95 ( ot )', "shaquille o'neal ( 29 )", "shaquille o'neal ( 13 )", "shaquille o'neal ( 6 )", 'arco arena 12810', '7 - 3'], ['11', 'november 16', 'detroit', 'w 104 - 86 ( ot )', "amar ' e stoudemire ( 29 )", "amar ' e stoudemire ( 11 )", 'steve nash ( 7 )', 'us airways center 18422', '8 - 3'], ['12', 'november 17', 'utah', 'l 97 - 109 ( ot )', "amar ' e stoudemire ( 30 )", "amar ' e stoudemire ( 8 )", 'steve nash ( 8 )', 'energysolutions arena 19911', '8 - 4'], ['13', 'november 20', 'la lakers', 'l 92 - 105 ( ot )', "amar ' e stoudemire ( 21 )", "shaquille o'neal ( 9 )", 'steve nash ( 10 )', 'us airways center 18422', '8 - 5'], ['14', 'november 22', 'portland', 'w 102 - 92 ( ot )', "shaquille o'neal ( 19 )", "shaquille o'neal ( 17 )", 'steve nash ( 7 )', 'us airways center 18422', '9 - 5'], ['15', 'november 25', 'oklahoma city', 'w 99 - 98 ( ot )', "amar ' e stoudemire ( 22 )", 'steve nash ( 8 )', 'steve nash ( 15 )', 'ford center 19136', '10 - 5'], ['16', 'november 26', 'minnesota', 'w 110 - 102 ( ot )', 'steve nash ( 20 )', "shaquille o'neal ( 10 )", 'steve nash ( 6 )', 'target center 11708', '11 - 5'], ['17', 'november 28', 'miami', 'l 92 - 107 ( ot )', 'leandro barbosa ( 20 )', "shaquille o'neal ( 9 )", 'leandro barbosa ( 5 )', 'us airways center 18422', '11 - 6'], ['18', 'november 30', 'new jersey', 'l 109 - 117 ( ot )', 'steve nash ( 26 )', "amar ' e stoudemire ( 12 )", 'steve nash ( 9 )', 'us airways center 18422', '11 - 7']]
2008 oafl season
https://en.wikipedia.org/wiki/2008_OAFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15764352-3.html.csv
ordinal
the kangaroos scored the most points at humber college north on 5-31-08 in the 2008 oafl season .
{'row': '2', 'col': '5', 'order': '1', 'col_other': '6', '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', 'score', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; score ; 1 }'}, 'ground'], 'result': 'humber college north', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; score ; 1 } ; ground }'}, 'humber college north'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; score ; 1 } ; ground } ; humber college north } = true', 'tointer': 'select the row whose score record of all rows is 1st maximum . the ground record of this row is humber college north .'}
eq { hop { nth_argmax { all_rows ; score ; 1 } ; ground } ; humber college north } = true
select the row whose score record of all rows is 1st maximum . the ground record of this row is humber college north .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, '1_6': 6, 'ground_7': 7, 'humber college north_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', 'score_5': 'score', '1_6': '1', 'ground_7': 'ground', 'humber college north_8': 'humber college north'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], '1_6': [0], 'ground_7': [1], 'humber college north_8': [2]}
['date', 'time', 'home', 'away', 'score', 'ground']
[['2008 - 05 - 31', '10:00', 'toronto downtown dingos', 'broadview hawks', '34 - 86', 'humber college north'], ['2008 - 05 - 31', '11:00', 'hamilton wildcats', 'etobicoke kangaroos', '52 - 110', 'humber college north'], ['2008 - 05 - 31', '14:00', 'ottawa swans', 'high park demons', '20 - 99', 'rideau carleton raceway'], ['2008 - 05 - 31', '14:00', 'guelph gargoyles', 'central blues', '65 - 19', 'magaret green park'], ['2008 - 05 - 31', '14:00', 'toronto eagles', 'toronto rebels', '106 - 35', 'humber college north']]
gilbert aldana
https://en.wikipedia.org/wiki/Gilbert_Aldana
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17441930-2.html.csv
majority
the majority of gilbert aldana 's fights ended in wins for gilbert aldana .
{'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'res', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the res records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; res ; win } = true'}
most_eq { all_rows ; res ; win } = true
for the res records of all rows , most of them fuzzily match to win .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'res_3': 3, 'win_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'res_3': 'res', 'win_4': 'win'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'res_3': [0], 'win_4': [0]}
['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location']
[['win', '6 - 2', 'rich beecroft', 'submission ( kimura )', 'ritc 90 - rage in the cage', '1', '0:26', 'arizona , united states'], ['loss', '5 - 2', 'cheick kongo', 'tko ( doctor stoppage )', 'ufc 61', '1', '4:13', 'nevada , united states'], ['loss', '5 - 1', 'paul buentello', 'tko ( strikes )', 'ufc 57', '2', '2:27', 'nevada , united states'], ['win', '5 - 0', 'chad armstrong', 'tko', 'ritc 75 - friday night fights', '1', '1:00', 'arizona , united states'], ['win', '4 - 0', 'melville calabaca', 'ko', 'ritc 70 - rage in the cage 70', '1', '0:30', 'arizona , united states'], ['win', '3 - 0', 'tim mcmullen', 'ko', 'ritc 65 - rage in the cage 65', '1', '0:15', 'arizona , united states'], ['win', '2 - 0', 'karl perkins', 'ko', 'ritc 62 - more punishment', '1', '1:55', 'arizona , united states'], ['win', '1 - 0', 'herb garcia', 'ko', 'ritc 61 - relentless', '1', '0:03', 'arizona , united states']]
jordi arrese
https://en.wikipedia.org/wiki/Jordi_Arrese
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1727920-2.html.csv
comparative
jordi arrese won a tennis tournament in bordeaux , france earlier than he won in san marino .
{'row_1': '2', 'row_2': '4', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'bordeaux , france'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to bordeaux , france .', 'tostr': 'filter_eq { all_rows ; tournament ; bordeaux , france }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; bordeaux , france } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to bordeaux , france . take the date record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'san marino'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to san marino .', 'tostr': 'filter_eq { all_rows ; tournament ; san marino }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; san marino } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to san marino . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; tournament ; bordeaux , france } ; date } ; hop { filter_eq { all_rows ; tournament ; san marino } ; date } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to bordeaux , france . take the date record of this row . select the rows whose tournament record fuzzily matches to san marino . take the date record of this row . the first record is less than the second record .'}
less { hop { filter_eq { all_rows ; tournament ; bordeaux , france } ; date } ; hop { filter_eq { all_rows ; tournament ; san marino } ; date } } = true
select the rows whose tournament record fuzzily matches to bordeaux , france . take the date record of this row . select the rows whose tournament record fuzzily matches to san marino . take the date record of this row . the first record is less than the second record .
5
5
{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'bordeaux , france_8': 8, 'date_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'san marino_12': 12, 'date_13': 13}
{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'bordeaux , france_8': 'bordeaux , france', 'date_9': 'date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'san marino_12': 'san marino', 'date_13': 'date'}
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'bordeaux , france_8': [0], 'date_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'san marino_12': [1], 'date_13': [3]}
['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score in the final']
[['runner - up', '1985', 'bologna , italy', 'clay', 'alberto tous', 'paolo canè simone colombo', '5 - 7 , 4 - 6'], ['winner', '1986', 'bordeaux , france', 'clay', 'david de miguel', 'ronald agénor mansour bahrami', '7 - 5 , 6 - 4'], ['winner', '1989', 'prague , czechoslovakia', 'clay', 'horst skoff', 'petr korda tomáš šmíd', '6 - 4 , 6 - 4'], ['winner', '1991', 'san marino', 'clay', 'carlos costa', 'christian miniussi diego pérez', '6 - 3 , 3 - 6 , 6 - 3'], ['runner - up', '1993', 'umag , croatia', 'clay', 'francisco roig', 'filip dewulf tom vanhoudt', '4 - 6 , 5 - 7'], ['runner - up', '1994', 'san marino', 'clay', 'renzo furlan', 'neil broad greg van emburgh', '4 - 6 , 6 - 7'], ['runner - up', '1994', 'bucharest , romania', 'clay', 'jose antonio conde', 'wayne arthurs simon youl', '4 - 6 , 4 - 6'], ['runner - up', '1995', 'oporto , portugal', 'clay', 'àlex corretja', 'tomás carbonell francisco roig', '3 - 6 , 6 - 7'], ['runner - up', '1995', 'kitzbühel , austria', 'clay', 'wayne arthurs', 'francisco montana greg van emburgh', '7 - 6 , 3 - 6 , 6 - 7'], ['winner', '1995', 'san marino', 'clay', 'andrew kratzmann', 'pablo albano federico mordegan', '7 - 6 , 3 - 6 , 6 - 2']]
zhang chunhui
https://en.wikipedia.org/wiki/Zhang_Chunhui
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11409274-2.html.csv
ordinal
the 2nd to last competition for zhang chunhui was when the venue was at olympic stadium in japan .
