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płock governorate | https://en.wikipedia.org/wiki/P%C5%82ock_Governorate | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12333984-1.html.csv | ordinal | the second most spoken language in the plock governorate is yiddish . | {'row': '2', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'number', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; number ; 2 }'}, 'language'], 'result': 'yiddish', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; number ; 2 } ; language }'}, 'yiddish'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; number ; 2 } ; language } ; yiddish } = true', 'tointer': 'select the row whose number record of all rows is 2nd maximum . the language record of this row is yiddish .'} | eq { hop { nth_argmax { all_rows ; number ; 2 } ; language } ; yiddish } = true | select the row whose number record of all rows is 2nd maximum . the language record of this row is yiddish . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'number_5': 5, '2_6': 6, 'language_7': 7, 'yiddish_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'number_5': 'number', '2_6': '2', 'language_7': 'language', 'yiddish_8': 'yiddish'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'number_5': [0], '2_6': [0], 'language_7': [1], 'yiddish_8': [2]} | ['language', 'number', 'percentage ( % )', 'males', 'females'] | [['polish', '447 685', '80.86', '216 794', '230 891'], ['yiddish', '51 215', '9.25', '24 538', '26 677'], ['german', '35 931', '6.49', '17 409', '18 522'], ['russian', '15 137', '2.73', '13 551', '1 586'], ['ukrainian', '2 350', '0.42', '2 302', '48'], ['other', '1 285', '0.23', '1 041', '244'], ["persons that did n't name their native language", '27', '> 0.01', '14', '13'], ['total', '553 633', '100', '275 652', '277 981']] |
win ( tv station ) | https://en.wikipedia.org/wiki/WIN_%28TV_station%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13596926-1.html.csv | majority | most of the channels have an analogue power of over 1000 kw . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1000 kw', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'analogue power', '1000 kw'], 'result': True, 'ind': 0, 'tointer': 'for the analogue power records of all rows , most of them are greater than 1000 kw .', 'tostr': 'most_greater { all_rows ; analogue power ; 1000 kw } = true'} | most_greater { all_rows ; analogue power ; 1000 kw } = true | for the analogue power records of all rows , most of them are greater than 1000 kw . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'analogue power_3': 3, '1000 kw_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'analogue power_3': 'analogue power', '1000 kw_4': '1000 kw'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'analogue power_3': [0], '1000 kw_4': [0]} | ['region served', 'ch 1', 'on - air date', 'analogue power', 'digital power', 'analogue haat', 'digital haat', 'transmitter location'] | [['canberra', '31 ( uhf )', '31 march 1989', '600 kw', '50 kw', '362 m', '362 m', 'black mountain'], ['central tablelands', '39 ( uhf )', '30 december 1989', '2000 kw', '570 kw', '627 m', '628 m', 'mount canobolas'], ['central western slopes', '32 ( uhf )', '30 december 1989', '1000 kw', '600 kw', '648 m', '653 m', 'mount cenn cruaich'], ['illawarra & regional sydney', '59 ( uhf )', '18 march 1962', '950 kw', '250 kw', '505 m', '600 m', 'knights hill'], ['south western slopes and eastern riverina', '32 ( uhf )', '30 december 1989', '1600 kw', '600 kw', '525 m', '540 m', 'mount ulandra']] |
8th coastal defence flotilla | https://en.wikipedia.org/wiki/8th_Coastal_Defence_Flotilla | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18965165-1.html.csv | comparative | there are more llublin class vessels in service than deba class vessels for the 8th coastal defence flotilla . | {'row_1': '2', 'row_2': '3', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'vessel', 'lublin class'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose vessel record fuzzily matches to lublin class .', 'tostr': 'filter_eq { all_rows ; vessel ; lublin class }'}, 'in service'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; vessel ; lublin class } ; in service }', 'tointer': 'select the rows whose vessel record fuzzily matches to lublin class . take the in service record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'vessel', 'deba class'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose vessel record fuzzily matches to deba class .', 'tostr': 'filter_eq { all_rows ; vessel ; deba class }'}, 'in service'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; vessel ; deba class } ; in service }', 'tointer': 'select the rows whose vessel record fuzzily matches to deba class . take the in service record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; vessel ; lublin class } ; in service } ; hop { filter_eq { all_rows ; vessel ; deba class } ; in service } } = true', 'tointer': 'select the rows whose vessel record fuzzily matches to lublin class . take the in service record of this row . select the rows whose vessel record fuzzily matches to deba class . take the in service record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; vessel ; lublin class } ; in service } ; hop { filter_eq { all_rows ; vessel ; deba class } ; in service } } = true | select the rows whose vessel record fuzzily matches to lublin class . take the in service record of this row . select the rows whose vessel record fuzzily matches to deba class . take the in service record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'vessel_7': 7, 'lublin class_8': 8, 'in service_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'vessel_11': 11, 'deba class_12': 12, 'in service_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'vessel_7': 'vessel', 'lublin class_8': 'lublin class', 'in service_9': 'in service', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'vessel_11': 'vessel', 'deba class_12': 'deba class', 'in service_13': 'in service'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'vessel_7': [0], 'lublin class_8': [0], 'in service_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'vessel_11': [1], 'deba class_12': [1], 'in service_13': [3]} | ['vessel', 'origin', 'type', 'in service', 'unit'] | [['xavery czernicki class', 'poland', 'logistic support', '1', '2nd minelaying and transport squadron'], ['lublin class', 'poland', 'landing craft', '5', '2nd minelaying and transport squadron'], ['deba class', 'poland', 'landing craft', '3', '2nd minelaying and transport squadron'], ['gardno class', 'poland', 'minesweeper', '12', '12th minesweeper squadron'], ['various class', 'poland', 'auxiliary vessels', '14', 'naval base swinoujscie ( auxiliary squadron )']] |
federal government college ikot ekpene | https://en.wikipedia.org/wiki/Federal_Government_College_Ikot_Ekpene | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11464746-1.html.csv | majority | all of the houses in the federal government college ikot ekpene have a coeducational composition . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'coed', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'composition', 'coed'], 'result': True, 'ind': 0, 'tointer': 'for the composition records of all rows , all of them fuzzily match to coed .', 'tostr': 'all_eq { all_rows ; composition ; coed } = true'} | all_eq { all_rows ; composition ; coed } = true | for the composition records of all rows , all of them fuzzily match to coed . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'composition_3': 3, 'coed_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'composition_3': 'composition', 'coed_4': 'coed'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'composition_3': [0], 'coed_4': [0]} | ['house name', 'composition', 'named after', 'founded', 'colours'] | [['benue', 'coed', 'river benue', '1973', 'yellow'], ['gongola', 'coed', 'gongola river', '1980', 'purple'], ['niger', 'coed', 'river niger', '1973', 'green'], ['rima', 'coed', 'rima river', '1980', 'brown'], ['ogun', 'coed', 'ogun river', '1980', 'blue']] |
portuguese legislative election , 1991 | https://en.wikipedia.org/wiki/Portuguese_legislative_election%2C_1991 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1886589-1.html.csv | unique | july 19 , 1987 was the only year were the lead was over 25 % . | {'scope': 'all', 'row': '17', 'col': '7', 'col_other': '1', 'criterion': 'greater_than', 'value': '25 %', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'lead', '25 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lead record is greater than 25 % .', 'tostr': 'filter_greater { all_rows ; lead ; 25 % }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; lead ; 25 % } }', 'tointer': 'select the rows whose lead record is greater than 25 % . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'lead', '25 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lead record is greater than 25 % .', 'tostr': 'filter_greater { all_rows ; lead ; 25 % }'}, 'date released'], 'result': 'july 19 , 1987', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; lead ; 25 % } ; date released }'}, 'july 19 , 1987'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; lead ; 25 % } ; date released } ; july 19 , 1987 }', 'tointer': 'the date released record of this unqiue row is july 19 , 1987 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; lead ; 25 % } } ; eq { hop { filter_greater { all_rows ; lead ; 25 % } ; date released } ; july 19 , 1987 } } = true', 'tointer': 'select the rows whose lead record is greater than 25 % . there is only one such row in the table . the date released record of this unqiue row is july 19 , 1987 .'} | and { only { filter_greater { all_rows ; lead ; 25 % } } ; eq { hop { filter_greater { all_rows ; lead ; 25 % } ; date released } ; july 19 , 1987 } } = true | select the rows whose lead record is greater than 25 % . there is only one such row in the table . the date released record of this unqiue row is july 19 , 1987 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'lead_7': 7, '25%_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date released_9': 9, 'july 19 , 1987_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'lead_7': 'lead', '25%_8': '25 %', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date released_9': 'date released', 'july 19 , 1987_10': 'july 19 , 1987'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'lead_7': [0], '25%_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date released_9': [2], 'july 19 , 1987_10': [3]} | ['date released', 'polling institute', 'social democratic', 'socialist', 'green - communist', 'democratic and social centre', 'lead'] | [['october 6 , 1991', 'election results', '50.6 % 135 seats', '29.1 % 72 seats', '8.8 % 17 seats', '4.4 % 5 seats', '21.5 %'], ['october 6 , 1991', 'exit poll - rtp1 universidade católica', '48.0 % - 51.9 %', '28.5 % - 31.5 %', '7.5 % - 10.0 %', '4.5 % - 5.5 %', '19.5 % - 20.4 %'], ['october 6 , 1991', 'exit poll - tsf / expresso euroexpansão', '45.8 % - 50.2 %', '29.8 % - 33.9 %', '6.8 % - 9.1 %', '3.7 % - 5.5 %', '16.0 % - 16.3 %'], ['october 6 , 1991', 'exit poll - antena1 euroteste', '47.0 % - 50.0 %', '31.0 % - 34.0 %', '7.5 % - 10.0 %', '4.0 % - 5.0 %', '16.0 %'], ['september 28 , 1991', 'euroteste', '47.3 %', '35.5 %', '8.5 %', '4.1 %', '11.8 %'], ['september 28 , 1991', 'euroteste', '46.0 %', '37.0 %', '9.7 %', '3.9 %', '9.0 %'], ['september 28 , 1991', 'euroexpansão', '44.0 %', '33.0 %', '9.0 %', '6.0 %', '11.0 %'], ['september 27 , 1991', 'marktest', '43.1 %', '32.8 %', '7.7 %', '4.6 %', '10.3 %'], ['september 27 , 1991', 'pluriteste', '41.2 %', '34.7 %', '8.4 %', '8.1 %', '6.5 %'], ['september 20 , 1991', 'euroteste', '45.6 %', '35.5 %', '10.0 %', '4.4 %', '10.1 %'], ['september 20 , 1991', 'marktest', '41.9 %', '31.9 %', '7.3 %', '4.4 %', '10.0 %'], ['september 16 , 1991', 'pluriteste', '39.2 %', '26.6 %', '6.2 %', '6.0 %', '12.6 %'], ['september 16 , 1991', 'euroteste', '45.1 %', '34.5 %', '10.2 %', '5.2 %', '10.6 %'], ['september 14 , 1991', 'norma', '45.0 %', '37.5 %', '11.2 %', '3.5 %', '7.5 %'], ['august 28 , 1991', 'euroexpansão / marktest', '35.3 %', '36.8 %', '8.7 %', '4.9 %', '1.5 %'], ['august 4 , 1991', 'euroteste / jn', '47.5 %', '37.8 %', '12.3 %', '8.2 %', '7.7 %'], ['july 19 , 1987', '1987 election', '50.2 % 148 seats', '22.2 % 60 seats', '12.1 % 31 seats', '4.4 % 4 seats', '28.0 %']] |
1963 vfl season | https://en.wikipedia.org/wiki/1963_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10783853-8.html.csv | comparative | richmond had a higher scoring game than collingwood . | {'row_1': '1', 'row_2': '2', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'richmond'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away team record fuzzily matches to richmond .', 'tostr': 'filter_eq { all_rows ; away team ; richmond }'}, 'away team score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; away team ; richmond } ; away team score }', 'tointer': 'select the rows whose away team record fuzzily matches to richmond . take the away team score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'collingwood'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose away team record fuzzily matches to collingwood .', 'tostr': 'filter_eq { all_rows ; away team ; collingwood }'}, 'away team score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; away team ; collingwood } ; away team score }', 'tointer': 'select the rows whose away team record fuzzily matches to collingwood . take the away team score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; away team ; richmond } ; away team score } ; hop { filter_eq { all_rows ; away team ; collingwood } ; away team score } } = true', 'tointer': 'select the rows whose away team record fuzzily matches to richmond . take the away team score record of this row . select the rows whose away team record fuzzily matches to collingwood . take the away team score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; away team ; richmond } ; away team score } ; hop { filter_eq { all_rows ; away team ; collingwood } ; away team score } } = true | select the rows whose away team record fuzzily matches to richmond . take the away team score record of this row . select the rows whose away team record fuzzily matches to collingwood . take the away team score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'away team_7': 7, 'richmond_8': 8, 'away team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'away team_11': 11, 'collingwood_12': 12, 'away team score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'away team_7': 'away team', 'richmond_8': 'richmond', 'away team score_9': 'away team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'away team_11': 'away team', 'collingwood_12': 'collingwood', 'away team score_13': 'away team score'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'away team_7': [0], 'richmond_8': [0], 'away team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'away team_11': [1], 'collingwood_12': [1], 'away team score_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '13.11 ( 89 )', 'richmond', '7.5 ( 47 )', 'windy hill', '21200', '8 june 1963'], ['carlton', '6.8 ( 44 )', 'collingwood', '6.10 ( 46 )', 'princes park', '38698', '8 june 1963'], ['st kilda', '8.13 ( 61 )', 'hawthorn', '9.11 ( 65 )', 'junction oval', '34900', '8 june 1963'], ['footscray', '6.16 ( 52 )', 'south melbourne', '5.9 ( 39 )', 'western oval', '22950', '10 june 1963'], ['fitzroy', '2.11 ( 23 )', 'north melbourne', '6.15 ( 51 )', 'brunswick street oval', '13400', '10 june 1963'], ['melbourne', '11.16 ( 82 )', 'geelong', '4.11 ( 35 )', 'mcg', '81550', '10 june 1963']] |
fortune global 500 | https://en.wikipedia.org/wiki/Fortune_Global_500 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17581425-1.html.csv | ordinal | walmart is 2nd on the fortune global 500 list with a revenue of 469.2 billion usd . | {'scope': 'all', 'row': '2', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'revenue in usd', '2'], 'result': '469.2 billion', 'ind': 0, 'tostr': 'nth_max { all_rows ; revenue in usd ; 2 }', 'tointer': 'the 2nd maximum revenue in usd record of all rows is 469.2 billion .'}, '469.2 billion'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; revenue in usd ; 2 } ; 469.2 billion }', 'tointer': 'the 2nd maximum revenue in usd record of all rows is 469.2 billion .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'revenue in usd', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; revenue in usd ; 2 }'}, 'company'], 'result': 'walmart', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; revenue in usd ; 2 } ; company }'}, 'walmart'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; revenue in usd ; 2 } ; company } ; walmart }', 'tointer': 'the company record of the row with 2nd maximum revenue in usd record is walmart .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; revenue in usd ; 2 } ; 469.2 billion } ; eq { hop { nth_argmax { all_rows ; revenue in usd ; 2 } ; company } ; walmart } } = true', 'tointer': 'the 2nd maximum revenue in usd record of all rows is 469.2 billion . the company record of the row with 2nd maximum revenue in usd record is walmart .'} | and { eq { nth_max { all_rows ; revenue in usd ; 2 } ; 469.2 billion } ; eq { hop { nth_argmax { all_rows ; revenue in usd ; 2 } ; company } ; walmart } } = true | the 2nd maximum revenue in usd record of all rows is 469.2 billion . the company record of the row with 2nd maximum revenue in usd record is walmart . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'revenue in usd_8': 8, '2_9': 9, '469.2 billion_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'revenue in usd_12': 12, '2_13': 13, 'company_14': 14, 'walmart_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'revenue in usd_8': 'revenue in usd', '2_9': '2', '469.2 billion_10': '469.2 billion', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'revenue in usd_12': 'revenue in usd', '2_13': '2', 'company_14': 'company', 'walmart_15': 'walmart'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'revenue in usd_8': [0], '2_9': [0], '469.2 billion_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'revenue in usd_12': [2], '2_13': [2], 'company_14': [3], 'walmart_15': [4]} | ['rank', 'company', 'country', 'industry', 'revenue in usd'] | [['1', 'royal dutch shell', 'netherlands', 'petroleum', '481.7 billion'], ['2', 'walmart', 'united states', 'retail', '469.2 billion'], ['3', 'exxonmobil', 'united states', 'petroleum', '449.9 billion'], ['4', 'sinopec', 'china', 'petroleum', '428.2 billion'], ['5', 'china national petroleum corporation', 'china', 'petroleum', '408.6 billion'], ['6', 'bp', 'united kingdom', 'petroleum', '388.3 billion'], ['7', 'state grid corporation of china', 'china', 'power', '298.4 billion'], ['8', 'toyota', 'japan', 'automobiles', '265.7 billion'], ['9', 'volkswagen', 'germany', 'automobiles', '247.6 billion'], ['10', 'total', 'france', 'petroleum', '234.3 billion']] |
sandra roma | https://en.wikipedia.org/wiki/Sandra_Roma | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14495322-6.html.csv | count | among the itf finals that sandra roma won , 4 of them were on clay surface . | {'scope': 'subset', 'criterion': 'equal', 'value': 'clay', 'result': '4', 'col': '4', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'winner'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; outcome ; winner }', 'tointer': 'select the rows whose outcome record fuzzily matches to winner .'}, 'surface', 'clay'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose outcome record fuzzily matches to winner . among these rows , select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { filter_eq { all_rows ; outcome ; winner } ; surface ; clay }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; outcome ; winner } ; surface ; clay } }', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . among these rows , select the rows whose surface record fuzzily matches to clay . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; outcome ; winner } ; surface ; clay } } ; 4 } = true', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . among these rows , select the rows whose surface record fuzzily matches to clay . the number of such rows is 4 .'} | eq { count { filter_eq { filter_eq { all_rows ; outcome ; winner } ; surface ; clay } } ; 4 } = true | select the rows whose outcome record fuzzily matches to winner . among these rows , select the rows whose surface record fuzzily matches to clay . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'outcome_6': 6, 'winner_7': 7, 'surface_8': 8, 'clay_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'outcome_6': 'outcome', 'winner_7': 'winner', 'surface_8': 'surface', 'clay_9': 'clay', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'outcome_6': [0], 'winner_7': [0], 'surface_8': [1], 'clay_9': [1], '4_10': [3]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', '19 may 2009', 'antalya , turkey', 'clay', 'julia klackenberg', 'amanda carreras valentina sulpizio', '0 - 6 , 3 - 6'], ['runner - up', '22 june 2009', 'kristinehamn , sweden', 'clay', 'sofia arvidsson', 'hanne skak jensen johanna larsson', '6 - 7 ( 5 - 7 ) , 2 - 6'], ['winner', '29 june 2009', 'ystad , sweden', 'clay', 'sofia arvidsson', 'melanie klaffner hanna nooni', '6 - 4 , 6 - 4'], ['winner', '27 july 2009', 'tampere , finland', 'clay', 'emma laine', 'alizé lim vivienne vierin', '6 - 4 , 6 - 3'], ['winner', '7 may 2012', 'båstad , sweden', 'clay', 'eveliina virtanen', 'hilda melander paulina milosavljevic', '6 - 2 , 3 - 6 ,'], ['winner', '14 may 2012', 'båstad , sweden', 'clay', 'eveliina virtanen', 'lucy brown milana špremo', '6 - 3 , 6 - 7 ( 4 - 7 ) ,'], ['winner', '18 march 2013', 'sunderland , united kingdom', 'hard ( i )', 'hilda melander', 'amy bowtell lucy brown', '6 - 0 , 6 - 3']] |
1971 isle of man tt | https://en.wikipedia.org/wiki/1971_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10638654-3.html.csv | count | 9 riders in the 1971 isle of man tt were from the united kingdom . | {'scope': 'all', 'criterion': 'equal', 'value': 'united kingdom', 'result': '9', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united kingdom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united kingdom .', 'tostr': 'filter_eq { all_rows ; country ; united kingdom }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united kingdom } }', 'tointer': 'select the rows whose country record fuzzily matches to united kingdom . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united kingdom } } ; 9 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united kingdom . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; country ; united kingdom } } ; 9 } = true | select the rows whose country record fuzzily matches to united kingdom . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united kingdom_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united kingdom_6': 'united kingdom', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united kingdom_6': [0], '9_7': [2]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'tony jefferies', 'united kingdom', 'yamsel', '89.81 mph', '2:05.48.6', '15'], ['2', 'gordon pantall', 'united kingdom', 'yamaha', '89.55 mph', '2:06.25.0', '12'], ['3', 'bill smith', 'united kingdom', 'honda', '89.81 mph', '2:07.40.8', '10'], ['4', 'john williams', 'united kingdom', 'ajs', '88.94 mph', '2:07.17.0', '8'], ['5', 'mick chatterton', 'united kingdom', 'yamaha', '87.38 mph', '2:09.33.6', '6'], ['6', 'gerry mateer', 'united kingdom', 'aermacchi', '87.18 mph', '2:09.51.8', '5'], ['7', 'mick grant', 'united kingdom', 'yamaha', '86.50 mph', '2:28.30.6', '4'], ['8', 'billy guthrie', 'united kingdom', 'yamaha', '86.31 mph', '2:11.09.0', '3'], ['9', 'gã ¼ nter bartusch', 'east germany', 'mz', '86.15 mph', '2:11.24.2', '2'], ['10', 'peter berwick', 'united kingdom', 'suzuki', '85.90 mph', '2:11.47.2', '1']] |
1984 grand prix ( tennis ) | https://en.wikipedia.org/wiki/1984_Grand_Prix_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29295463-9.html.csv | majority | most of the matches for tennis 's 1984 grand prix took place in ohio . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ohio', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'tournament', 'ohio'], 'result': True, 'ind': 0, 'tointer': 'for the tournament records of all rows , most of them fuzzily match to ohio .', 'tostr': 'most_eq { all_rows ; tournament ; ohio } = true'} | most_eq { all_rows ; tournament ; ohio } = true | for the tournament records of all rows , most of them fuzzily match to ohio . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tournament_3': 3, 'ohio_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tournament_3': 'tournament', 'ohio_4': 'ohio'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tournament_3': [0], 'ohio_4': [0]} | ['week of', 'tournament', 'champion', 'runner - up', 'semifinalists', 'quarterfinalists'] | [['6 august', 'cleveland , ohio , usa hard', 'terry moor 3 - 6 , 7 - 6 , 6 - 2', 'marty davis', 'matt mitchell jeff klaparda', 'david dowlen david pate greg holmes mike de palmer'], ['6 august', 'cleveland , ohio , usa hard', 'francisco gonzález matt mitchell 7 - 6 , 7 - 5', 'scott davis chris dunk', 'matt mitchell jeff klaparda', 'david dowlen david pate greg holmes mike de palmer'], ['20 august', 'cincinnati open cincinnati , ohio , usa hard', 'mats wilander 7 - 6 , 6 - 3', 'anders järryd', 'joakim nyström jimmy connors', 'paul mcnamee dan cassidy john sadri stefan edberg'], ['20 august', 'cincinnati open cincinnati , ohio , usa hard', 'francisco gonzález matt mitchell 4 - 6 , 6 - 3 , 7 - 6', 'gene mayer balázs taróczy', 'joakim nyström jimmy connors', 'paul mcnamee dan cassidy john sadri stefan edberg'], ['28 august', 'us open flushing meadow , new york , usa hard', 'john mcenroe 6 - 3 , 6 - 4 , 6 - 1', 'ivan lendl', 'jimmy connors pat cash', 'gene mayer john lloyd mats wilander andrés gómez'], ['28 august', 'us open flushing meadow , new york , usa hard', 'john fitzgerald tomáš šmíd 7 - 6 , 6 - 3 , 6 - 3', 'stefan edberg anders järryd', 'jimmy connors pat cash', 'gene mayer john lloyd mats wilander andrés gómez']] |
soo line locomotives | https://en.wikipedia.org/wiki/Soo_Line_locomotives | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17248696-3.html.csv | aggregation | from 1882 to 1887 , schenectady manufactured a total of 27 locomotives for soo line locomotives . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '27', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'schenectady'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'schenectady'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; manufacturer ; schenectady }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to schenectady .'}, 'quantity made'], 'result': '27', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; manufacturer ; schenectady } ; quantity made }'}, '27'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; manufacturer ; schenectady } ; quantity made } ; 27 } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to schenectady . the sum of the quantity made record of these rows is 27 .'} | round_eq { sum { filter_eq { all_rows ; manufacturer ; schenectady } ; quantity made } ; 27 } = true | select the rows whose manufacturer record fuzzily matches to schenectady . the sum of the quantity made record of these rows is 27 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'manufacturer_5': 5, 'schenectady_6': 6, 'quantity made_7': 7, '27_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'manufacturer_5': 'manufacturer', 'schenectady_6': 'schenectady', 'quantity made_7': 'quantity made', '27_8': '27'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manufacturer_5': [0], 'schenectady_6': [0], 'quantity made_7': [1], '27_8': [2]} | ['class', 'wheel arrangement', 'manufacturer', 'year made', 'quantity made', 'quantity preserved'] | [['4 - 4 - 0 - oooo - american', '4 - 4 - 0 - oooo - american', '4 - 4 - 0 - oooo - american', '4 - 4 - 0 - oooo - american', '4 - 4 - 0 - oooo - american', '4 - 4 - 0 - oooo - american'], ['c', '4 - 4 - 0', 'baldwin', '1886 - 1887', '6', '0'], ['c - 1', '4 - 4 - 0', 'new jersey', '1857', '1', '0'], ['c - 1', '4 - 4 - 0', 'new jersey', '1862', '1', '0'], ['v', '4 - 4 - 0', 'new jersey', '1855', '1', '0'], ['c - 3', '4 - 4 - 0', 'rhode island', '1884', '2', '0'], ['c - 4 / c - 5', '4 - 4 - 0', 'baldwin', '1886 - 1887', '44', '0'], ['c - 5 - s', '4 - 4 - 0', 'mstp & sstem ( rebuilder )', '1928 - 1931 ( rebuilt )', '9', '0'], ['c - 20', '4 - 4 - 0', 'schenectady', '1882', '2', '0'], ['c - 21', '4 - 4 - 0', 'schenectady', '1885', '12', '0'], ['c - 22', '4 - 4 - 0', 'schenectady', '1886', '11', '0'], ['c - 23', '4 - 4 - 0', 'baldwin', '1886 - 1887', '12', '0'], ['c - 24', '4 - 4 - 0', 'brooks', '1902 ( rebuilt )', '1', '0'], ['c - 25', '4 - 4 - 0', 'schenectady', '1887', '2', '0']] |