{'row': '7', 'col': '1', 'order': '7', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 7 }'}, 'venue'], 'result': 'olympic stadium , tokyo , japan', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 7 } ; venue }'}, 'olympic stadium , tokyo , japan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 7 } ; venue } ; olympic stadium , tokyo , japan } = true', 'tointer': 'select the row whose date record of all rows is 7th minimum . the venue record of this row is olympic stadium , tokyo , japan .'}
eq { hop { nth_argmin { all_rows ; date ; 7 } ; venue } ; olympic stadium , tokyo , japan } = true
select the row whose date record of all rows is 7th minimum . the venue record of this row is olympic stadium , tokyo , japan .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '7_6': 6, 'venue_7': 7, 'olympic stadium , tokyo , japan_8': 8}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '7_6': '7', 'venue_7': 'venue', 'olympic stadium , tokyo , japan_8': 'olympic stadium , tokyo , japan'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '7_6': [0], 'venue_7': [1], 'olympic stadium , tokyo , japan_8': [2]}
['date', 'venue', 'result', 'goals', 'competition']
[['14 january 2009', 'hong kong stadium , hong kong', '2 - 1', '0', 'friendly'], ['21 january 2009', 'hong kong stadium , hong kong', '1 - 3', '0', '2011 afc asian cup qualification'], ['28 january 2009', "ali muhesen stadium , sana'a , yemen", '0 - 1', '0', '2011 afc asian cup qualification'], ['27 august 2009', 'world games stadium , kaohsiung , taiwan', '12 - 0', '0', '2010 east asian football championship semi - final'], ['9 october 2009', 'outsourcing stadium , shizuoka , japan', '0 - 6', '0', '2011 afc asian cup qualification'], ['18 november 2009', 'hong kong stadium , hong kong', '0 - 4', '0', '2011 afc asian cup qualification'], ['7 february 2010', 'olympic stadium , tokyo , japan', '0 - 5', '0', '2010 east asian football championship'], ['17 november 2010', 'hong kong stadium , hong kong', '0 - 7', '0', 'friendly']]
1960 - 61 segunda división
https://en.wikipedia.org/wiki/1960%E2%80%9361_Segunda_Divisi%C3%B3n
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17715861-2.html.csv
ordinal
in the 1960-61 segunda división , among teams with 15 or more losses , cd tarrasa had the highest difference between goals for and goals against .
{'scope': 'subset', 'row': '16', 'col': '10', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '7', 'criterion': 'greater_than_eq', 'value': '15'}}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'losses', '15'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; losses ; 15 }', 'tointer': 'select the rows whose losses record is greater than or equal to 15 .'}, 'goal difference', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_greater_eq { all_rows ; losses ; 15 } ; goal difference ; 1 }'}, 'club'], 'result': 'cd tarrasa', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_greater_eq { all_rows ; losses ; 15 } ; goal difference ; 1 } ; club }'}, 'cd tarrasa'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_greater_eq { all_rows ; losses ; 15 } ; goal difference ; 1 } ; club } ; cd tarrasa } = true', 'tointer': 'select the rows whose losses record is greater than or equal to 15 . select the row whose goal difference record of these rows is 1st minimum . the club record of this row is cd tarrasa .'}
eq { hop { nth_argmin { filter_greater_eq { all_rows ; losses ; 15 } ; goal difference ; 1 } ; club } ; cd tarrasa } = true
select the rows whose losses record is greater than or equal to 15 . select the row whose goal difference record of these rows is 1st minimum . the club record of this row is cd tarrasa .
4
4
{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'losses_6': 6, '15_7': 7, 'goal difference_8': 8, '1_9': 9, 'club_10': 10, 'cd tarrasa_11': 11}
{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'losses_6': 'losses', '15_7': '15', 'goal difference_8': 'goal difference', '1_9': '1', 'club_10': 'club', 'cd tarrasa_11': 'cd tarrasa'}
{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'losses_6': [0], '15_7': [0], 'goal difference_8': [1], '1_9': [1], 'club_10': [2], 'cd tarrasa_11': [3]}
['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference']
[['1', 'ca osasuna', '30', '46', '21', '4', '5', '83', '25', '+ 58'], ['2', 'rc celta de vigo', '30', '40', '17', '6', '7', '56', '30', '+ 26'], ['3', 'deportivo la coruña', '30', '36', '15', '6', '9', '68', '47', '+ 21'], ['4', 'cd orense', '30', '36', '14', '8', '8', '45', '36', '+ 9'], ['5', 'pontevedra cf', '30', '31', '11', '9', '10', '39', '40', '- 1'], ['6', 'cd sabadell cf', '30', '31', '11', '9', '10', '30', '40', '- 10'], ['7', 'cultural leonesa', '30', '30', '11', '8', '11', '39', '42', '- 3'], ['8', 'cd basconia', '30', '29', '14', '1', '15', '41', '57', '- 16'], ['9', 'san sebastián cf', '30', '29', '11', '7', '12', '51', '50', '+ 1'], ['10', 'ud salamanca', '30', '29', '11', '7', '12', '42', '36', '+ 6'], ['11', 'sd indauchu', '30', '27', '12', '3', '15', '46', '59', '- 13'], ['12', 'cd condal 1', '30', '26', '8', '10', '12', '44', '49', '- 5'], ['13', 'real gijón', '30', '25', '10', '5', '15', '41', '53', '- 12'], ['14', 'club sestao', '30', '24', '8', '8', '14', '35', '51', '- 16'], ['15', 'baracaldo ah', '30', '22', '7', '8', '15', '33', '51', '- 18'], ['16', 'cd tarrasa', '30', '19', '5', '9', '16', '33', '60', '- 27']]
ednilson
https://en.wikipedia.org/wiki/Ednilson
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17226452-1.html.csv
count
ednilson played in teams in portugal for 5 consecutive years .
{'scope': 'all', 'criterion': 'equal', 'value': 'portugal', 'result': '5', 'col': '3', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'portugal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to portugal .', 'tostr': 'filter_eq { all_rows ; country ; portugal }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; portugal } }', 'tointer': 'select the rows whose country record fuzzily matches to portugal . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; portugal } } ; 5 } = true', 'tointer': 'select the rows whose country record fuzzily matches to portugal . the number of such rows is 5 .'}
eq { count { filter_eq { all_rows ; country ; portugal } } ; 5 } = true
select the rows whose country record fuzzily matches to portugal . the number of such rows is 5 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'portugal_6': 6, '5_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'portugal_6': 'portugal', '5_7': '5'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'portugal_6': [0], '5_7': [2]}
['season', 'team', 'country', 'division', 'apps', 'goals']
[['1999 - 00', 'roma', 'italy', '1', '1', '0'], ['2000 - 01', 'benfica', 'portugal', '1', '13', '0'], ['2001 - 02', 'benfica', 'portugal', '1', '22', '0'], ['2002 - 03', 'benfica', 'portugal', '1', '8', '0'], ['2003 - 04', 'vitória guimarães', 'portugal', '1', '8', '0'], ['2004 - 05', 'gil vicente', 'portugal', '1', '20', '0'], ['2005 - 06', 'ofi crete', 'greece', '1', '4', '0'], ['2006 - 07', 'ofi crete', 'greece', '1', '13', '0'], ['2007 - 08', 'partizan', 'serbia', '1', '14', '0'], ['2008 - 09', 'aek larnaca', 'cyprus', '1', '5', '0'], ['2009 - 10', 'dinamo tbilisi', 'georgia', '1', '29', '0']]
acc - big ten challenge
https://en.wikipedia.org/wiki/ACC%E2%80%93Big_Ten_Challenge
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1672976-1.html.csv
superlative
the georgia tech yellow jackets have the highest amount of losses in the acc - big ten challenge .