1979 world figure skating championships | https://en.wikipedia.org/wiki/1979_World_Figure_Skating_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11312764-5.html.csv | ordinal | at the 1979 world figure skating championships , the 2nd highest score went to marina cherkasova / sergei shakhrai . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 2 }'}, 'name'], 'result': 'marina cherkasova / sergei shakhrai', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 2 } ; name }'}, 'marina cherkasova / sergei shakhrai'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points ; 2 } ; name } ; marina cherkasova / sergei shakhrai } = true', 'tointer': 'select the row whose points record of all rows is 2nd maximum . the name record of this row is marina cherkasova / sergei shakhrai .'} | eq { hop { nth_argmax { all_rows ; points ; 2 } ; name } ; marina cherkasova / sergei shakhrai } = true | select the row whose points record of all rows is 2nd maximum . the name record of this row is marina cherkasova / sergei shakhrai . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '2_6': 6, 'name_7': 7, 'marina cherkasova / sergei shakhrai_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', '2_6': '2', 'name_7': 'name', 'marina cherkasova / sergei shakhrai_8': 'marina cherkasova / sergei shakhrai'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '2_6': [0], 'name_7': [1], 'marina cherkasova / sergei shakhrai_8': [2]} | ['rank', 'name', 'nation', 'points', 'places'] | [['1', 'tai babilonia / randy gardner', 'united states', '144.54', '12'], ['2', 'marina cherkasova / sergei shakhrai', 'soviet union', '142.22', '16'], ['3', 'sabine baeãÿ / tassilo thierbach', 'east germany', '137.74', '32'], ['4', 'irina vorobieva / igor lisovski', 'soviet union', '138.72', '33'], ['5', 'marina pestova / stanislav leonovich', 'soviet union', '133.98', '46'], ['6', 'vicki heasley / robert wagenhoffer', 'united states', '132.50', '54'], ['7', 'cornelia haufe / kersten bellmann', 'east germany', '128.98', '70'], ['8', 'christina riegel / andreas nischwitz', 'west germany', '128.56', '75'], ['9', 'sheryl franks / michael botticelli', 'united states', '127.64', '77'], ['10', 'kerstin stolfig / veit kempe', 'east germany', '125.92', '84'], ['11', 'barbara underhill / paul martini', 'canada', '123.92', '94'], ['12', 'gabriele beck / jochen stahl', 'west germany', '117.62', '114'], ['13', 'elizabeth cain / peter cain', 'australia', '115.32', '117'], ['14', 'kyoko hagiwara / hisao ozaki', 'japan', '114.02', '120']] |
cycling at the 2008 summer olympics - men 's bmx | https://en.wikipedia.org/wiki/Cycling_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_BMX | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18603914-7.html.csv | superlative | artūrs matisons took the most time to complete the second run . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', '2nd run'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 2nd run }'}, 'name'], 'result': 'artūrs matisons ( lat )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; 2nd run } ; name }'}, 'artūrs matisons ( lat )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; 2nd run } ; name } ; artūrs matisons ( lat ) } = true', 'tointer': 'select the row whose 2nd run record of all rows is maximum . the name record of this row is artūrs matisons ( lat ) .'} | eq { hop { argmax { all_rows ; 2nd run } ; name } ; artūrs matisons ( lat ) } = true | select the row whose 2nd run record of all rows is maximum . the name record of this row is artūrs matisons ( lat ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, '2nd run_5': 5, 'name_6': 6, 'artūrs matisons ( lat )_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', '2nd run_5': '2nd run', 'name_6': 'name', 'artūrs matisons ( lat )_7': 'artūrs matisons ( lat )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], '2nd run_5': [0], 'name_6': [1], 'artūrs matisons ( lat )_7': [2]} | ['rank', 'name', '1st run', '2nd run', '3rd run', 'total'] | [['1', 'mike day ( usa )', '36.470 ( 1 )', '36.219 ( 1 )', '37.461 ( 3 )', '5'], ['2', 'sifiso nhlapo ( rsa )', '37.197 ( 3 )', '36.597 ( 3 )', '36.457 ( 2 )', '8'], ['3', 'donny robinson ( usa )', '36.832 ( 2 )', '36.462 ( 2 )', '56.249 ( 6 )', '10'], ['4', 'andrés jiménez caicedo ( col )', '37.363 ( 4 )', '36.862 ( 4 )', '44.507 ( 5 )', '13'], ['5', 'raymon van der biezen ( ned )', '55.121 ( 7 )', '37.258 ( 6 )', '36.200 ( 1 )', '14'], ['6', 'kyle bennett ( usa )', '43.518 ( 5 )', '37.200 ( 5 )', '43.897 ( 4 )', '14'], ['7', 'artūrs matisons ( lat )', '53.379 ( 6 )', '1:17.170 ( 8 )', 'dnf ( 8 )', '22'], ['8', 'marc willers ( nzl )', '1:22.619 ( 8 )', '43.256 ( 7 )', 'dnf ( 8 )', '23']] |
2008 european judo championships | https://en.wikipedia.org/wiki/2008_European_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16880519-3.html.csv | count | in the 2008 european judo championships , for teams that won at least 1 gold medal , there were 3 nations that won 2 silver medals . | {'scope': 'subset', 'criterion': 'equal', 'value': '2', 'result': '3', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than_eq', 'value': '1'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'gold', '1'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; gold ; 1 }', 'tointer': 'select the rows whose gold record is greater than or equal to 1 .'}, 'silver', '2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose gold record is greater than or equal to 1 . among these rows , select the rows whose silver record is equal to 2 .', 'tostr': 'filter_eq { filter_greater_eq { all_rows ; gold ; 1 } ; silver ; 2 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater_eq { all_rows ; gold ; 1 } ; silver ; 2 } }', 'tointer': 'select the rows whose gold record is greater than or equal to 1 . among these rows , select the rows whose silver record is equal to 2 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater_eq { all_rows ; gold ; 1 } ; silver ; 2 } } ; 3 } = true', 'tointer': 'select the rows whose gold record is greater than or equal to 1 . among these rows , select the rows whose silver record is equal to 2 . the number of such rows is 3 .'} | eq { count { filter_eq { filter_greater_eq { all_rows ; gold ; 1 } ; silver ; 2 } } ; 3 } = true | select the rows whose gold record is greater than or equal to 1 . among these rows , select the rows whose silver record is equal to 2 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'gold_6': 6, '1_7': 7, 'silver_8': 8, '2_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'gold_6': 'gold', '1_7': '1', 'silver_8': 'silver', '2_9': '2', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'gold_6': [0], '1_7': [0], 'silver_8': [1], '2_9': [1], '3_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'netherlands', '2', '2', '0', '4'], ['2', 'france', '2', '1', '3', '6'], ['3', 'austria', '2', '0', '0', '2'], ['4', 'spain', '1', '3', '1', '5'], ['5', 'germany', '1', '2', '3', '6'], ['6', 'russia', '1', '2', '1', '4'], ['7', 'italy', '1', '1', '1', '3'], ['8 =', 'georgia', '1', '0', '3', '4'], ['8 =', 'portugal', '1', '0', '3', '4'], ['10', 'romania', '1', '0', '1', '2'], ['11', 'belgium', '1', '0', '0', '1'], ['12', 'hungary', '0', '1', '2', '3'], ['13', 'azerbaijan', '0', '1', '1', '2'], ['14', 'poland', '0', '1', '0', '1'], ['15', 'slovenia', '0', '0', '3', '3'], ['16 =', 'belarus', '0', '0', '2', '2'], ['16 =', 'israel', '0', '0', '2', '2'], ['18 =', 'greece', '0', '0', '1', '1'], ['18 =', 'ukraine', '0', '0', '1', '1']] |
nero wolfe ( 1981 tv series ) | https://en.wikipedia.org/wiki/Nero_Wolfe_%281981_TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17189526-1.html.csv | count | edward m abroms directed a total of 3 episodes of nero wolfe . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'edward m abroms', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'edward m abroms'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to edward m abroms .', 'tostr': 'filter_eq { all_rows ; director ; edward m abroms }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; director ; edward m abroms } }', 'tointer': 'select the rows whose director record fuzzily matches to edward m abroms . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; director ; edward m abroms } } ; 3 } = true', 'tointer': 'select the rows whose director record fuzzily matches to edward m abroms . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; director ; edward m abroms } } ; 3 } = true | select the rows whose director record fuzzily matches to edward m abroms . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'director_5': 5, 'edward m abroms_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'director_5': 'director', 'edward m abroms_6': 'edward m abroms', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'director_5': [0], 'edward m abroms_6': [0], '3_7': [2]} | ['title', 'season', 'director', 'teleplay', 'first broadcast'] | [['the golden spiders', '1.1', "michael o'herlihy", 'wallace ware + peter nasco', 'january 16 , 1981'], ['death on the doorstep', '1.2', 'george mccowan', 'stephen downing', 'january 23 , 1981'], ['before i die', '1.3', 'edward m abroms', 'alfred hayes', 'january 30 , 1981'], ['wolfe at the door', '1.4', 'herbert hirschman', 'lee sheldon', 'february 6 , 1981'], ['might as well be dead', '1.5', 'george mccowan', 'seeleg lester', 'february 13 , 1981'], ['to catch a dead man', '1.6', 'edward m abroms', 'john meredyth lucas', 'february 20 , 1981'], ['in the best families', '1.7', 'george mccowan', 'alfred hayes', 'march 6 , 1981'], ['murder by the book', '1.8', 'bob kelljan', 'wallace ware', 'march 13 , 1981'], ['what happened to april', '1.9', 'edward m abroms', 'stephen downing', 'march 20 , 1981'], ['gambit', '1.10', 'george mccowan', 'stephen kandel', 'april 3 , 1981'], ['death and the dolls', '1.11', 'gerald mayer', 'gerald sanford', 'april 10 , 1981'], ['the murder in question', '1.12', 'george mccowan', 'merwin gerard', 'april 17 , 1981'], ['the blue ribbon hostage', '1.13', 'ron satlof', 'dick nelson', 'may 5 , 1981'], ['sweet revenge', '1.14', 'george mccowan', 'ben roberts', 'june 2 , 1981']] |
metro conference | https://en.wikipedia.org/wiki/Metro_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2293402-2.html.csv | unique | the university of louisville is the only institution founded in the 1700s . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'less_than', 'value': '1800', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'founded', '1800'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose founded record is less than 1800 .', 'tostr': 'filter_less { all_rows ; founded ; 1800 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; founded ; 1800 } }', 'tointer': 'select the rows whose founded record is less than 1800 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'founded', '1800'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose founded record is less than 1800 .', 'tostr': 'filter_less { all_rows ; founded ; 1800 }'}, 'institution'], 'result': 'university of louisville', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; founded ; 1800 } ; institution }'}, 'university of louisville'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; founded ; 1800 } ; institution } ; university of louisville }', 'tointer': 'the institution record of this unqiue row is university of louisville .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; founded ; 1800 } } ; eq { hop { filter_less { all_rows ; founded ; 1800 } ; institution } ; university of louisville } } = true', 'tointer': 'select the rows whose founded record is less than 1800 . there is only one such row in the table . the institution record of this unqiue row is university of louisville .'} | and { only { filter_less { all_rows ; founded ; 1800 } } ; eq { hop { filter_less { all_rows ; founded ; 1800 } ; institution } ; university of louisville } } = true | select the rows whose founded record is less than 1800 . there is only one such row in the table . the institution record of this unqiue row is university of louisville . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'founded_7': 7, '1800_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'institution_9': 9, 'university of louisville_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'founded_7': 'founded', '1800_8': '1800', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'institution_9': 'institution', 'university of louisville_10': 'university of louisville'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'founded_7': [0], '1800_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'institution_9': [2], 'university of louisville_10': [3]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'joined', 'left'] | [['university of cincinnati', 'bearcats', 'cincinnati , ohio', '1819', 'public', '41357', '1975', '1991'], ['georgia institute of technology', 'yellow jackets', 'atlanta , georgia', '1885', 'public', '21557', '1975', '1978'], ['university of louisville', 'cardinals', 'louisville , kentucky', '1798', 'public', '22249', '1975', '1995'], ['university of memphis , 1', 'tigers', 'memphis , tennessee', '1912', 'public', '22365', '1975', '1991'], ['saint louis university', 'billikens', 'saint louis , missouri', '1818', 'private', '13785', '1975', '1982']] |
1968 - 69 philadelphia flyers season | https://en.wikipedia.org/wiki/1968%E2%80%9369_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14191335-4.html.csv | majority | all games of the 1968 - 69 philadelphia flyers ' season were scheduled for the month of december . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'december', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to december .', 'tostr': 'all_eq { all_rows ; date ; december } = true'} | all_eq { all_rows ; date ; december } = true | for the date records of all rows , all of them fuzzily match to december . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'december_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'december_4': 'december'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'december_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 1', 'philadelphia', '3 - 3', 'detroit', 'parent', '13039', '6 - 13 - 3'], ['december 4', 'philadelphia', '1 - 3', 'los angeles', 'parent', '5847', '6 - 14 - 3'], ['december 6', 'philadelphia', '0 - 4', 'oakland', 'favell', '3166', '6 - 15 - 3'], ['december 8', 'st louis', '4 - 4', 'philadelphia', 'parent', '10329', '6 - 15 - 4'], ['december 12', 'toronto', '1 - 0', 'philadelphia', 'parent', '8531', '6 - 16 - 4'], ['december 14', 'philadelphia', '0 - 1', 'montreal', 'parent', '16584', '6 - 17 - 4'], ['december 15', 'philadelphia', '3 - 1', 'new york', 'parent', '12731', '7 - 17 - 4'], ['december 17', 'pittsburgh', '2 - 8', 'philadelphia', 'parent', '6986', '8 - 17 - 4'], ['december 19', 'minnesota', '5 - 5', 'philadelphia', 'parent', '8394', '8 - 17 - 5'], ['december 21', 'philadelphia', '2 - 1', 'los angeles', 'favell', '7108', '9 - 17 - 5'], ['december 22', 'philadelphia', '1 - 2', 'oakland', 'favell', '1829', '9 - 18 - 5'], ['december 25', 'new york', '2 - 2', 'philadelphia', 'favell', '9545', '9 - 18 - 6'], ['december 27', 'philadelphia', '3 - 3', 'detroit', 'parent', '11935', '9 - 18 - 7'], ['december 29', 'oakland', '2 - 1', 'philadelphia', 'parent', '12767', '9 - 19 - 7']] |
viktor leonenko | https://en.wikipedia.org/wiki/Viktor_Leonenko | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11327303-2.html.csv | ordinal | the game played on 18 may 1993 was the first game that viktor leonenko scored an international goal in . | {'row': '1', 'col': '1', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '1'], 'result': '18 may 1993', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 1 }', 'tointer': 'the 1st minimum date record of all rows is 18 may 1993 .'}, '18 may 1993'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; date ; 1 } ; 18 may 1993 } = true', 'tointer': 'the 1st minimum date record of all rows is 18 may 1993 .'} | eq { nth_min { all_rows ; date ; 1 } ; 18 may 1993 } = true | the 1st minimum date record of all rows is 18 may 1993 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'date_4': 4, '1_5': 5, '18 may 1993_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'date_4': 'date', '1_5': '1', '18 may 1993_6': '18 may 1993'} | {'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'date_4': [0], '1_5': [0], '18 may 1993_6': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['18 may 1993', 'vilnius , lithuania', '1 - 1', '1 - 2', 'friendly'], ['16 october 1993', 'high point , united states', '1 - 1', '1 - 2', 'friendly'], ['16 october 1993', 'high point , united states', '1 - 2', '1 - 2', 'friendly'], ['25 may 1994', 'kyiv , ukraine', '1 - 1', '3 - 1', 'friendly'], ['13 august 1996', 'kyiv , ukraine', '1 - 1', '5 - 2', 'friendly'], ['13 august 1996', 'kyiv , ukraine', '3 - 1', '5 - 2', 'friendly']] |
1992 in spaceflight | https://en.wikipedia.org/wiki/1992_in_spaceflight | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17621896-3.html.csv | superlative | the most time spent in space in 1992 was on may 13th . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'duration'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; duration }'}, 'start date / time'], 'result': '13 may 21:17', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; duration } ; start date / time }'}, '13 may 21:17'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; duration } ; start date / time } ; 13 may 21:17 } = true', 'tointer': 'select the row whose duration record of all rows is maximum . the start date / time record of this row is 13 may 21:17 .'} | eq { hop { argmax { all_rows ; duration } ; start date / time } ; 13 may 21:17 } = true | select the row whose duration record of all rows is maximum . the start date / time record of this row is 13 may 21:17 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'duration_5': 5, 'start date / time_6': 6, '13 may 21:17_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'duration_5': 'duration', 'start date / time_6': 'start date / time', '13 may 21:17_7': '13 may 21:17'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'duration_5': [0], 'start date / time_6': [1], '13 may 21:17_7': [2]} | ['start date / time', 'duration', 'end time', 'spacecraft', 'crew'] | [['20 february 20:09', '4 hours 12 minutes', '21 february 00:21', 'mir eo - 10 kvant - 2', 'aleksandr volkov sergei krikalyov'], ['10 may 20:40', '3 hours 43 minutes', '11 may 00:23', 'sts - 49 endeavour', 'pierre j thuot richard hieb'], ['11 may 21:05', '5 hours 30 minutes', '12 may 02:35', 'sts - 49 endeavour', 'pierre j thuot richard hieb'], ['13 may 21:17', '8 hours 29 minutes', '14 may 05:46', 'sts - 49 endeavour', 'pierre j thuot richard hieb thomas akers'], ['14 may ~ 21:00', '7 hours 44 minutes', '15 may ~ 04:45', 'sts - 49 endeavour', 'thomas akers kathryn c thornton'], ['8 july 12:38', '2 hours 3 minutes', '14:41', 'mir eo - 11 kvant - 2', 'aleksandr viktorenko aleksandr kaleri'], ['3 september 13:32', '3 hours 56 minutes', '17:28', 'mir eo - 12 kvant - 2', 'sergei avdeyev anatoly solovyev'], ['7 september 11:47', '5 hours 8 minutes', '16:55', 'mir eo - 12 kvant - 2', 'sergei avdeyev anatoly solovyev'], ['11 september 10:06', '5 hours 44 minutes', '15:50', 'mir eo - 12 kvant - 2', 'sergei avdeyev anatoly solovyev'], ['15 september 07:49', '3 hours 33 minutes', '11:22', 'mir eo - 12 kvant - 2', 'sergei avdeyev anatoly solovyev']] |
1901 michigan wolverines football team | https://en.wikipedia.org/wiki/1901_Michigan_Wolverines_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14342210-14.html.csv | superlative | bruce shorts had the most extra points 1 point in the 1901 michigan wolverines football team . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'extra points 1 point'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; extra points 1 point }'}, 'player'], 'result': 'bruce shorts', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; extra points 1 point } ; player }'}, 'bruce shorts'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; extra points 1 point } ; player } ; bruce shorts } = true', 'tointer': 'select the row whose extra points 1 point record of all rows is maximum . the player record of this row is bruce shorts .'} | eq { hop { argmax { all_rows ; extra points 1 point } ; player } ; bruce shorts } = true | select the row whose extra points 1 point record of all rows is maximum . the player record of this row is bruce shorts . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'extra points 1 point_5': 5, 'player_6': 6, 'bruce shorts_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'extra points 1 point_5': 'extra points 1 point', 'player_6': 'player', 'bruce shorts_7': 'bruce shorts'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'extra points 1 point_5': [0], 'player_6': [1], 'bruce shorts_7': [2]} | ['player', 'touchdowns ( 5 points )', 'extra points 1 point', 'field goals ( 5 points )', 'total points'] | [['bruce shorts', '13', '53', '1', '123'], ['willie heston', '20', '0', '0', '100'], ['neil snow', '19', '0', '0', '95'], ['albert herrnstein', '12', '0', '0', '60'], ['everett sweeley', '7', '2', '1', '42'], ['hugh white', '6', '0', '0', '30'], ['walter shaw', '4', '7', '0', '27'], ['arthur redner', '5', '0', '0', '25'], ['curtis redden', '4', '0', '0', '20'], ['herb graver', '1', '3', '0', '8']] |
1989 - 90 segunda división | https://en.wikipedia.org/wiki/1989%E2%80%9390_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12107080-2.html.csv | aggregation | in the ' 89 - '90 segunda football division , teams scored an average total of 38.5 goals . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '38.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'goals for'], 'result': '38.5', 'ind': 0, 'tostr': 'avg { all_rows ; goals for }'}, '38.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; goals for } ; 38.5 } = true', 'tointer': 'the average of the goals for record of all rows is 38.5 .'} | round_eq { avg { all_rows ; goals for } ; 38.5 } = true | the average of the goals for record of all rows is 38.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'goals for_4': 4, '38.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'goals for_4': 'goals for', '38.5_5': '38.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'goals for_4': [0], '38.5_5': [1]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'real burgos', '38', '50 + 12', '18', '14', '6', '53', '24', '+ 29'], ['2', 'real betis', '38', '47 + 9', '16', '15', '7', '44', '29', '+ 15'], ['3', 'bilbao athletic 1', '38', '45 + 7', '15', '15', '8', '50', '36', '+ 14'], ['4', 'deportivo de la coruña', '38', '44 + 6', '19', '6', '13', '45', '38', '+ 7'], ['5', 'rcd español', '38', '42 + 4', '15', '12', '11', '50', '33', '+ 17'], ['6', 'ud las palmas', '38', '40 + 2', '15', '10', '13', '42', '37', '+ 5'], ['7', 'ce sabadell fc', '38', '40 + 2', '13', '14', '11', '40', '39', '+ 1'], ['8', 'palamós cf', '38', '40 + 2', '13', '14', '11', '29', '39', '- 10'], ['9', 'real murcia', '38', '38', '13', '12', '13', '38', '39', '- 1'], ['10', 'xerez cd', '38', '38', '11', '16', '11', '26', '31', '- 5'], ['11', 'sestao', '38', '36 - 2', '13', '10', '15', '33', '32', '+ 1'], ['12', 'ue figueres', '38', '36 - 2', '12', '12', '14', '37', '46', '- 9'], ['13', 'ud salamanca', '38', '36 - 2', '14', '8', '16', '35', '33', '+ 2'], ['14', 'elche cf', '38', '36 - 2', '12', '12', '14', '39', '41', '- 2'], ['15', 'levante ud', '38', '36 - 2', '9', '18', '11', '34', '43', '- 9'], ['16', 'sd eibar', '38', '34 - 4', '11', '12', '15', '35', '42', '- 7'], ['17', 'racing de santander', '38', '33 - 5', '11', '11', '16', '32', '36', '- 4'], ['18', 'castilla cf', '38', '31 - 7', '11', '9', '18', '36', '44', '- 8'], ['19', 'recreativo de huelva', '38', '29 - 9', '12', '5', '21', '39', '56', '- 17'], ['20', 'atlético madrileño', '38', '29 - 9', '8', '13', '17', '33', '52', '- 19']] |
1998 icc knockout trophy | https://en.wikipedia.org/wiki/1998_ICC_KnockOut_Trophy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11950720-8.html.csv | majority | in the 1998 icc knockout , most of the players born after 1970 batted right hand . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'right hand bat', 'subset': {'col': '3', 'criterion': 'greater_than_eq', 'value': '1 january 1971'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'date of birth', '1 january 1971'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; date of birth ; 1 january 1971 }', 'tointer': 'select the rows whose date of birth record is greater than or equal to 1 january 1971 .'}, 'batting style', 'right hand bat'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date of birth record is greater than or equal to 1 january 1971 . for the batting style records of these rows , most of them fuzzily match to right hand bat .', 'tostr': 'most_eq { filter_greater_eq { all_rows ; date of birth ; 1 january 1971 } ; batting style ; right hand bat } = true'} | most_eq { filter_greater_eq { all_rows ; date of birth ; 1 january 1971 } ; batting style ; right hand bat } = true | select the rows whose date of birth record is greater than or equal to 1 january 1971 . for the batting style records of these rows , most of them fuzzily match to right hand bat . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_greater_eq_0': 0, 'all_rows_3': 3, 'date of birth_4': 4, '1 january 1971_5': 5, 'batting style_6': 6, 'right hand bat_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_3': 'all_rows', 'date of birth_4': 'date of birth', '1 january 1971_5': '1 january 1971', 'batting style_6': 'batting style', 'right hand bat_7': 'right hand bat'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_greater_eq_0': [1], 'all_rows_3': [0], 'date of birth_4': [0], '1 january 1971_5': [0], 'batting style_6': [1], 'right hand bat_7': [1]} | ['no', 'player', 'date of birth', 'batting style', 'bowling style', 'first class team'] | [['59', 'brian lara ( captain )', '2 may 1969', 'left hand bat', 'right arm leg break googly', 'trinidad and tobago'], ['55', 'keith arthurton', '21 february 1965', 'left hand bat', 'left arm orthodox spin', 'leeward islands'], ['66', 'shivnarine chanderpaul', '16 august 1974', 'left hand bat', 'right arm leg break', 'guyana'], ['86', 'mervyn dillon', '5 june 1974', 'right hand bat', 'right arm fast - medium', 'trinidad and tobago'], ['50', 'carl hooper', '15 december 1966', 'right hand bat', 'right arm off break', 'guyana'], ['76', 'ridley jacobs ( wicket - keeper )', '26 november 1967', 'left hand bat', 'wicket - keeper', 'leeward islands'], ['89', 'reon king', '6 october 1975', 'right hand bat', 'right arm fast - medium', 'guyana'], ['58', 'clayton lambert', '10 february 1962', 'left hand bat', 'right arm off break', 'guyana'], ['85', 'rawl lewis', '5 september 1974', 'right hand bat', 'right arm leg break googly', 'windward islands'], ['78', 'nixon mclean', '20 july 1973', 'left hand bat', 'right arm fast', 'windward islands'], ['87', 'neil mcgarrell', '12 july 1972', 'right hand bat', 'left arm orthodox spin', 'guyana'], ['51', 'phil simmons', '18 april 1963', 'right hand bat', 'right arm medium', 'trinidad and tobago'], ['61', 'philo wallace', '2 august 1970', 'right hand bat', 'right arm medium', 'barbados'], ['68', 'stuart williams', '12 august 1969', 'right hand bat', 'right arm medium', 'leeward islands']] |
1974 icf canoe sprint world championships | https://en.wikipedia.org/wiki/1974_ICF_Canoe_Sprint_World_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18607938-4.html.csv | comparative | in the 1974 icf canoe sprint world championships romania received more bronze medals than the soviet union . | {'row_1': '2', 'row_2': '1', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'romania'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to romania .', 'tostr': 'filter_eq { all_rows ; nation ; romania }'}, 'bronze'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; romania } ; bronze }', 'tointer': 'select the rows whose nation record fuzzily matches to romania . take the bronze record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'soviet union'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to soviet union .', 'tostr': 'filter_eq { all_rows ; nation ; soviet union }'}, 'bronze'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; soviet union } ; bronze }', 'tointer': 'select the rows whose nation record fuzzily matches to soviet union . take the bronze record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; nation ; romania } ; bronze } ; hop { filter_eq { all_rows ; nation ; soviet union } ; bronze } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to romania . take the bronze record of this row . select the rows whose nation record fuzzily matches to soviet union . take the bronze record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; nation ; romania } ; bronze } ; hop { filter_eq { all_rows ; nation ; soviet union } ; bronze } } = true | select the rows whose nation record fuzzily matches to romania . take the bronze record of this row . select the rows whose nation record fuzzily matches to soviet union . take the bronze record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nation_7': 7, 'romania_8': 8, 'bronze_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'soviet union_12': 12, 'bronze_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nation_7': 'nation', 'romania_8': 'romania', 'bronze_9': 'bronze', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'soviet union_12': 'soviet union', 'bronze_13': 'bronze'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'romania_8': [0], 'bronze_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'soviet union_12': [1], 'bronze_13': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '6', '7', '1', '14'], ['2', 'romania', '3', '2', '6', '11'], ['3', 'hungary', '3', '4', '3', '10'], ['4', 'east germany', '4', '2', '2', '8'], ['5', 'poland', '1', '2', '3', '6'], ['6', 'italy', '1', '0', '1', '2'], ['7', 'belgium', '0', '1', '0', '1'], ['8', 'czechoslovakia', '0', '0', '1', '1'], ['9', 'france', '0', '0', '1', '1'], ['total', 'total', '18', '18', '18', '54']] |