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'loss'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; loss }'}, 'institution'], 'result': 'georgia tech yellow jackets', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; loss } ; institution }'}, 'georgia tech yellow jackets'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; loss } ; institution } ; georgia tech yellow jackets } = true', 'tointer': 'select the row whose loss record of all rows is maximum . the institution record of this row is georgia tech yellow jackets .'}
eq { hop { argmax { all_rows ; loss } ; institution } ; georgia tech yellow jackets } = true
select the row whose loss record of all rows is maximum . the institution record of this row is georgia tech yellow jackets .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'loss_5': 5, 'institution_6': 6, 'georgia tech yellow jackets_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'loss_5': 'loss', 'institution_6': 'institution', 'georgia tech yellow jackets_7': 'georgia tech yellow jackets'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'loss_5': [0], 'institution_6': [1], 'georgia tech yellow jackets_7': [2]}
['institution', 'wins', 'loss', 'home wins', 'home losses', 'away wins', 'away losses', 'neutral wins', 'neutral losses']
[['boston college eagles', '6', '1', '3', '1', '3', '0', '0', '0'], ['clemson tigers', '9', '5', '4', '3', '5', '2', '0', '0'], ['duke blue devils', '12', '2', '5', '0', '3', '2', '4', '0'], ['florida state seminoles', '6', '8', '4', '3', '2', '5', '0', '0'], ['georgia tech yellow jackets', '4', '9', '3', '2', '1', '6', '0', '1'], ['maryland terrapins', '10', '4', '5', '1', '4', '1', '1', '2'], ['miami hurricanes', '2', '4', '2', '1', '0', '3', '0', '0'], ['north carolina tar heels', '7', '7', '3', '3', '2', '4', '2', '0'], ['nc state wolfpack', '5', '8', '4', '2', '1', '6', '0', '0'], ['notre dame fighting irish', '0', '0', '0', '0', '0', '0', '0', '0'], ['pitt panthers', '0', '0', '0', '0', '0', '0', '0', '0'], ['syracuse orange', '0', '0', '0', '0', '0', '0', '0', '0'], ['virginia cavaliers', '8', '5', '5', '1', '3', '4', '0', '0'], ['virginia tech hokies', '3', '5', '2', '2', '1', '3', '0', '0'], ['wake forest demon deacons', '10', '3', '6', '1', '4', '2', '0', '0'], ['overall', '82', '61', '46', '20', '29', '38', '7', '3']]
1990 u.s. open ( golf )
https://en.wikipedia.org/wiki/1990_U.S._Open_%28golf%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17129548-4.html.csv
aggregation
the average number of strokes to par at the 1990 u.s. open was -5.6 .
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '-5.6', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'to par'], 'result': '-5.6', 'ind': 0, 'tostr': 'avg { all_rows ; to par }'}, '-5.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; to par } ; -5.6 } = true', 'tointer': 'the average of the to par record of all rows is -5.6 .'}
round_eq { avg { all_rows ; to par } ; -5.6 } = true
the average of the to par record of all rows is -5.6 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'to par_4': 4, '-5.6_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '-5.6_5': '-5.6'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'to par_4': [0], '-5.6_5': [1]}
['place', 'player', 'country', 'score', 'to par']
[['1', 'tim simpson', 'united states', '66 + 69 = 135', '- 9'], ['2', 'jeff sluman', 'united states', '66 + 70 = 136', '- 8'], ['3', 'mike donald', 'united states', '67 + 70 = 137', '- 7'], ['4', 'mark brooks', 'united states', '68 + 70 = 138', '- 6'], ['t5', 'hale irwin', 'united states', '69 + 70 = 139', '- 5'], ['t5', 'scott simpson', 'united states', '66 + 73 = 139', '- 5'], ['t7', 'billy ray brown', 'united states', '69 + 71 = 140', '- 4'], ['t7', 'jim gallagher , jr', 'united states', '71 + 69 = 140', '- 4'], ['t7', 'john huston', 'united states', '68 + 72 = 140', '- 4'], ['t7', 'ian woosnam', 'wales', '70 + 70 = 140', '- 4']]
lt & sr 37 class
https://en.wikipedia.org/wiki/LT%26SR_37_Class
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20391799-1.html.csv
unique
the shoeburyness lt & sr 37 class locomotive was the only one withdrawn in 1952 .
{'scope': 'all', 'row': '9', 'col': '8', 'col_other': '2', 'criterion': 'equal', 'value': '1952', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'withdrawn', '1952'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose withdrawn record is equal to 1952 .', 'tostr': 'filter_eq { all_rows ; withdrawn ; 1952 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; withdrawn ; 1952 } }', 'tointer': 'select the rows whose withdrawn record is equal to 1952 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'withdrawn', '1952'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose withdrawn record is equal to 1952 .', 'tostr': 'filter_eq { all_rows ; withdrawn ; 1952 }'}, 'ltsr name'], 'result': 'shoeburyness', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; withdrawn ; 1952 } ; ltsr name }'}, 'shoeburyness'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; withdrawn ; 1952 } ; ltsr name } ; shoeburyness }', 'tointer': 'the ltsr name record of this unqiue row is shoeburyness .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; withdrawn ; 1952 } } ; eq { hop { filter_eq { all_rows ; withdrawn ; 1952 } ; ltsr name } ; shoeburyness } } = true', 'tointer': 'select the rows whose withdrawn record is equal to 1952 . there is only one such row in the table . the ltsr name record of this unqiue row is shoeburyness .'}
and { only { filter_eq { all_rows ; withdrawn ; 1952 } } ; eq { hop { filter_eq { all_rows ; withdrawn ; 1952 } ; ltsr name } ; shoeburyness } } = true
select the rows whose withdrawn record is equal to 1952 . there is only one such row in the table . the ltsr name record of this unqiue row is shoeburyness .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'withdrawn_7': 7, '1952_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'ltsr name_9': 9, 'shoeburyness_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'withdrawn_7': 'withdrawn', '1952_8': '1952', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'ltsr name_9': 'ltsr name', 'shoeburyness_10': 'shoeburyness'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'withdrawn_7': [0], '1952_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'ltsr name_9': [2], 'shoeburyness_10': [3]}
['ltsr no', 'ltsr name', 'builder', 'built', 'mr no', 'lms 1930 no', 'br no', 'withdrawn']
[['37', 'woodgrange', 'ss 4245', '1897', '2146', '2135', '41953', '1951'], ['38', 'westcliff', 'ss 4246', '1897', '2147', '2136', '41954', '1951'], ['39', 'forest gate', 'ss 4247', '1897', '2148', '2137', '41955', '1951'], ['40', 'benfleet', 'ss 4248', '1897', '2149', '2138', '41956', '1951'], ['41', 'leytonstone', 'ss 4249', '1897', '2150', '2139', '41957', '1951'], ['42', 'east horndon', 'ss 4250', '1897', '2151', '2140', '41958', '1951'], ['43', 'great ilford', 'dübs 3666', '1898', '2152', '2141', '41959', '1951'], ['44', 'prittlewell', 'dübs 3667', '1898', '2153', '2142', '41960', '1951'], ['45', 'shoeburyness', 'dübs 3668', '1898', '2154', '2143', '41961', '1952'], ['46', 'southchurch', 'dübs 3669', '1898', '2155', '2144', '41962', '1951'], ['47', 'stratford', 'dübs 3670', '1898', '2156', '2145', '41963', '1951']]
1935 in brazilian football
https://en.wikipedia.org/wiki/1935_in_Brazilian_football
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15358573-1.html.csv
comparative
sírio libanês played one less game than jardim américa .
{'row_1': '5', 'row_2': '6', 'col': '4', 'col_other': '2', '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', 'team', 'sírio libanês'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês .', 'tostr': 'filter_eq { all_rows ; team ; sírio libanês }'}, 'played'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; sírio libanês } ; played }', 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'jardim américa'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to jardim américa .', 'tostr': 'filter_eq { all_rows ; team ; jardim américa }'}, 'played'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; jardim américa } ; played }', 'tointer': 'select the rows whose team record fuzzily matches to jardim américa . take the played record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; hop { filter_eq { all_rows ; team ; jardim américa } ; played } }', 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row . select the rows whose team record fuzzily matches to jardim américa . take the played 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', 'team', 'sírio libanês'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês .', 'tostr': 'filter_eq { all_rows ; team ; sírio libanês }'}, 'played'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; sírio libanês } ; played }', 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row .'}, '12'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 }', 'tointer': 'the played record of the first row is 12 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'jardim américa'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to jardim américa .', 'tostr': 'filter_eq { all_rows ; team ; jardim américa }'}, 'played'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; jardim américa } ; played }', 'tointer': 'select the rows whose team record fuzzily matches to jardim américa . take the played record of this row .'}, '13'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 }', 'tointer': 'the played record of the second row is 13 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 } ; eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 } }', 'tointer': 'the played record of the first row is 12 . the played record of the second row is 13 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; hop { filter_eq { all_rows ; team ; jardim américa } ; played } } ; and { eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 } ; eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 } } } = true', 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row . select the rows whose team record fuzzily matches to jardim américa . take the played record of this row . the first record is less than the second record . the played record of the first row is 12 . the played record of the second row is 13 .'}
and { less { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; hop { filter_eq { all_rows ; team ; jardim américa } ; played } } ; and { eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 } ; eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 } } } = true
select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row . select the rows whose team record fuzzily matches to jardim américa . take the played record of this row . the first record is less than the second record . the played record of the first row is 12 . the played record of the second row is 13 .