1992 - 93 toronto maple leafs season | https://en.wikipedia.org/wiki/1992%E2%80%9393_Toronto_Maple_Leafs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13913477-9.html.csv | comparative | the toronto maple leafs had a game against the philadelphia visitors earlier than st louis in the 1992 - 93 season . | {'row_1': '4', 'row_2': '6', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'philadelphia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose visitor record fuzzily matches to philadelphia .', 'tostr': 'filter_eq { all_rows ; visitor ; philadelphia }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; visitor ; philadelphia } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to philadelphia . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'st louis'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose visitor record fuzzily matches to st louis .', 'tostr': 'filter_eq { all_rows ; visitor ; st louis }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; visitor ; st louis } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to st louis . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; visitor ; philadelphia } ; date } ; hop { filter_eq { all_rows ; visitor ; st louis } ; date } } = true', 'tointer': 'select the rows whose visitor record fuzzily matches to philadelphia . take the date record of this row . select the rows whose visitor record fuzzily matches to st louis . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; visitor ; philadelphia } ; date } ; hop { filter_eq { all_rows ; visitor ; st louis } ; date } } = true | select the rows whose visitor record fuzzily matches to philadelphia . take the date record of this row . select the rows whose visitor record fuzzily matches to st louis . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'visitor_7': 7, 'philadelphia_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'visitor_11': 11, 'st louis_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'visitor_7': 'visitor', 'philadelphia_8': 'philadelphia', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'visitor_11': 'visitor', 'st louis_12': 'st louis', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'visitor_7': [0], 'philadelphia_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'visitor_11': [1], 'st louis_12': [1], 'date_13': [3]} | ['game', 'date', 'visitor', 'score', 'home', 'record', 'points'] | [['78', 'april 3', 'new jersey', '1 - 0', 'toronto', '42 - 25 - 11', '95'], ['79', 'april 4', 'toronto', '0 - 4', 'philadelphia', '42 - 26 - 11', '95'], ['80', 'april 8', 'toronto', '3 - 5', 'winnipeg', '42 - 27 - 11', '95'], ['81', 'april 10', 'philadelphia', '0 - 4', 'toronto', '42 - 28 - 11', '95'], ['82', 'april 11', 'toronto', '4 - 2', 'hartford', '43 - 28 - 11', '97'], ['83', 'april 13', 'st louis', '2 - 1', 'toronto', '44 - 28 - 11', '99'], ['84', 'april 15', 'toronto', '2 - 3', 'chicago', '44 - 29 - 11', '99']] |
mercedes - benz r230 | https://en.wikipedia.org/wiki/Mercedes-Benz_R230 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1867831-2.html.csv | aggregation | on average , the various mercedes - benz r230 models have peak power at around 5500 rpm . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '5500', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'power rpm'], 'result': '5500', 'ind': 0, 'tostr': 'avg { all_rows ; power rpm }'}, '5500'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; power rpm } ; 5500 } = true', 'tointer': 'the average of the power rpm record of all rows is 5500 .'} | round_eq { avg { all_rows ; power rpm } ; 5500 } = true | the average of the power rpm record of all rows is 5500 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'power rpm_4': 4, '5500_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'power rpm_4': 'power rpm', '5500_5': '5500'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'power rpm_4': [0], '5500_5': [1]} | ['model', 'years', 'type / code', 'power rpm', 'torque rpm'] | [['sl 350', '2006 - 2008', 'cubic centimetres ( cuin ) v6 ( m272 )', '6000', '2400 - 5000'], ['sl 500 , sl 550', '2006 - 2008', 'cubic centimetres ( cuin ) v8 ( m273 )', '6000', '2800 - 4800'], ['sl 55 amg', '2006 - 2008', 'cubic centimetres ( cuin ) v8 supercharged ( m113 )', '6100', '2600 - 4000'], ['sl 600', '2006 - 2008', 'cubic centimetres ( cuin ) v12 biturbo ( m275 )', '5000', '1900 - 3500'], ['sl 65 amg', '2004 -', 'cubic centimetres ( cuin ) v12 biturbo ( m275 amg )', '4800 - 5100', '2000 - 4000']] |
wobbe index | https://en.wikipedia.org/wiki/Wobbe_index | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1868929-1.html.csv | ordinal | the fuel that had the second highest upper index kcal/nm was iso-butane . | {'row': '9', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'upper index kcal / nm 3', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; upper index kcal / nm 3 ; 2 }'}, 'fuel gas'], 'result': 'iso - butane', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; upper index kcal / nm 3 ; 2 } ; fuel gas }'}, 'iso - butane'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; upper index kcal / nm 3 ; 2 } ; fuel gas } ; iso - butane } = true', 'tointer': 'select the row whose upper index kcal / nm 3 record of all rows is 2nd maximum . the fuel gas record of this row is iso - butane .'} | eq { hop { nth_argmax { all_rows ; upper index kcal / nm 3 ; 2 } ; fuel gas } ; iso - butane } = true | select the row whose upper index kcal / nm 3 record of all rows is 2nd maximum . the fuel gas record of this row is iso - butane . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'upper index kcal / nm 3_5': 5, '2_6': 6, 'fuel gas_7': 7, 'iso - butane_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', 'upper index kcal / nm 3_5': 'upper index kcal / nm 3', '2_6': '2', 'fuel gas_7': 'fuel gas', 'iso - butane_8': 'iso - butane'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'upper index kcal / nm 3_5': [0], '2_6': [0], 'fuel gas_7': [1], 'iso - butane_8': [2]} | ['fuel gas', 'upper index kcal / nm 3', 'lower index kcal / nm 3', 'upper index mj / nm 3', 'lower index mj / nm 3'] | [['hydrogen', '11528', '9715', '48.23', '40.65'], ['methane', '12735', '11452', '53.28', '47.91'], ['ethane', '16298', '14931', '68.19', '62.47'], ['ethylene', '15253', '14344', '63.82', '60.01'], ['natural gas', '12837', '11597', '53.71', '48.52'], ['propane', '19376', '17817', '81.07', '74.54'], ['propylene', '18413', '17180', '77.04', '71.88'], ['n - butane', '22066', '20336', '92.32', '85.08'], ['iso - butane', '21980', '20247', '91.96', '84.71'], ['butylene - 1', '21142', '19728', '88.46', '82.54'], ['lpg', '20755', '19106', '86.84', '79.94'], ['acetylene', '14655', '14141', '61.32', '59.16']] |
united states house of representatives elections , 1948 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1948 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342218-5.html.csv | comparative | of the incumbents in the 1948 election for the us house of representatives , wilbur mills was first elected 6 years before james william trimble . | {'row_1': '2', 'row_2': '3', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '6 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'wilbur mills'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to wilbur mills .', 'tostr': 'filter_eq { all_rows ; incumbent ; wilbur mills }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; wilbur mills } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to wilbur mills . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'james william trimble'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to james william trimble .', 'tostr': 'filter_eq { all_rows ; incumbent ; james william trimble }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; james william trimble } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to james william trimble . take the first elected record of this row .'}], 'result': '-6 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; incumbent ; wilbur mills } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; james william trimble } ; first elected } }'}, '-6 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; incumbent ; wilbur mills } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; james william trimble } ; first elected } } ; -6 years } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to wilbur mills . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to james william trimble . take the first elected record of this row . the second record is 6 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; incumbent ; wilbur mills } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; james william trimble } ; first elected } } ; -6 years } = true | select the rows whose incumbent record fuzzily matches to wilbur mills . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to james william trimble . take the first elected record of this row . the second record is 6 years larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'incumbent_8': 8, 'wilbur mills_9': 9, 'first elected_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'incumbent_12': 12, 'james william trimble_13': 13, 'first elected_14': 14, '-6 years_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'incumbent_8': 'incumbent', 'wilbur mills_9': 'wilbur mills', 'first elected_10': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'incumbent_12': 'incumbent', 'james william trimble_13': 'james william trimble', 'first elected_14': 'first elected', '-6 years_15': '-6 years'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'incumbent_8': [0], 'wilbur mills_9': [0], 'first elected_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'incumbent_12': [1], 'james william trimble_13': [1], 'first elected_14': [3], '-6 years_15': [5]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'ezekiel c gathings', 'democratic', '1938', 're - elected', 'ezekiel c gathings ( d ) unopposed'], ['arkansas 2', 'wilbur mills', 'democratic', '1938', 're - elected', 'wilbur mills ( d ) unopposed'], ['arkansas 3', 'james william trimble', 'democratic', '1944', 're - elected', 'james william trimble ( d ) unopposed'], ['arkansas 4', 'william fadjo cravens', 'democratic', '1939', 'retired democratic hold', 'boyd anderson tackett ( d ) unopposed'], ['arkansas 5', 'brooks hays', 'democratic', '1942', 're - elected', 'brooks hays ( d ) unopposed'], ['arkansas 6', 'william f norrell', 'democratic', '1938', 're - elected', 'william f norrell ( d ) unopposed']] |
turkish airlines | https://en.wikipedia.org/wiki/Turkish_Airlines | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-167925-2.html.csv | superlative | the turkish airlines flight crash on 3 march 1974 had the highest number of fatalities . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '7', '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', 'fatalities'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; fatalities }'}, 'date'], 'result': '3 march 1974', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; fatalities } ; date }'}, '3 march 1974'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; fatalities } ; date } ; 3 march 1974 } = true', 'tointer': 'select the row whose fatalities record of all rows is maximum . the date record of this row is 3 march 1974 .'} | eq { hop { argmax { all_rows ; fatalities } ; date } ; 3 march 1974 } = true | select the row whose fatalities record of all rows is maximum . the date record of this row is 3 march 1974 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'fatalities_5': 5, 'date_6': 6, '3 march 1974_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'fatalities_5': 'fatalities', 'date_6': 'date', '3 march 1974_7': '3 march 1974'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'fatalities_5': [0], 'date_6': [1], '3 march 1974_7': [2]} | ['date', 'flight', 'aircraft', 'registration', 'location', 'fatalities'] | [['17 february 1959', 'n / a', 'vickers viscount type 793', 'tc - sev', 'london', '14'], ['23 september 1961', '100', 'fokker f27 - 100', 'tc - tay', 'ankara', '28'], ['8 march 1962', 'n / a', 'fairchild f - 27', 'tc - kop', 'adana', '11'], ['3 february 1964', 'n / a', 'douglas c - 47', 'tc - eti', 'ankara', '3'], ['2 february 1969', 'n / a', 'vickers viscount type 794', 'tc - set', 'ankara', '0'], ['26 january 1974', 'n / a', 'fokker f28 - 1000', 'tc - jao', 'izmir', '66'], ['3 march 1974', '981', 'mcdonnell douglas dc - 10', 'tc - jav', 'fontaine - chaalis , oise', '346'], ['30 january 1975', '345', 'fokker f28 - 1000', 'tc - jap', 'istanbul', '42'], ['19 september 1976', '452', 'boeing 727', 'tc - jbh', 'isparta', '154'], ['23 december 1979', 'n / a', 'fokker f28 - 1000', 'tc - jat', 'ankara', '41'], ['16 january 1983', '158', 'boeing 727', 'tc - jbr', 'ankara', '47'], ['29 december 1994', '278', 'boeing 737', 'tc - jes', 'van', '57'], ['7 april 1999', '5904', 'boeing 737', 'tc - jep', 'ceyhan', '6'], ['8 january 2003', '634', 'avro rj - 100', 'tc - thg', 'diyarbakä ± r', '75'], ['25 february 2009', '1951', 'boeing 737', 'tc - jge', 'amsterdam', '9']] |