13
9
{'and_8': 8, 'result_9': 9, 'less_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'team_11': 11, 'sírio libanês_12': 12, 'played_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'team_15': 15, 'jardim américa_16': 16, 'played_17': 17, 'and_7': 7, 'eq_5': 5, '12_18': 18, 'eq_6': 6, '13_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', 'team_11': 'team', 'sírio libanês_12': 'sírio libanês', 'played_13': 'played', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'team_15': 'team', 'jardim américa_16': 'jardim américa', 'played_17': 'played', 'and_7': 'and', 'eq_5': 'eq', '12_18': '12', 'eq_6': 'eq', '13_19': '13'}
{'and_8': [9], 'result_9': [], 'less_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'team_11': [0], 'sírio libanês_12': [0], 'played_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'team_15': [1], 'jardim américa_16': [1], 'played_17': [3], 'and_7': [8], 'eq_5': [7], '12_18': [5], 'eq_6': [7], '13_19': [6]}
['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference']
[['1', 'portuguesa', '22', '14', '2', '2', '17', '48'], ['2', 'ypiranga - sp', '22', '14', '0', '3', '33', '17'], ['3', 'estudantes', '20', '14', '2', '3', '16', '31'], ['4', 'ec são caetano', '16', '14', '2', '5', '31', '- 2'], ['5', 'sírio libanês', '12', '12', '2', '5', '31', '- 9'], ['6', 'jardim américa', '7', '13', '1', '9', '39', '- 16'], ['7', 'humberto primo', '7', '14', '1', '10', '48', '- 28'], ['8', 'ordem e progresso', '2', '13', '0', '12', '54', '- 41']]
list of australian football league pre - season and night series premiers
https://en.wikipedia.org/wiki/List_of_Australian_Football_League_pre-season_and_night_series_premiers
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1139835-9.html.csv
unique
the geelong premier was the only time that the venue was etihad stadium .
{'scope': 'all', 'row': '11', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'etihad stadium', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'etihad stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to etihad stadium .', 'tostr': 'filter_eq { all_rows ; venue ; etihad stadium }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; etihad stadium } }', 'tointer': 'select the rows whose venue record fuzzily matches to etihad stadium . 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', 'etihad stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to etihad stadium .', 'tostr': 'filter_eq { all_rows ; venue ; etihad stadium }'}, 'premier'], 'result': 'geelong', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; etihad stadium } ; premier }'}, 'geelong'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; etihad stadium } ; premier } ; geelong }', 'tointer': 'the premier record of this unqiue row is geelong .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; etihad stadium } } ; eq { hop { filter_eq { all_rows ; venue ; etihad stadium } ; premier } ; geelong } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to etihad stadium . there is only one such row in the table . the premier record of this unqiue row is geelong .'}
and { only { filter_eq { all_rows ; venue ; etihad stadium } } ; eq { hop { filter_eq { all_rows ; venue ; etihad stadium } ; premier } ; geelong } } = true
select the rows whose venue record fuzzily matches to etihad stadium . there is only one such row in the table . the premier record of this unqiue row is geelong .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'etihad stadium_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'premier_9': 9, 'geelong_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', 'etihad stadium_8': 'etihad stadium', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'premier_9': 'premier', 'geelong_10': 'geelong'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'etihad stadium_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'premier_9': [2], 'geelong_10': [3]}
['season', 'premier', 'runner up', 'score', 'venue', 'attendance', 'premiership']
[['1984', 'essendon', 'sydney swans', '13.11 ( 89 ) - 5.8 ( 38 )', 'waverley park', '30824', 'night series'], ['1984', 'essendon', 'hawthorn', '14.21 ( 105 ) - 12.9 ( 81 )', 'mcg', '92685', 'vfl grand final'], ['1986', 'hawthorn', 'carlton', '9.12 ( 66 ) - 5.6 ( 36 )', 'waverley park', '19627', 'night series'], ['1986', 'hawthorn', 'carlton', '16.14 ( 110 ) - 9.14 ( 68 )', 'mcg', '101861', 'vfl grand final'], ['1988', 'hawthorn', 'geelong', '10.10 ( 70 ) - 9.13 ( 67 )', 'waverley park', '35803', 'pre - season cup'], ['1988', 'hawthorn', 'melbourne', '22.20 ( 152 ) - 6.20 ( 56 )', 'mcg', '93754', 'vfl grand final'], ['1993', 'essendon', 'richmond', '14.18 ( 102 ) - 11.13 ( 79 )', 'waverley park', '75533', 'pre - season cup'], ['1993', 'essendon', 'carlton carlton', '20.13 ( 133 ) - 13.11 ( 89 )', 'mcg', '96862', 'afl grand final'], ['2000', 'essendon', 'north melbourne', '16.21 ( 117 ) - 11.10 ( 76 )', 'mcg', '56720', 'pre - season cup'], ['2000', 'essendon', 'melbourne', '19.21 ( 135 ) - 11.9 ( 75 )', 'mcg', '96249', 'afl grand final'], ['2009', 'geelong', 'collingwood', '0.18.19 ( 127 ) - 1.6.6 ( 51 )', 'etihad stadium', '37277', 'pre - season cup']]
three rivers conference ( indiana )
https://en.wikipedia.org/wiki/Three_Rivers_Conference_%28Indiana%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15176211-2.html.csv
comparative
triton joined the three rivers conference before oak hill joined the conference .
{'row_1': '3', 'row_2': '5', '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', 'school', 'triton'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to triton .', 'tostr': 'filter_eq { all_rows ; school ; triton }'}, 'year joined'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; triton } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to triton . take the year joined record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'oak hill'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose school record fuzzily matches to oak hill .', 'tostr': 'filter_eq { all_rows ; school ; oak hill }'}, 'year joined'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; school ; oak hill } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to oak hill . take the year joined record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; school ; triton } ; year joined } ; hop { filter_eq { all_rows ; school ; oak hill } ; year joined } } = true', 'tointer': 'select the rows whose school record fuzzily matches to triton . take the year joined record of this row . select the rows whose school record fuzzily matches to oak hill . take the year joined record of this row . the first record is less than the second record .'}
less { hop { filter_eq { all_rows ; school ; triton } ; year joined } ; hop { filter_eq { all_rows ; school ; oak hill } ; year joined } } = true
select the rows whose school record fuzzily matches to triton . take the year joined record of this row . select the rows whose school record fuzzily matches to oak hill . take the year joined 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, 'school_7': 7, 'triton_8': 8, 'year joined_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'school_11': 11, 'oak hill_12': 12, 'year joined_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', 'school_7': 'school', 'triton_8': 'triton', 'year joined_9': 'year joined', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'school_11': 'school', 'oak hill_12': 'oak hill', 'year joined_13': 'year joined'}
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'school_7': [0], 'triton_8': [0], 'year joined_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'school_11': [1], 'oak hill_12': [1], 'year joined_13': [3]}
['school', 'location', 'mascot', 'county', 'year joined', 'previous conference', 'year left', 'new conference']
[['caston', 'fulton', 'comets', '25 fulton', '1971', 'independents', '1978', 'joined midwest'], ['culver community', 'culver', 'cavaliers', '50 marshall', '1971', 'independents', '1976', 'independents'], ['triton', 'bourbon', 'trojans', '50 marshall', '1971', 'independent', '1980', 'joined northern state'], ['eastern ( greentown )', 'greentown', 'comets', '34 howard', '1980', 'mid - indiana', '1987', 'joined mid - indiana'], ['oak hill', 'converse', 'golden eagles', '27 grant', '1980', 'mid - indiana', '2006', 'joined central indiana']]
united states house of representatives elections , 1974
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1974
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341690-20.html.csv
majority
all of the maryland incumbents in the 1974 united states house of representatives elections were re-elected .
{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 're-elected', 'subset': None}
{'func': 'all_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , all of them fuzzily match to re-elected .', 'tostr': 'all_eq { all_rows ; result ; re-elected } = true'}
all_eq { all_rows ; result ; re-elected } = true
for the result records of all rows , all of them fuzzily match to re-elected .
1
1
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're-elected_4': 4}
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're-elected_4': 're-elected'}
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're-elected_4': [0]}
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
[['maryland 1', 'robert bauman', 'republican', '1973', 're - elected', 'robert bauman ( r ) 53.0 % thomas j hatem ( d ) 47.0 %'], ['maryland 2', 'clarence long', 'democratic', '1962', 're - elected', 'clarence long ( d ) 77.1 % john m seney ( r ) 22.9 %'], ['maryland 4', 'marjorie holt', 'republican', '1972', 're - elected', 'marjorie holt ( r ) 58.1 % fred l wineland ( d ) 41.9 %'], ['maryland 6', 'goodloe byron', 'democratic', '1970', 're - elected', 'goodloe byron ( d ) 73.7 % elton r wampler ( r ) 26.3 %'], ['maryland 7', 'parren mitchell', 'democratic', '1970', 're - elected', 'parren mitchell ( d ) unopposed']]
duneland athletic conference
https://en.wikipedia.org/wiki/Duneland_Athletic_Conference
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15090962-1.html.csv
comparative
merrillville joined the duneland athletic conference before laporte did .
{'row_1': '5', 'row_2': '4', 'col': '8', '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', 'school', 'merrillville'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to merrillville .', 'tostr': 'filter_eq { all_rows ; school ; merrillville }'}, 'year joined'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; merrillville } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to merrillville . take the year joined record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'laporte'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose school record fuzzily matches to laporte .', 'tostr': 'filter_eq { all_rows ; school ; laporte }'}, 'year joined'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; school ; laporte } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to laporte . take the year joined record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; school ; merrillville } ; year joined } ; hop { filter_eq { all_rows ; school ; laporte } ; year joined } } = true', 'tointer': 'select the rows whose school record fuzzily matches to merrillville . take the year joined record of this row . select the rows whose school record fuzzily matches to laporte . take the year joined record of this row . the first record is less than the second record .'}
less { hop { filter_eq { all_rows ; school ; merrillville } ; year joined } ; hop { filter_eq { all_rows ; school ; laporte } ; year joined } } = true
select the rows whose school record fuzzily matches to merrillville . take the year joined record of this row . select the rows whose school record fuzzily matches to laporte . take the year joined 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, 'school_7': 7, 'merrillville_8': 8, 'year joined_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'school_11': 11, 'laporte_12': 12, 'year joined_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', 'school_7': 'school', 'merrillville_8': 'merrillville', 'year joined_9': 'year joined', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'school_11': 'school', 'laporte_12': 'laporte', 'year joined_13': 'year joined'}
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'school_7': [0], 'merrillville_8': [0], 'year joined_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'school_11': [1], 'laporte_12': [1], 'year joined_13': [3]}
['school', 'location', 'mascot', 'county', 'enrollment 08 - 09', 'ihsaa class', 'ihsaa class football', 'year joined', 'previous conference']
[['chesterton', 'chesterton', 'trojans', '64 porter', '1921', '4a', '6a', '1970', 'calumet'], ['crown point', 'crown point', 'bulldogs', '45 lake', '2426', '4a', '6a', '1993', 'lake suburban'], ['lake central', 'saint john', 'indians', '45 lake', '3141', '4a', '6a', '2003', 'independents'], ['laporte', 'laporte', 'slicers', '46 laporte', '1956', '4a', '5a', '1976', 'northern indiana'], ['merrillville', 'merrillville', 'pirates', '45 lake', '2241', '4a', '6a', '1975', 'lake suburban'], ['michigan city', 'michigan city', 'wolves', '46 laporte', '1919', '4a', '5a', '1995', 'none ( new school )'], ['portage', 'portage', 'indians', '64 porter', '2618', '4a', '6a', '1970', 'calumet'], ['valparaiso', 'valparaiso', 'vikings', '64 porter', '2072', '4a', '6a', '1970', 'independents']]
virginia wade
https://en.wikipedia.org/wiki/Virginia_Wade
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-177273-2.html.csv
count
virginia wade participated in the us open tournament six times .
{'scope': 'all', 'criterion': 'equal', 'value': 'us open', 'result': '6', 'col': '3', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'championship', 'us open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose championship record fuzzily matches to us open .', 'tostr': 'filter_eq { all_rows ; championship ; us open }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; championship ; us open } }', 'tointer': 'select the rows whose championship record fuzzily matches to us open . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; championship ; us open } } ; 6 } = true', 'tointer': 'select the rows whose championship record fuzzily matches to us open . the number of such rows is 6 .'}
eq { count { filter_eq { all_rows ; championship ; us open } } ; 6 } = true
select the rows whose championship record fuzzily matches to us open . 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, 'championship_5': 5, 'us open_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', 'championship_5': 'championship', 'us open_6': 'us open', '6_7': '6'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'championship_5': [0], 'us open_6': [0], '6_7': [2]}
['outcome', 'year', 'championship', 'surface', 'partner', 'opponents', 'score']
[['runner - up', '1969', 'us open', 'grass', 'margaret court', 'françoise dürr darlene hard', '0 - 6 , 6 - 4 , 6 - 4'], ['runner - up', '1970', 'wimbledon', 'grass', 'françoise dürr', 'rosie casals billie jean king', '6 - 2 , 6 - 3'], ['runner - up', '1970', 'us open', 'grass', 'rosie casals', 'margaret court judy tegart dalton', '6 - 3 , 6 - 4'], ['runner - up', '1972', 'us open', 'grass', 'margaret court', 'françoise dürr betty stöve', '6 - 3 , 1 - 6 , 6 - 3'], ['winner', '1973', 'australian open', 'grass', 'margaret court', 'kerry harris kerry melville', '6 - 4 , 6 - 4'], ['winner', '1973', 'french open', 'clay', 'margaret court', 'françoise dürr betty stöve', '6 - 2 , 6 - 3'], ['winner', '1973', 'us open', 'grass', 'margaret court', 'rosie casals billie jean king', '2 - 6 , 6 - 3 , 7 - 5'], ['winner', '1975', 'us open', 'clay', 'margaret court', 'rosie casals billie jean king', '7 - 5 , 2 - 6 , 7 - 6 ( 5 )'], ['runner - up', '1976', 'us open', 'clay', 'olga morozova', 'linky boshoff ilana kloss', '6 - 1 , 6 - 4'], ['runner - up', '1979', 'french open', 'clay', 'françoise dürr', 'betty stöve wendy turnbull', '3 - 6 , 7 - 5 , 6 - 4']]
fiba oceania championship for women
https://en.wikipedia.org/wiki/FIBA_Oceania_Championship_for_Women
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13150131-4.html.csv
superlative
in the fiba oceania championship for women , the highest number of gold medals was won by the holder of rank 1 .
{'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'gold'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gold }'}, 'rank'], 'result': '1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gold } ; rank }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gold } ; rank } ; 1 } = true', 'tointer': 'select the row whose gold record of all rows is maximum . the rank record of this row is 1 .'}
eq { hop { argmax { all_rows ; gold } ; rank } ; 1 } = true
select the row whose gold record of all rows is maximum . the rank record of this row is 1 .
3
3
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'rank_6': 6, '1_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'rank_6': 'rank', '1_7': '1'}
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'rank_6': [1], '1_7': [2]}
['rank', 'gold', 'silver', 'bronze', 'total']
[['1', '3', '0', '0', '3'], ['2', '1', '3', '1', '5'], ['3', '1', '0', '0', '1'], ['5', '0', '2', '4', '6'], ['6', '0', '1', '1', '2']]
marc girardelli
https://en.wikipedia.org/wiki/Marc_Girardelli
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1376129-1.html.csv
majority
marc giradielli finished top 10 in season ranking for most of his career .
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': None}
{'func': 'most_less', 'args': ['all_rows', 'overall', '10'], 'result': True, 'ind': 0, 'tointer': 'for the overall records of all rows , most of them are less than 10 .', 'tostr': 'most_less { all_rows ; overall ; 10 } = true'}
most_less { all_rows ; overall ; 10 } = true
for the overall records of all rows , most of them are less than 10 .