1926 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1926_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18007085-1.html.csv | aggregation | at the 1926 u.s. golf open , total money earned by players tied for 3rd place was 752 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '752', 'subset': {'col': '1', 'criterion': 'equal', 'value': 't3'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'place', 't3'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; place ; t3 }', 'tointer': 'select the rows whose place record fuzzily matches to t3 .'}, 'money'], 'result': '752', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; place ; t3 } ; money }'}, '752'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; place ; t3 } ; money } ; 752 } = true', 'tointer': 'select the rows whose place record fuzzily matches to t3 . the sum of the money record of these rows is 752 .'} | round_eq { sum { filter_eq { all_rows ; place ; t3 } ; money } ; 752 } = true | select the rows whose place record fuzzily matches to t3 . the sum of the money record of these rows is 752 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'place_5': 5, 't3_6': 6, 'money_7': 7, '752_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'place_5': 'place', 't3_6': 't3', 'money_7': 'money', '752_8': '752'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'place_5': [0], 't3_6': [0], 'money_7': [1], '752_8': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'bobby jones ( a )', 'united states', '70 + 79 + 71 + 73 = 293', '+ 5', '0'], ['2', 'joe turnesa', 'united states', '71 + 74 + 72 + 77 = 294', '+ 6', '500'], ['t3', 'leo diegel', 'united states', '72 + 76 + 75 + 74 = 297', '+ 9', '188'], ['t3', 'johnny farrell', 'united states', '76 + 79 + 69 + 73 = 297', '+ 9', '188'], ['t3', 'bill mehlhorn', 'united states', '68 + 75 + 76 + 78 = 297', '+ 9', '188'], ['t3', 'gene sarazen', 'united states', '78 + 77 + 72 + 70 = 297', '+ 9', '188'], ['7', 'walter hagen', 'united states', '73 + 77 + 74 + 74 = 298', '+ 10', '90'], ['8', 'willie hunter', 'scotland united states', '75 + 77 + 69 + 79 = 300', '+ 12', '80'], ['t9', 'tommy armour', 'scotland united states', '76 + 76 + 74 + 75 = 301', '+ 13', '68'], ['t9', 'willie klein', 'united states', '76 + 74 + 75 + 76 = 301', '+ 13', '68'], ['t9', 'macdonald smith', 'scotland united states', '82 + 76 + 68 + 75 = 301', '+ 13', '68'], ['t9', 'dan williams', 'united states', '72 + 74 + 80 + 75 = 301', '+ 13', '68']] |
2006 masters tournament | https://en.wikipedia.org/wiki/2006_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12626983-4.html.csv | aggregation | the average score for the top 3 players at the 2006 masters tournament was 68 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '68', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '3'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'place', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; place ; 3 }', 'tointer': 'select the rows whose place record is less than or equal to 3 .'}, 'score'], 'result': '68', 'ind': 1, 'tostr': 'avg { filter_less_eq { all_rows ; place ; 3 } ; score }'}, '68'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less_eq { all_rows ; place ; 3 } ; score } ; 68 } = true', 'tointer': 'select the rows whose place record is less than or equal to 3 . the average of the score record of these rows is 68 .'} | round_eq { avg { filter_less_eq { all_rows ; place ; 3 } ; score } ; 68 } = true | select the rows whose place record is less than or equal to 3 . the average of the score record of these rows is 68 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'place_5': 5, '3_6': 6, 'score_7': 7, '68_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'place_5': 'place', '3_6': '3', 'score_7': 'score', '68_8': '68'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'place_5': [0], '3_6': [0], 'score_7': [1], '68_8': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'vijay singh', 'fiji', '67', '- 5'], ['2', 'rocco mediate', 'united states', '68', '- 4'], ['3', 'arron oberholser', 'united states', '69', '- 3'], ['t4', 'tim clark', 'south africa', '70', '- 2'], ['t4', 'retief goosen', 'south africa', '70', '- 2'], ['t4', 'phil mickelson', 'united states', '70', '- 2'], ['t4', 'geoff ogilvy', 'australia', '70', '- 2'], ['t8', 'stuart appleby', 'australia', '71', '- 1'], ['t8', 'rich beem', 'united states', '71', '- 1'], ['t8', 'chad campbell', 'united states', '71', '- 1'], ['t8', 'fred couples', 'united states', '71', '- 1'], ['t8', 'ben crenshaw', 'united states', '71', '- 1'], ['t8', 'ben curtis', 'united states', '71', '- 1'], ['t8', 'ernie els', 'south africa', '71', '- 1'], ['t8', 'david howell', 'england', '71', '- 1'], ['t8', 'billy mayfair', 'united states', '71', '- 1'], ['t8', "nick o'hern", 'australia', '71', '- 1'], ['t8', 'mike weir', 'canada', '71', '- 1']] |
2010 - 11 memphis grizzlies season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Memphis_Grizzlies_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27756474-6.html.csv | majority | mike conley had the majority of high assists performances in the 2010 - 11 memphis grizzlies season . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'mike conley', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high assists', 'mike conley'], 'result': True, 'ind': 0, 'tointer': 'for the high assists records of all rows , most of them fuzzily match to mike conley .', 'tostr': 'most_eq { all_rows ; high assists ; mike conley } = true'} | most_eq { all_rows ; high assists ; mike conley } = true | for the high assists records of all rows , most of them fuzzily match to mike conley . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high assists_3': 3, 'mike conley_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high assists_3': 'high assists', 'mike conley_4': 'mike conley'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high assists_3': [0], 'mike conley_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['4', 'november 2', 'la lakers', 'l 105 - 124 ( ot )', 'rudy gay ( 30 )', 'marc gasol ( 8 )', 'mike conley ( 8 )', 'staples center 18997', '2 - 2'], ['5', 'november 3', 'golden state', 'l 109 - 115 ( ot )', 'rudy gay ( 35 )', 'marc gasol ( 8 )', 'mike conley ( 13 )', 'oracle arena 16607', '2 - 3'], ['6', 'november 5', 'phoenix', 'l 118 - 123 ( 2ot )', 'rudy gay , marc gasol ( 26 )', 'zach randolph ( 14 )', 'mike conley ( 7 )', 'us airways center 16470', '2 - 4'], ['7', 'november 6', 'sacramento', 'w 100 - 91 ( ot )', 'rudy gay ( 32 )', 'zach randolph ( 11 )', 'mike conley ( 5 )', 'arco arena 14085', '3 - 4'], ['8', 'november 8', 'phoenix', 'w 109 - 99 ( ot )', 'zach randolph ( 23 )', 'zach randolph ( 20 )', 'mike conley ( 6 )', 'fedexforum 10786', '4 - 4'], ['9', 'november 10', 'dallas', 'l 91 - 106 ( ot )', 'zach randolph ( 23 )', 'rudy gay , zach randolph ( 9 )', 'mike conley ( 5 )', 'fedexforum 10767', '4 - 5'], ['10', 'november 13', 'boston', 'l 110 - 116 ( ot )', 'rudy gay ( 22 )', 'zach randolph ( 11 )', 'marc gasol ( 5 )', 'fedexforum 18119', '4 - 6'], ['11', 'november 15', 'orlando', 'l 72 - 89 ( ot )', 'marc gasol ( 14 )', 'zach randolph , rudy gay ( 9 )', 'mike conley ( 8 )', 'amway center 18846', '4 - 7'], ['12', 'november 16', 'portland', 'l 99 - 100 ( ot )', 'rudy gay ( 20 )', 'zach randolph ( 14 )', 'mike conley ( 6 )', 'fedexforum 10827', '4 - 8'], ['13', 'november 19', 'washington', 'l 86 - 89 ( ot )', 'zach randolph ( 19 )', 'zach randolph ( 12 )', 'mike conley ( 6 )', 'verizon center 13504', '4 - 9'], ['14', 'november 20', 'miami', 'w 97 - 95 ( ot )', 'zach randolph ( 21 )', 'zach randolph ( 13 )', 'mike conley ( 6 )', 'fedexforum 18119', '5 - 9'], ['15', 'november 24', 'detroit', 'w 105 - 84 ( ot )', 'zach randolph ( 21 )', 'zach randolph ( 14 )', 'mike conley ( 7 )', 'fedexforum 11283', '6 - 9'], ['16', 'november 26', 'golden state', 'w 116 - 111 ( ot )', 'rudy gay ( 25 )', 'zach randolph ( 7 )', 'mike conley ( 5 )', 'fedexforum 14753', '7 - 9'], ['17', 'november 27', 'cleveland', 'l 86 - 92 ( ot )', 'rudy gay ( 17 )', 'zach randolph ( 11 )', 'rudy gay ( 6 )', 'quicken loans arena 20562', '7 - 10']] |
1954 vfl season | https://en.wikipedia.org/wiki/1954_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-4.html.csv | aggregation | during the 1954 vfl season , the average away team score was 10.86 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '10.86', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'away team score'], 'result': '10.86', 'ind': 0, 'tostr': 'avg { all_rows ; away team score }'}, '10.86'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; away team score } ; 10.86 } = true', 'tointer': 'the average of the away team score record of all rows is 10.86 .'} | round_eq { avg { all_rows ; away team score } ; 10.86 } = true | the average of the away team score record of all rows is 10.86 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'away team score_4': 4, '10.86_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'away team score_4': 'away team score', '10.86_5': '10.86'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'away team score_4': [0], '10.86_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '13.17 ( 95 )', 'st kilda', '8.5 ( 53 )', 'kardinia park', '18000', '8 may 1954'], ['collingwood', '10.17 ( 77 )', 'essendon', '9.10 ( 64 )', 'victoria park', '37000', '8 may 1954'], ['carlton', '17.21 ( 123 )', 'footscray', '20.14 ( 134 )', 'princes park', '22000', '8 may 1954'], ['south melbourne', '12.9 ( 81 )', 'richmond', '10.16 ( 76 )', 'lake oval', '23000', '8 may 1954'], ['north melbourne', '11.10 ( 76 )', 'hawthorn', '10.13 ( 73 )', 'arden street oval', '16000', '8 may 1954'], ['melbourne', '14.12 ( 96 )', 'fitzroy', '7.12 ( 54 )', 'mcg', '17500', '8 may 1954']] |
jovan kirovski | https://en.wikipedia.org/wiki/Jovan_Kirovski | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1115680-1.html.csv | majority | the majority of international goals by jovan kirovski were in friendly competition matches . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friendly', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to friendly .', 'tostr': 'most_eq { all_rows ; competition ; friendly } = true'} | most_eq { all_rows ; competition ; friendly } = true | for the competition records of all rows , most of them fuzzily match to friendly . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', 'november 22 , 1994', '1 - 0', '3 - 0', 'friendly'], ['2', 'december 11 , 1994', '1 - 1', '1 - 1', 'friendly'], ['3', 'january 21 , 1996', '3 - 0', '3 - 0', '1996 concacaf gold cup'], ['4', 'june 17 , 1997', '2 - 0', '2 - 1', 'friendly'], ['5', 'february 6 , 1999', '1 - 0', '3 - 0', 'friendly'], ['6', 'july 24 , 1999', '2 - 0', '2 - 1', 'friendly'], ['7', 'february 12 , 2000', '1 - 0', '3 - 0', '2000 concacaf gold cup'], ['8', 'march 29 , 2003', '1 - 0', '2 - 0', 'friendly'], ['9', 'june 8 , 2003', '2 - 1', '2 - 1', 'friendly']] |
circuit trois - rivières | https://en.wikipedia.org/wiki/Circuit_Trois-Rivi%C3%A8res | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11095234-7.html.csv | ordinal | the 2nd fewest number of laps that were driven at the circuit trois - rivières was in 2010 . | {'row': '4', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'distance / duration', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; distance / duration ; 2 }'}, 'year'], 'result': '2010', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; distance / duration ; 2 } ; year }'}, '2010'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; distance / duration ; 2 } ; year } ; 2010 } = true', 'tointer': 'select the row whose distance / duration record of all rows is 2nd minimum . the year record of this row is 2010 .'} | eq { hop { nth_argmin { all_rows ; distance / duration ; 2 } ; year } ; 2010 } = true | select the row whose distance / duration record of all rows is 2nd minimum . the year record of this row is 2010 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'distance / duration_5': 5, '2_6': 6, 'year_7': 7, '2010_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'distance / duration_5': 'distance / duration', '2_6': '2', 'year_7': 'year', '2010_8': '2010'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'distance / duration_5': [0], '2_6': [0], 'year_7': [1], '2010_8': [2]} | ['year', 'date', 'driver', 'team', 'distance / duration'] | [['2007', 'sept 4', 'kerry micks', 'beyond digital imaging', '41 laps'], ['2008', 'aug 17', 'andrew ranger', 'wal - mart / tide', '46 laps'], ['2009', 'aug 17', 'andrew ranger', 'wal - mart / tide', '43 laps'], ['2010', 'aug 15', 'andrew ranger', 'dodge dealers of quebec', '42 laps'], ['2011', 'aug 7', 'robin buck', 'quaker state / durabody', '44 laps'], ['2012', 'aug 7', 'andrew ranger', 'dodge / gc motorsports', '44 laps']] |
1981 - 82 coupe de france | https://en.wikipedia.org/wiki/1981%E2%80%9382_Coupe_de_France | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16893470-1.html.csv | comparative | as saint - étienne had a higher scoring game than girondins de bordeaux . | {'row_1': '2', 'row_2': '1', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 1', 'as saint - étienne ( d1 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team 1 record fuzzily matches to as saint - étienne ( d1 ) .', 'tostr': 'filter_eq { all_rows ; team 1 ; as saint - étienne ( d1 ) }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team 1 ; as saint - étienne ( d1 ) } ; score }', 'tointer': 'select the rows whose team 1 record fuzzily matches to as saint - étienne ( d1 ) . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 1', 'girondins de bordeaux ( d1 )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team 1 record fuzzily matches to girondins de bordeaux ( d1 ) .', 'tostr': 'filter_eq { all_rows ; team 1 ; girondins de bordeaux ( d1 ) }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team 1 ; girondins de bordeaux ( d1 ) } ; score }', 'tointer': 'select the rows whose team 1 record fuzzily matches to girondins de bordeaux ( d1 ) . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team 1 ; as saint - étienne ( d1 ) } ; score } ; hop { filter_eq { all_rows ; team 1 ; girondins de bordeaux ( d1 ) } ; score } } = true', 'tointer': 'select the rows whose team 1 record fuzzily matches to as saint - étienne ( d1 ) . take the score record of this row . select the rows whose team 1 record fuzzily matches to girondins de bordeaux ( d1 ) . take the score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; team 1 ; as saint - étienne ( d1 ) } ; score } ; hop { filter_eq { all_rows ; team 1 ; girondins de bordeaux ( d1 ) } ; score } } = true | select the rows whose team 1 record fuzzily matches to as saint - étienne ( d1 ) . take the score record of this row . select the rows whose team 1 record fuzzily matches to girondins de bordeaux ( d1 ) . take the score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team 1_7': 7, 'as saint - étienne (d1)_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team 1_11': 11, 'girondins de bordeaux (d1)_12': 12, 'score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team 1_7': 'team 1', 'as saint - étienne (d1)_8': 'as saint - étienne ( d1 )', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team 1_11': 'team 1', 'girondins de bordeaux (d1)_12': 'girondins de bordeaux ( d1 )', 'score_13': 'score'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team 1_7': [0], 'as saint - étienne (d1)_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team 1_11': [1], 'girondins de bordeaux (d1)_12': [1], 'score_13': [3]} | ['team 1', 'score', 'team 2', '1st round', '2nd round'] | [['girondins de bordeaux ( d1 )', '4 - 2', 'as monaco ( d1 )', '2 - 1', '2 - 1'], ['as saint - étienne ( d1 )', '5 - 3', 'stade brestois ( d1 )', '2 - 0', '3 - 3'], ['sc bastia ( d1 )', '4 - 3', 'olympique lyonnais ( d1 )', '2 - 0', '2 - 3'], ['tours fc ( d1 )', '6 - 5', 'fc metz ( d1 )', '4 - 1', '2 - 4'], ['olympique de marseille ( d2 )', '1 - 4', 'paris sg ( d1 )', '0 - 1', '1 - 3'], ['sporting toulon var ( d2 )', '4 - 2', 'as nancy ( d1 )', '2 - 1', '2 - 1'], ['valenciennes fc ( d1 )', '4 - 2', 'le havre ac ( d2 )', '2 - 0', '2 - 2'], ['stade lavallois ( d1 )', '2 - 1', 'besançon rc ( d2 )', '2 - 1', '0 - 0']] |