1
1
{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'overall_3': 3, '10_4': 4}
{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'overall_3': 'overall', '10_4': '10'}
{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'overall_3': [0], '10_4': [0]}
['season', 'overall', 'slalom', 'giant slalom', 'super g', 'downhill', 'combined']
[['1980', '84', '-', '32', 'not run', '-', '-'], ['1981', '26', '15', '23', 'not run', '-', '-'], ['1982', '6', '8', '3', 'not run', '-', '-'], ['1983', '4', '7', '6', 'not awarded', '-', '3'], ['1984', '3', '1', '4', 'not awarded', '-', '34'], ['1985', '1', '1', '1', 'not awarded', '19', '-'], ['1986', '1', '11', '5', '3', '4', '2'], ['1987', '2', '28', '5', '2', '10', '-'], ['1988', '5', '23', '13', '4', '7', '-'], ['1989', '1', '3', '5', '5', '1', '1'], ['1990', '25', '15', '12', '-', '-', '-'], ['1991', '1', '1', '3', '10', '28', '1'], ['1992', '3', '12', '7', '2', '13', '11'], ['1993', '1', '13', '3', '5', '6', '1'], ['1994', '2', '29', '19', '2', '1', '-'], ['1995', '4', '9', '18', '10', '24', '1'], ['1996', '22', '20', '23', '51', '47', '2'], ['1997', '115', '58', '49', '-', '-', '-']]
2008 - 09 croatian cup
https://en.wikipedia.org/wiki/2008%E2%80%9309_Croatian_Cup
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18828647-1.html.csv
count
two of the rounds had 16 as the number of fixtures .
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '16', 'result': '2', 'col': '3', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'number of fixtures', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose number of fixtures record fuzzily matches to 16 .', 'tostr': 'filter_eq { all_rows ; number of fixtures ; 16 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; number of fixtures ; 16 } }', 'tointer': 'select the rows whose number of fixtures record fuzzily matches to 16 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; number of fixtures ; 16 } } ; 2 } = true', 'tointer': 'select the rows whose number of fixtures record fuzzily matches to 16 . the number of such rows is 2 .'}
eq { count { filter_eq { all_rows ; number of fixtures ; 16 } } ; 2 } = true
select the rows whose number of fixtures record fuzzily matches to 16 . 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, 'number of fixtures_5': 5, '16_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', 'number of fixtures_5': 'number of fixtures', '16_6': '16', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'number of fixtures_5': [0], '16_6': [0], '2_7': [2]}
['round', 'main date', 'number of fixtures', 'clubs', 'new entries this round']
[['preliminary round', '27 august 2008', '16', '48 → 32', 'none'], ['first round', '23 and 24 september 2008', '16', '32 → 16', '16'], ['second round', '29 october 2008', '8', '16 → 8', 'none'], ['quarter - finals', '12 and 26 november 2008', '8', '8 → 4', 'none'], ['semi - finals', '4 and 18 march 2009', '4', '4 → 2', 'none'], ['final', '13 and 28 may 2009', '2', '2 → 1', 'none']]
2006 sydney roosters season
https://en.wikipedia.org/wiki/2006_Sydney_Roosters_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18838673-1.html.csv
unique
the game against the north queensland cowboys was the only one played at dairy farmers stadium .
{'scope': 'all', 'row': '8', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'dairy farmers stadium', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'dairy farmers stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to dairy farmers stadium .', 'tostr': 'filter_eq { all_rows ; venue ; dairy farmers stadium }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; dairy farmers stadium } }', 'tointer': 'select the rows whose venue record fuzzily matches to dairy farmers stadium . 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', 'dairy farmers stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to dairy farmers stadium .', 'tostr': 'filter_eq { all_rows ; venue ; dairy farmers stadium }'}, 'opponent'], 'result': 'north queensland cowboys', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent }'}, 'north queensland cowboys'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent } ; north queensland cowboys }', 'tointer': 'the opponent record of this unqiue row is north queensland cowboys .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; dairy farmers stadium } } ; eq { hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent } ; north queensland cowboys } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to dairy farmers stadium . there is only one such row in the table . the opponent record of this unqiue row is north queensland cowboys .'}
and { only { filter_eq { all_rows ; venue ; dairy farmers stadium } } ; eq { hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent } ; north queensland cowboys } } = true
select the rows whose venue record fuzzily matches to dairy farmers stadium . there is only one such row in the table . the opponent record of this unqiue row is north queensland cowboys .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'dairy farmers stadium_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opponent_9': 9, 'north queensland cowboys_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', 'dairy farmers stadium_8': 'dairy farmers stadium', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opponent_9': 'opponent', 'north queensland cowboys_10': 'north queensland cowboys'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'dairy farmers stadium_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opponent_9': [2], 'north queensland cowboys_10': [3]}
['round', 'opponent', 'result', 'opp', 'venue']
[['1', 'south sydney rabbitohs', 'win', '22', 'aussie stadium'], ['2', 'melbourne storm', 'loss', '16', 'sfs'], ['3', 'canberra raiders', 'win', '26', 'sfs'], ['4', 'manly sea eagles', 'loss', '30', 'brookvale oval'], ['5', 'cronulla sharks', 'win', '24', 'toyota park'], ['6', 'brisbane broncos', 'loss', '24', 'sfs'], ['7', 'st george - illawarra dragons', 'loss', '22', 'aussie stadium'], ['8', 'north queensland cowboys', 'win', '18', 'dairy farmers stadium']]
peruvian segunda división
https://en.wikipedia.org/wiki/Peruvian_Segunda_Divisi%C3%B3n
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12335018-1.html.csv
count
7 teams started their current spell in the segunda division in 2013 .
{'scope': 'all', 'criterion': 'equal', 'value': '2013', 'result': '7', 'col': '5', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first season of current spell in segunda división', '2013'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first season of current spell in segunda división record is equal to 2013 .', 'tostr': 'filter_eq { all_rows ; first season of current spell in segunda división ; 2013 }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first season of current spell in segunda división ; 2013 } }', 'tointer': 'select the rows whose first season of current spell in segunda división record is equal to 2013 . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first season of current spell in segunda división ; 2013 } } ; 7 } = true', 'tointer': 'select the rows whose first season of current spell in segunda división record is equal to 2013 . the number of such rows is 7 .'}
eq { count { filter_eq { all_rows ; first season of current spell in segunda división ; 2013 } } ; 7 } = true
select the rows whose first season of current spell in segunda división record is equal to 2013 . the number of such rows is 7 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'first season of current spell in segunda división_5': 5, '2013_6': 6, '7_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'first season of current spell in segunda división_5': 'first season of current spell in segunda división', '2013_6': '2013', '7_7': '7'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'first season of current spell in segunda división_5': [0], '2013_6': [0], '7_7': [2]}
['team', 'city', 'founded', 'first season in segunda división', 'first season of current spell in segunda división', 'stadium', 'capacity', 'field', 'top division titles', 'last top division title']
[['alfonso ugarte', 'puno', '1928', '2006', '2013', 'enrique torres belón', '20000', 'grass', '0', '-'], ['alianza universidad', 'huánuco', '1939', '2012', '2012', 'heraclio tapia', '15000', 'grass', '0', '-'], ['atlético minero', 'matucana', '1997', '2006', '2009', 'municipal de matucana', '5000', 'grass', '0', '-'], ['atlético torino', 'talara', '1946', '2009', '2009', 'campeonísimo', '8000', 'grass', '0', '-'], ['defensor san alejandro', 'aguaytía', '1969', '2013', '2013', 'aliardo soria pérez', '13000', 'grass', '0', '-'], ['deportivo coopsol', 'chancay', '1964', '1999', '1999', 'rómulo shaw cisneros', '13000', 'grass', '1', '2000'], ['deportivo municipal', 'lima', '1935', '1968', '2013', 'miguel grau', '15000', 'grass', '2', '2006'], ['sport boys', 'callao', '1927', '1988', '2013', 'miguel grau', '15000', 'grass', '2', '2009'], ['sport victoria', 'ica', '1919', '2013', '2013', 'max augustín', '24576', 'grass', '0', '-'], ['sportivo huracán', 'arequipa', '1927', '2013', '2013', 'mariano melgar', '20000', 'grass', '0', '-'], ['walter ormeño', 'cañete', '1950', '1988', '2013', 'oscar ramos cabieses', '8000', 'grass', '0', '-']]
2009 - 10 pittsburgh panthers men 's basketball team
https://en.wikipedia.org/wiki/2009%E2%80%9310_Pittsburgh_Panthers_men%27s_basketball_team
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24925945-3.html.csv
aggregation
for the 2009 - 10 pittsburgh panthers men 's basketball team , the average weight for the players was 212.14 .
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '212.14', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weight ( lb )'], 'result': '212.14', 'ind': 0, 'tostr': 'avg { all_rows ; weight ( lb ) }'}, '212.14'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weight ( lb ) } ; 212.14 } = true', 'tointer': 'the average of the weight ( lb ) record of all rows is 212.14 .'}
round_eq { avg { all_rows ; weight ( lb ) } ; 212.14 } = true
the average of the weight ( lb ) record of all rows is 212.14 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weight ( lb )_4': 4, '212.14_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weight ( lb )_4': 'weight ( lb )', '212.14_5': '212.14'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weight ( lb )_4': [0], '212.14_5': [1]}
['name', '-', 'position', 'height', 'weight ( lb )', 'year', 'hometown', 'previous school']
[['chase adams', '3', 'guard', 'ft10in ( m )', '190', '2 senior', 'baltimore , md', 'centenary / mount saint joseph hs'], ['gilbert brown', '5', 'guard / forward', 'ft6in ( m )', '200', '2 junior ( rs )', 'harrisburg , pa', 'south kent school'], ['jermaine dixon', '24', 'guard', 'ft3in ( m )', '200', '3 senior , transfer', 'baltimore , md', 'tallahassee cc / maine central inst / blake hs'], ['tim frye', '44', 'guard', 'ft4in ( m )', '205', '2 junior', 'mars , pa', 'mars area hs'], ['ashton gibbs', '12', 'guard', 'ft2in ( m )', '190', '1 sophomore', 'scotch plains , nj', 'seton hall prep'], ['gary mcghee', '52', 'center', 'ft10in ( m )', '250', '2 junior', 'anderson , in', 'highland hs'], ['dwight miller', '25', 'forward', 'ft8in ( m )', '240', '1 freshman ( rs )', 'nassau , bahamas', 'st pius x hs'], ['lamar patterson', '21', 'guard / forward', 'ft5in ( m )', '220', '1 freshman', 'lancaster , pa', "st benedict 's prep / jp mccaskey hs"], ['jj richardson', '55', 'forward', 'ft7in ( m )', '235', '1 freshman', 'missouri city , tx', 'fort bend hightower hs'], ['nick rivers', '14', 'guard', 'ft0in ( m )', '180', '1 junior', 'phoenix , az', 'brophy college prep'], ['nasir robinson', '35', 'forward', 'ft5in ( m )', '220', '1 sophomore', 'chester , pa', 'chester hs'], ['dante taylor', '11', 'forward', 'ft9in ( m )', '240', '1 freshman', 'greenburgh , ny', 'national christian academy ( md )'], ['brad wanamaker', '22', 'guard', 'ft4in ( m )', '210', '2 junior', 'philadelphia , pa', 'roman catholic hs'], ['travon woodall', '1', 'guard', 'ft11in ( m )', '190', '1 freshman ( rs )', 'brooklyn , ny', 'st anthony hs']]
list of radio station callsigns in the northern territory
https://en.wikipedia.org/wiki/List_of_radio_station_callsigns_in_the_Northern_Territory
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14155573-2.html.csv
count
there are 6 areas served of radio stations in the northern territory .
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '2', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'area served'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose area served record is arbitrary .', 'tostr': 'filter_all { all_rows ; area served }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; area served } }', 'tointer': 'select the rows whose area served record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; area served } } ; 6 } = true', 'tointer': 'select the rows whose area served record is arbitrary . the number of such rows is 6 .'}
eq { count { filter_all { all_rows ; area served } } ; 6 } = true
select the rows whose area served 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, 'area served_5': 5, '6_6': 6}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'area served_5': 'area served', '6_6': '6'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'area served_5': [0], '6_6': [2]}
['callsign', 'area served', 'frequency', 'band', 'freq currently', 'purpose']
[['5al', 'alice springs', '1530', 'am', '8al ( 783 khz )', 'national'], ['5dr', 'darwin', '1500', 'am', 'see 8dr', 'national'], ['8dn', 'darwin', '1242', 'am', '8tab ( hpon )', 'commercial'], ['8dr', 'darwin', '0 657', 'am', '8rn', 'national'], ['8kn', 'katherine', '0 639', 'am', '8rn', 'national'], ['8tc', 'tennant creek', '0 684', 'am', '8rn', 'national']]
1997 world club championship
https://en.wikipedia.org/wiki/1997_World_Club_Championship
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10637415-1.html.csv
majority
in the '97 rugby world club championship , most of the clubs with differentials over 100 did n't lose a match .
{'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': {'col': '6', 'criterion': 'greater_than', 'value': '100'}}
{'func': 'most_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'diff', '100'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; diff ; 100 }', 'tointer': 'select the rows whose diff record is greater than 100 .'}, 'lost', '0'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose diff record is greater than 100 . for the lost records of these rows , most of them are equal to 0 .', 'tostr': 'most_eq { filter_greater { all_rows ; diff ; 100 } ; lost ; 0 } = true'}
most_eq { filter_greater { all_rows ; diff ; 100 } ; lost ; 0 } = true
select the rows whose diff record is greater than 100 . for the lost records of these rows , most of them are equal to 0 .
2
2
{'most_eq_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'diff_4': 4, '100_5': 5, 'lost_6': 6, '0_7': 7}
{'most_eq_1': 'most_eq', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'diff_4': 'diff', '100_5': '100', 'lost_6': 'lost', '0_7': '0'}
{'most_eq_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'diff_4': [0], '100_5': [0], 'lost_6': [1], '0_7': [1]}
['club', 'played', 'lost', 'drawn', 'against', 'diff', 'points']
[['brisbane broncos', '6', '0', '0', '52', '218', '12'], ['auckland warriors', '6', '0', '0', '82', '186', '12'], ['cronulla sharks', '6', '0', '0', '54', '176', '12'], ['penrith panthers', '6', '0', '0', '120', '136', '12'], ['canberra raiders', '6', '1', '0', '108', '194', '10'], ['canterbury bulldogs', '6', '2', '0', '121', '97', '8']]
list of supernanny episodes
https://en.wikipedia.org/wiki/List_of_Supernanny_episodes
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-5.html.csv
unique
the hillhouse - docherty family is the only episode of supernanny that was aired in the month of august .
{'scope': 'all', 'row': '1', 'col': '5', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': 'august', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'august'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to august .', 'tostr': 'filter_eq { all_rows ; original air date ; august }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; original air date ; august } }', 'tointer': 'select the rows whose original air date record fuzzily matches to august . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'august'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to august .', 'tostr': 'filter_eq { all_rows ; original air date ; august }'}, 'family / families'], 'result': 'the hillhouse - docherty family', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; original air date ; august } ; family / families }'}, 'the hillhouse - docherty family'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; original air date ; august } ; family / families } ; the hillhouse - docherty family }', 'tointer': 'the family / families record of this unqiue row is the hillhouse - docherty family .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; original air date ; august } } ; eq { hop { filter_eq { all_rows ; original air date ; august } ; family / families } ; the hillhouse - docherty family } } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to august . there is only one such row in the table . the family / families record of this unqiue row is the hillhouse - docherty family .'}
and { only { filter_eq { all_rows ; original air date ; august } } ; eq { hop { filter_eq { all_rows ; original air date ; august } ; family / families } ; the hillhouse - docherty family } } = true
select the rows whose original air date record fuzzily matches to august . there is only one such row in the table . the family / families record of this unqiue row is the hillhouse - docherty family .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'original air date_7': 7, 'august_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'family / families_9': 9, 'the hillhouse - docherty family_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'original air date_7': 'original air date', 'august_8': 'august', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'family / families_9': 'family / families', 'the hillhouse - docherty family_10': 'the hillhouse - docherty family'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'original air date_7': [0], 'august_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'family / families_9': [2], 'the hillhouse - docherty family_10': [3]}
['no overall', 'no in series', 'family / families', 'location ( s )', 'original air date']
[['uk16', '1', 'the hillhouse - docherty family', 'ayr ( scotland )', '29 august 2006'], ['uk17', '2', 'the howat family', 'shenley', '5 september 2006'], ['uk18', '3', 'the brown - smith family', 'warrington', '12 september 2006'], ['uk19', '4', 'the bates family', 'evesham', '19 september 2006'], ['uk20', '5', 'the williams family', 'birmingham', '26 september 2006']]
worcestershire county cricket club
https://en.wikipedia.org/wiki/Worcestershire_County_Cricket_Club
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1156428-2.html.csv
aggregation
the worcestershire county cricket club played a total of 1239 worcs f-c matches from 1910 - present .