2007 open championship | https://en.wikipedia.org/wiki/2007_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12278571-8.html.csv | aggregation | the combined winnings of the players who tied for 8th in the 2007 open championship was $ 379,000 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '$ 379,000', 'subset': {'col': '1', 'criterion': 'equal', 'value': 't8'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'place', 't8'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; place ; t8 }', 'tointer': 'select the rows whose place record fuzzily matches to t8 .'}, 'money'], 'result': '$ 379,000', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; place ; t8 } ; money }'}, '$ 379,000'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; place ; t8 } ; money } ; $ 379,000 } = true', 'tointer': 'select the rows whose place record fuzzily matches to t8 . the sum of the money record of these rows is $ 379,000 .'} | round_eq { sum { filter_eq { all_rows ; place ; t8 } ; money } ; $ 379,000 } = true | select the rows whose place record fuzzily matches to t8 . the sum of the money record of these rows is $ 379,000 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'place_5': 5, 't8_6': 6, 'money_7': 7, '$379,000_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'place_5': 'place', 't8_6': 't8', 'money_7': 'money', '$379,000_8': '$ 379,000'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'place_5': [0], 't8_6': [0], 'money_7': [1], '$379,000_8': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'pádraig harrington', 'ireland', '69 + 73 + 68 + 67 = 277', '- 7', 'playoff'], ['t1', 'sergio garcía', 'spain', '65 + 71 + 68 + 73 = 277', '- 7', 'playoff'], ['3', 'andrés romero', 'argentina', '71 + 70 + 70 + 67 = 278', '- 6', '290000'], ['t4', 'ernie els', 'south africa', '72 + 70 + 68 + 69 = 279', '- 5', '200000'], ['t4', 'richard green', 'australia', '72 + 73 + 70 + 64 = 279', '- 5', '200000'], ['t6', 'stewart cink', 'united states', '73 + 73 + 69 + 65 = 280', '- 4', '145500'], ['t6', 'hunter mahan', 'united states', '69 + 73 + 68 + 70 = 280', '- 4', '145500'], ['t8', 'kj choi', 'south korea', '69 + 69 + 72 + 71 = 281', '- 3', '94750'], ['t8', 'ben curtis', 'united states', '72 + 74 + 70 + 65 = 281', '- 3', '94750'], ['t8', 'steve stricker', 'united states', '71 + 72 + 64 + 74 = 281', '- 3', '94750'], ['t8', 'mike weir', 'canada', '71 + 68 + 72 + 70 = 281', '- 3', '94750']] |
mexico national under - 20 football team | https://en.wikipedia.org/wiki/Mexico_national_under-20_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17736508-2.html.csv | ordinal | of the managers of the mexico national under - 20 football team , horacio casarin has the 2nd lowest win percentage . | {'row': '1', 'col': '6', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'win %', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; win % ; 2 }'}, 'manager'], 'result': 'horacio casarin', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; win % ; 2 } ; manager }'}, 'horacio casarin'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; win % ; 2 } ; manager } ; horacio casarin } = true', 'tointer': 'select the row whose win % record of all rows is 2nd minimum . the manager record of this row is horacio casarin .'} | eq { hop { nth_argmin { all_rows ; win % ; 2 } ; manager } ; horacio casarin } = true | select the row whose win % record of all rows is 2nd minimum . the manager record of this row is horacio casarin . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'win %_5': 5, '2_6': 6, 'manager_7': 7, 'horacio casarin_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', 'win %_5': 'win %', '2_6': '2', 'manager_7': 'manager', 'horacio casarin_8': 'horacio casarin'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'win %_5': [0], '2_6': [0], 'manager_7': [1], 'horacio casarin_8': [2]} | ['manager', 'mexico career', 'played', 'drawn', 'lost', 'win %'] | [['horacio casarin', '1977', '5', '4', '0', '20.0'], ['mario velarde', '1983', '3', '1', '2', '0.00'], ['jesús del muro', '1985 , 1998 - 1999', '12', '1', '2', '75.00'], ['alfonso portugal diaz', '1991', '4', '2', '1', '25.0'], ['juan de dios castillo', '1992 - 1993', '7', '2', '1', '60'], ['juan manuel alvarez', '1994', '3', '0', '1', '56.6'], ['josé luis real', '1996 - 1997 , 2001', '12', '3', '3', '50.00'], ['eduardo rergis', '2002 - 2003', '6', '1', '3', '33.3'], ['humberto grondona', '2005', '3', '0', '2', '33.3'], ['jesús ramírez', '2007 - 2009', '8', '1', '1', '75.00'], ['juan carlos chávez', '2009 - 2011', '19', '3', '4', '63.15'], ['sergio almaguer', '2011 -', '5', '0', '0', '100']] |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-20.html.csv | unique | thomas j lane was the only incumbent who was first elected in 1941 . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '1941', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first elected', '1941'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is equal to 1941 .', 'tostr': 'filter_eq { all_rows ; first elected ; 1941 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; first elected ; 1941 } }', 'tointer': 'select the rows whose first elected record is equal to 1941 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first elected', '1941'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is equal to 1941 .', 'tostr': 'filter_eq { all_rows ; first elected ; 1941 }'}, 'incumbent'], 'result': 'thomas j lane', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; first elected ; 1941 } ; incumbent }'}, 'thomas j lane'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; first elected ; 1941 } ; incumbent } ; thomas j lane }', 'tointer': 'the incumbent record of this unqiue row is thomas j lane .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; first elected ; 1941 } } ; eq { hop { filter_eq { all_rows ; first elected ; 1941 } ; incumbent } ; thomas j lane } } = true', 'tointer': 'select the rows whose first elected record is equal to 1941 . there is only one such row in the table . the incumbent record of this unqiue row is thomas j lane .'} | and { only { filter_eq { all_rows ; first elected ; 1941 } } ; eq { hop { filter_eq { all_rows ; first elected ; 1941 } ; incumbent } ; thomas j lane } } = true | select the rows whose first elected record is equal to 1941 . there is only one such row in the table . the incumbent record of this unqiue row is thomas j lane . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'first elected_7': 7, '1941_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'thomas j lane_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'first elected_7': 'first elected', '1941_8': '1941', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'thomas j lane_10': 'thomas j lane'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'first elected_7': [0], '1941_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'thomas j lane_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['massachusetts 1', 'john w heselton', 'republican', '1944', 're - elected', 'john w heselton ( r ) 55.6 % john j dwyer ( d ) 44.4 %'], ['massachusetts 3', 'philip philbin', 'democratic', '1942', 're - elected', 'philip philbin ( d ) unopposed'], ['massachusetts 5', 'edith nourse rogers', 'republican', '1925', 're - elected', 'edith nourse rogers ( r ) unopposed'], ['massachusetts 7', 'thomas j lane', 'democratic', '1941', 're - elected', 'thomas j lane ( d ) unopposed'], ['massachusetts 11', "tip o'neill", 'democratic', '1952', 're - elected', "tip o'neill ( d ) 78.2 % charles s bolster ( r ) 21.8 %"]] |
pune suburban railway | https://en.wikipedia.org/wiki/Pune_Suburban_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29301050-1.html.csv | ordinal | train number 99806 has the second earliest departure time from prune . | {'row': '2', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'departure pune', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; departure pune ; 2 }'}, 'train number'], 'result': '99806', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; departure pune ; 2 } ; train number }'}, '99806'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; departure pune ; 2 } ; train number } ; 99806 } = true', 'tointer': 'select the row whose departure pune record of all rows is 2nd minimum . the train number record of this row is 99806 .'} | eq { hop { nth_argmin { all_rows ; departure pune ; 2 } ; train number } ; 99806 } = true | select the row whose departure pune record of all rows is 2nd minimum . the train number record of this row is 99806 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'departure pune_5': 5, '2_6': 6, 'train number_7': 7, '99806_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'departure pune_5': 'departure pune', '2_6': '2', 'train number_7': 'train number', '99806_8': '99806'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'departure pune_5': [0], '2_6': [0], 'train number_7': [1], '99806_8': [2]} | ['train number', 'train name', 'departure pune', 'arrival lonavla', 'frequency', 'origin'] | [['99804', 'lonavala local', '04:45', '06:05', 'daily', 'pune railway station'], ['99806', 'lonavala local', '05:45', '07:05', 'daily', 'pune railway station'], ['99808', 'lonavala local', '06:30', '07:50', 'daily', 'pune railway station'], ['99810', 'lonavala local', '08:05', '10:25', 'daily', 'pune railway station'], ['99812', 'lonavala local', '09:55', '11:15', 'daily', 'pune railway station'], ['99814', 'lonavala local', '10:50', '12:25', 'daily', 'shivajinagar station'], ['99816', 'lonavala local', '12:05', '13:17', 'daily', 'pune railway station'], ['99820', 'lonavala local', '13:00', '14:20', 'daily', 'pune railway station'], ['99822', 'lonavala local', '16:25', '17:45', 'daily', 'pune railway station'], ['99824', 'lonavala local', '16:25', '17:37', 'daily', 'pune railway station'], ['99826', 'lonavala local', '19:05', '20:25', 'daily', 'pune railway station'], ['99828', 'lonavala local', '19:35', '21:05', 'daily', 'shivajinagar station'], ['99830', 'lonavala local', '20:00', '21:20', 'daily', 'pune railway station'], ['99832', 'lonavala local', '20:00', '21:12', 'daily', 'pune railway station'], ['99834', 'lonavala local', '20:45', '21:57', 'daily', 'pune railway station'], ['99836', 'lonavala local', '21:10', '22:22', 'daily', 'pune railway station']] |
european poker tour | https://en.wikipedia.org/wiki/European_Poker_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1296513-8.html.csv | majority | the majority of winners prize money for the european poker tour events were more than 500,000 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '500,000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'prize', '500,000'], 'result': True, 'ind': 0, 'tointer': 'for the prize records of all rows , most of them are greater than 500,000 .', 'tostr': 'most_greater { all_rows ; prize ; 500,000 } = true'} | most_greater { all_rows ; prize ; 500,000 } = true | for the prize records of all rows , most of them are greater than 500,000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'prize_3': 3, '500,000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'prize_3': 'prize', '500,000_4': '500,000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'prize_3': [0], '500,000_4': [0]} | ['date', 'city', 'event', 'winner', 'prize'] | [['2 - 7 august 2011', 'tallinn', 'ept tallinn', 'ronny kaiser', '275000'], ['27 aug - 1 sep 2011', 'barcelona', 'ept barcelona', 'martin schleich', '850000'], ['30 sep - 6 oct 2011', 'london', 'ept london', 'benny spindler', '750000'], ['21 - 27 october 2011', 'sanremo', 'ept sanremo', 'andrey pateychuk', '800000'], ['15 - 20 november 2011', 'loutraki', 'ept loutraki', 'zimnan ziyard', '347000'], ['5 - 10 december 2011', 'prague', 'ept prague', 'martin finger', '720000'], ['5 - 15 january 2012', 'paradise island', '2012 pokerstars caribbean adventure', 'john dibella', '1775000'], ['31 jan - 6 feb 2012', 'deauville', 'ept deauville', 'vadzim kursevich', '875000'], ['20 - 25 february 2012', 'copenhagen', 'ept copenhagen', 'mickey petersen', 'dkk 2515000'], ['12 - 17 march 2012', 'madrid', 'ept madrid', 'frederik jensen', '435000'], ['26 - 31 march 2012', 'campione', 'ept campione', 'jannick wrang', '640000'], ['16 - 21 april 2012', 'berlin', 'ept berlin', 'davidi kitai', '712000'], ['25 - 30 april 2012', 'monte carlo', 'ept monte carlo grand final', 'mohsin charania', '1350000']] |
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 | majority | most of the schools in the three rivers conference joined in 1971 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1971', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'year joined', '1971'], 'result': True, 'ind': 0, 'tointer': 'for the year joined records of all rows , most of them are equal to 1971 .', 'tostr': 'most_eq { all_rows ; year joined ; 1971 } = true'} | most_eq { all_rows ; year joined ; 1971 } = true | for the year joined records of all rows , most of them are equal to 1971 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year joined_3': 3, '1971_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year joined_3': 'year joined', '1971_4': '1971'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'year joined_3': [0], '1971_4': [0]} | ['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']] |