{'scope': 'all', 'col': '4', 'type': 'sum', 'result': '1239', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'worcs f - c matches'], 'result': '1239', 'ind': 0, 'tostr': 'sum { all_rows ; worcs f - c matches }'}, '1239'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; worcs f - c matches } ; 1239 } = true', 'tointer': 'the sum of the worcs f - c matches record of all rows is 1239 .'}
round_eq { sum { all_rows ; worcs f - c matches } ; 1239 } = true
the sum of the worcs f - c matches record of all rows is 1239 .
2
2
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'worcs f - c matches_4': 4, '1239_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'worcs f - c matches_4': 'worcs f - c matches', '1239_5': '1239'}
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'worcs f - c matches_4': [0], '1239_5': [1]}
['name of ground', 'location', 'first - class span', 'worcs f - c matches', 'list a span', 'worcs la matches']
[['bournville cricket ground', 'bournville , birmingham', '1910 - 1911', '2', 'n / a', '0'], ['chain wire club ground', 'stourport - on - severn , worcestershire', '1980', '1', 'n / a', '0'], ['chester road north ground', 'kidderminster , worcestershire', '1921 - 2008', '68', '1969 - 2008', '5'], ['evesham cricket club ground', 'evesham , worcestershire', '1951', '1', 'n / a', '0'], ['new road ( county ground )', 'worcester', '1899 - present', '1072', '1963 - present', '425'], ['racecourse ground', 'hereford', '1919 - 1983', '5', '1983 - 1987', '3'], ['seth somers park', 'halesowen , west midlands', '1964 - 1969', '2', 'n / a', '0'], ['tipton road', 'dudley , west midlands', '1911 - 1971', '88', '1969 - 1977', '14']]
1979 - 80 philadelphia flyers season
https://en.wikipedia.org/wiki/1979%E2%80%9380_Philadelphia_Flyers_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208862-5.html.csv
ordinal
the philadelphia flyers ' game on january 19 recorded their highest attendance of the 1979 - 80 season .
{'row': '9', 'col': '6', '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': 'january 19', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; date }'}, 'january 19'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; january 19 } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the date record of this row is january 19 .'}
eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; january 19 } = true
select the row whose attendance record of all rows is 1st maximum . the date record of this row is january 19 .
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, 'january 19_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', 'january 19_8': 'january 19'}
{'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], 'january 19_8': [2]}
['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record']
[['january 4', 'philadelphia', '5 - 3', 'ny rangers', 'myre', '17398', '25 - 1 - 10'], ['january 6', 'philadelphia', '4 - 2', 'buffalo', 'peeters', '16433', '26 - 1 - 10'], ['january 7', 'philadelphia', '1 - 7', 'minnesota', 'myre', '15962', '26 - 2 - 10'], ['january 10', 'winnipeg', '4 - 5', 'philadelphia', 'peeters', '17077', '27 - 2 - 10'], ['january 12', 'philadelphia', '3 - 4', 'montreal', 'myre', '18091', '27 - 3 - 10'], ['january 13', 'st louis', '1 - 1', 'philadelphia', 'peeters', '17077', '27 - 3 - 11'], ['january 15', 'washington', '4 - 7', 'philadelphia', 'myre', '17077', '28 - 3 - 11'], ['january 17', 'chicago', '1 - 5', 'philadelphia', 'peeters', '17077', '29 - 3 - 11'], ['january 19', 'philadelphia', '4 - 4', 'washington', 'myre', '18130', '29 - 3 - 12'], ['january 22', 'philadelphia', '3 - 1', 'st louis', 'peeters', '17453', '30 - 3 - 12'], ['january 23', 'philadelphia', '4 - 1', 'chicago', 'myre', '17160', '31 - 3 - 12'], ['january 25', 'philadelphia', '5 - 4', 'winnipeg', 'peeters', '15122', '32 - 3 - 12'], ['january 27', 'philadelphia', '5 - 3', 'edmonton', 'peeters', '15423', '33 - 3 - 12'], ['january 31', 'minnesota', '2 - 4', 'philadelphia', 'st croix', '17077', '34 - 3 - 12']]
1979 vfl season
https://en.wikipedia.org/wiki/1979_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823719-21.html.csv
superlative
in the 1979 vfl season , the largest crowd occurred when collingwood was the home team .
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'home team'], 'result': 'collingwood', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; home team }'}, 'collingwood'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; home team } ; collingwood } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the home team record of this row is collingwood .'}
eq { hop { argmax { all_rows ; crowd } ; home team } ; collingwood } = true
select the row whose crowd record of all rows is maximum . the home team record of this row is collingwood .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'home team_6': 6, 'collingwood_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'home team_6': 'home team', 'collingwood_7': 'collingwood'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'home team_6': [1], 'collingwood_7': [2]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['melbourne', '24.17 ( 161 )', 'st kilda', '12.24 ( 96 )', 'mcg', '18435', '25 august 1979'], ['hawthorn', '7.18 ( 60 )', 'north melbourne', '24.21 ( 165 )', 'princes park', '18501', '25 august 1979'], ['geelong', '17.13 ( 115 )', 'richmond', '12.17 ( 89 )', 'kardinia park', '18039', '25 august 1979'], ['fitzroy', '22.19 ( 151 )', 'footscray', '14.16 ( 100 )', 'junction oval', '12076', '25 august 1979'], ['collingwood', '18.12 ( 120 )', 'carlton', '14.17 ( 101 )', 'victoria park', '36509', '25 august 1979'], ['essendon', '13.17 ( 95 )', 'south melbourne', '10.16 ( 76 )', 'vfl park', '32127', '25 august 1979']]
million dollar password
https://en.wikipedia.org/wiki/Million_Dollar_Password
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13673176-3.html.csv
superlative
the episode of the million dollar password game show , broadcast on sunday june 1 , 2008 , had the highest viewing figures .
{'scope': 'all', 'col_superlative': '6', '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', 'viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewers ( millions ) }'}, 'airdate'], 'result': 'sunday , june 1 , 2008', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewers ( millions ) } ; airdate }'}, 'sunday , june 1 , 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; viewers ( millions ) } ; airdate } ; sunday , june 1 , 2008 } = true', 'tointer': 'select the row whose viewers ( millions ) record of all rows is maximum . the airdate record of this row is sunday , june 1 , 2008 .'}
eq { hop { argmax { all_rows ; viewers ( millions ) } ; airdate } ; sunday , june 1 , 2008 } = true
select the row whose viewers ( millions ) record of all rows is maximum . the airdate record of this row is sunday , june 1 , 2008 .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewers (millions)_5': 5, 'airdate_6': 6, 'sunday , june 1 , 2008_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewers (millions)_5': 'viewers ( millions )', 'airdate_6': 'airdate', 'sunday , june 1 , 2008_7': 'sunday , june 1 , 2008'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewers (millions)_5': [0], 'airdate_6': [1], 'sunday , june 1 , 2008_7': [2]}
['airdate', 'celebrities', 'rating', 'share', '1849', 'viewers ( millions )', 'weekly rank', 'prod code']
[['sunday , june 1 , 2008', 'neil patrick harris , rachael ray', '6.8', '12', '2.2 / 7', '10.69', '3', '106'], ['sunday , june 8 , 2008', "tony hawk , rosie o'donnell", '6.3', '11', '2.1 / 6', '9.64', '5', '104'], ['thursday , june 12 , 2008', 'susie essman , betty white', '6.4', '12', '2.0 / 7', '9.52', '7', '102'], ['sunday , june 22 , 2008', 'shanna moakler , steven weber', '5.5', '10', '1.5 / 5', '8.29', '12', '105'], ['sunday , june 29 , 2008', 'sara evans , steve schirripa', '5.6', '10', '1.7 / 5', '8.55', '7', '101'], ['sunday , july 6 , 2008', 'monique coleman , damien fahey', '5.0', '9', '1.3 / 5', '7.53', '3', '103']]

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