1935 masters tournament | https://en.wikipedia.org/wiki/1935_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12586224-1.html.csv | majority | the majority of golfers in the top 10 finishes from the 1935 masters had a score below 71 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '71', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'score', '71'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them are less than 71 .', 'tostr': 'most_less { all_rows ; score ; 71 } = true'} | most_less { all_rows ; score ; 71 } = true | for the score records of all rows , most of them are less than 71 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '71_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '71_4': '71'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '71_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'henry picard', 'united states', '67', '- 5'], ['t2', 'gene sarazen', 'united states', '68', '- 4'], ['t2', 'ray mangrum', 'united states', '68', '- 4'], ['t2', 'willie goggin', 'united states', '68', '- 4'], ['5', 'craig wood', 'united states', '69', '- 3'], ['t6', 'olin dutra', 'united states', '70', '- 2'], ['t6', 'jimmy hines', 'united states', '70', '- 2'], ['t6', 'johnny revolta', 'united states', '70', '- 2'], ['t6', 'paul runyan', 'united states', '70', '- 2'], ['t10', 'tony manero', 'united states', '71', '- 1'], ['t10', 'leo diegel', 'united states', '71', '- 1'], ['t10', 'willie klein', 'united states', '71', '- 1'], ['t10', 'mike turnesa', 'united states', '71', '- 1']] |
united states house of representatives elections , 1966 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1966 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341843-44.html.csv | majority | most of the people that were voted into the texas house of representatives in 1966 had been re-elected . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 're - elected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to re - elected .', 'tostr': 'most_eq { all_rows ; result ; re - elected } = true'} | most_eq { all_rows ; result ; re - elected } = true | for the result records of all rows , most of them fuzzily match to re - elected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're - elected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're - elected_4': 're - elected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) unopposed'], ['texas 2', 'john dowdy redistricted from 7th', 'democratic', '1952', 're - elected', 'john dowdy ( d ) unopposed'], ['texas 3', 'joe r pool redistricted from at - large', 'democratic', '1962', 're - elected', 'joe r pool ( d ) 53.4 % bill hayes ( r ) 46.6 %'], ['texas 4', 'ray roberts', 'democratic', '1962', 're - elected', 'ray roberts ( d ) unopposed'], ['texas 4', 'lindley beckworth redistricted from 3rd', 'democratic', '1956', 'lost renomination democratic loss', 'ray roberts ( d ) unopposed'], ['texas 5', 'earle cabell', 'democratic', '1964', 're - elected', 'earle cabell ( d ) 61.0 % duke burgess ( r ) 39.0 %'], ['texas 6', 'olin e teague', 'democratic', '1946', 're - elected', 'olin e teague ( d ) unopposed'], ['texas 8', 'lera millard thomas', 'democratic', '1966', 'retired democratic hold', 'robert c eckhardt ( d ) 92.3 % w d spayne ( r ) 7.7 %'], ['texas 9', 'jack brooks redistricted from 2nd', 'democratic', '1952', 're - elected', 'jack brooks ( d ) unopposed'], ['texas 9', 'clark w thompson', 'democratic', '1947', 'retired democratic loss', 'jack brooks ( d ) unopposed'], ['texas 12', 'jim wright', 'democratic', '1954', 're - elected', 'jim wright ( d ) unopposed'], ['texas 14', 'john andrew young', 'democratic', '1956', 're - elected', 'john andrew young ( d ) unopposed'], ['texas 15', 'kika de la garza', 'democratic', '1964', 're - elected', 'kika de la garza ( d ) unopposed'], ['texas 16', 'richard c white', 'democratic', '1964', 're - elected', 'richard c white ( d ) unopposed'], ['texas 17', 'omar burleson', 'democratic', '1946', 're - elected', 'omar burleson ( d ) unopposed'], ['texas 18', 'walter e rogers', 'democratic', '1950', 'retired republican gain', 'bob price ( r ) 59.5 % dee miller ( d ) 40.5 %'], ['texas 19', 'george h mahon', 'democratic', '1934', 're - elected', 'george h mahon ( d ) unopposed'], ['texas 21', 'o c fisher', 'democratic', '1942', 're - elected', 'o c fisher ( d ) unopposed']] |
list of amd athlon x2 microprocessors | https://en.wikipedia.org/wiki/List_of_AMD_Athlon_X2_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13869651-2.html.csv | aggregation | the average frequency for amd athlon x2 microprocessors is around 2200 mhz . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '2200 mhz', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'frequency'], 'result': '2200 mhz', 'ind': 0, 'tostr': 'avg { all_rows ; frequency }'}, '2200 mhz'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; frequency } ; 2200 mhz } = true', 'tointer': 'the average of the frequency record of all rows is 2200 mhz .'} | round_eq { avg { all_rows ; frequency } ; 2200 mhz } = true | the average of the frequency record of all rows is 2200 mhz . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'frequency_4': 4, '2200 mhz_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'frequency_4': 'frequency', '2200 mhz_5': '2200 mhz'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'frequency_4': [0], '2200 mhz_5': [1]} | ['model number', 'stepping', 'frequency', 'l2 cache', 'multi 1', 'v core', 'socket', 'release date', 'part number ( s )'] | [['athlon x2 3250e', 'g2', '1500 mhz', '2 512 kb', '7.5', '1.15 - 1.25 v', 'socket am2', 'q4 , 2008', 'adj3250iav5do'], ['athlon x2 4050e', 'g2', '2100 mhz', '2 512 kb', '10.5', '1.15 - 1.25 v', 'socket am2', 'april 21 , 2008', 'adh4050iaa5do'], ['athlon x2 4450e', 'g2', '2300 mhz', '2 512 kb', '11.5', '1.15 - 1.25 v', 'socket am2', 'april 21 , 2008', 'adh4450iaa5do'], ['athlon x2 4850e', 'g2', '2500 mhz', '2 512 kb', '12.5', '1.15 - 1.25 v', 'socket am2', 'march 5 , 2008', 'adh4850iaa5do'], ['athlon x2 5050e', 'g2', '2600 mhz', '2 512 kb', '13', '1.15 - 1.25 v', 'socket am2', 'october 21 , 2008', 'adh5050iaa5do']] |
2002 fivb women 's volleyball world championship qualification | https://en.wikipedia.org/wiki/2002_FIVB_Women%27s_Volleyball_World_Championship_qualification | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17626199-35.html.csv | count | two of these matches took place on the 14th of july . | {'scope': 'all', 'criterion': 'equal', 'value': '14 jul', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '14 jul'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 14 jul .', 'tostr': 'filter_eq { all_rows ; date ; 14 jul }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; 14 jul } }', 'tointer': 'select the rows whose date record fuzzily matches to 14 jul . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; 14 jul } } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 14 jul . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; date ; 14 jul } } ; 2 } = true | select the rows whose date record fuzzily matches to 14 jul . 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, 'date_5': 5, '14 jul_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', 'date_5': 'date', '14 jul_6': '14 jul', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '14 jul_6': [0], '2_7': [2]} | ['date', 'score', 'set 1', 'set 2', 'set 3', 'total'] | [['13 jul', '0 - 3', '9 - 25', '17 - 25', '12 - 25', '38 - 75'], ['13 jul', '3 - 0', '25 - 23', '25 - 10', '25 - 13', '75 - 46'], ['14 jul', '3 - 0', '25 - 13', '25 - 10', '25 - 11', '75 - 34'], ['14 jul', '1 - 3', '25 - 22', '16 - 25', '15 - 25', '70 - 97'], ['15 jul', '0 - 3', '16 - 25', '19 - 25', '18 - 25', '53 - 75'], ['15 jul', '3 - 0', '25 - 23', '25 - 16', '25 - 14', '75 - 53']] |
florent piétrus | https://en.wikipedia.org/wiki/Florent_Pi%C3%A9trus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2761641-1.html.csv | superlative | florent piétrus scored the lowest number of points per game during the 2011 eurobasket tournament . | {'scope': 'all', 'col_superlative': '3', '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', 'points per game'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; points per game }'}, 'tournament'], 'result': '2011 eurobasket', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; points per game } ; tournament }'}, '2011 eurobasket'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; points per game } ; tournament } ; 2011 eurobasket } = true', 'tointer': 'select the row whose points per game record of all rows is minimum . the tournament record of this row is 2011 eurobasket .'} | eq { hop { argmin { all_rows ; points per game } ; tournament } ; 2011 eurobasket } = true | select the row whose points per game record of all rows is minimum . the tournament record of this row is 2011 eurobasket . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'points per game_5': 5, 'tournament_6': 6, '2011 eurobasket_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'points per game_5': 'points per game', 'tournament_6': 'tournament', '2011 eurobasket_7': '2011 eurobasket'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'points per game_5': [0], 'tournament_6': [1], '2011 eurobasket_7': [2]} | ['tournament', 'games played', 'points per game', 'rebounds per game', 'assists per game'] | [['2003 eurobasket', '6', '6.8', '5.3', '0.7'], ['2005 eurobasket', '7', '7.6', '7.1', '0.6'], ['2006 fiba world championship', '9', '9.7', '6.7', '0.6'], ['2007 eurobasket', '7', '8.9', '3.7', '0.6'], ['2009 eurobasket', '8', '6.5', '2.9', '1.1'], ['2010 fiba world championship', '4', '4.5', '4.8', '1.5'], ['2011 eurobasket', '11', '2.6', '3.4', '0.8'], ['2012 olympics', '6', '4.5', '2.8', '0.5']] |
list of bohemian consorts | https://en.wikipedia.org/wiki/List_of_Bohemian_consorts | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10870631-9.html.csv | ordinal | maria teresa of the two sicilies was the second person among the bohemian consort from the house of hasburg-lorraine to become queen . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'became queen', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; became queen ; 2 }'}, 'name'], 'result': 'maria teresa of the two sicilies', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; became queen ; 2 } ; name }'}, 'maria teresa of the two sicilies'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; became queen ; 2 } ; name } ; maria teresa of the two sicilies } = true', 'tointer': 'select the row whose became queen record of all rows is 2nd minimum . the name record of this row is maria teresa of the two sicilies .'} | eq { hop { nth_argmin { all_rows ; became queen ; 2 } ; name } ; maria teresa of the two sicilies } = true | select the row whose became queen record of all rows is 2nd minimum . the name record of this row is maria teresa of the two sicilies . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'became queen_5': 5, '2_6': 6, 'name_7': 7, 'maria teresa of the two sicilies_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', 'became queen_5': 'became queen', '2_6': '2', 'name_7': 'name', 'maria teresa of the two sicilies_8': 'maria teresa of the two sicilies'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'became queen_5': [0], '2_6': [0], 'name_7': [1], 'maria teresa of the two sicilies_8': [2]} | ['name', 'father', 'birth', 'marriage', 'became queen', 'ceased to be queen', 'death', 'spouse'] | [['maria louisa of spain', 'charles iii of spain', '24 november 1745', '16 february 1764', '20 february 1790', '1 march 1792', '15 may 1792', 'leopold ii'], ['maria teresa of the two sicilies', 'ferdinand i of the two sicilies', '6 june 1772', '15 august 1790', '1 march 1792', '13 april 1807', '13 april 1807', 'francis ii'], ['maria ludovika of austria - este', 'archduke ferdinand of austria - este', '14 december 1787', '6 january 1808', '6 january 1808', '7 april 1816', '7 april 1816', 'francis ii'], ['caroline augusta of bavaria', 'maximilian i joseph of bavaria', '8 february 1792', '29 october 1816', '29 october 1816', "2 march 1835 husband 's death", '9 february 1873', 'francis ii'], ['maria anna of sardinia', 'victor emmanuel i of sardinia', '19 september 1803', '12 february 1831', "2 march 1835 husband 's ascension", "2 december 1848 husband 's abdication", '4 may 1884', 'ferdinand v'], ['elisabeth of bavaria', 'maximilian joseph , duke in bavaria', '24 december 1837', '24 april 1854', '24 april 1854', '10 september 1898', '10 september 1898', 'francis joseph i'], ['zita of bourbon - parma', 'robert i , duke of parma', '9 may 1892', '13 june 1911', "21 november 1916 husband 's ascension", "11 november 1918 husband 's deposition", '14 march 1989', 'charles iii']] |
1977 - 78 new york rangers season | https://en.wikipedia.org/wiki/1977%E2%80%9378_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17310913-13.html.csv | count | in the 1977 - 78 new york rangers season , among canadian players , 6 of them played as wingers ( lw ) . | {'scope': 'subset', 'criterion': 'equal', 'value': 'lw', 'result': '6', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'canada'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nationality ; canada }', 'tointer': 'select the rows whose nationality record fuzzily matches to canada .'}, 'position', 'lw'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose position record fuzzily matches to lw .', 'tostr': 'filter_eq { filter_eq { all_rows ; nationality ; canada } ; position ; lw }'}], 'result': '6', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; nationality ; canada } ; position ; lw } }', 'tointer': 'select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose position record fuzzily matches to lw . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; nationality ; canada } ; position ; lw } } ; 6 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose position record fuzzily matches to lw . the number of such rows is 6 .'} | eq { count { filter_eq { filter_eq { all_rows ; nationality ; canada } ; position ; lw } } ; 6 } = true | select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose position record fuzzily matches to lw . the number of such rows is 6 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'nationality_6': 6, 'canada_7': 7, 'position_8': 8, 'lw_9': 9, '6_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'nationality_6': 'nationality', 'canada_7': 'canada', 'position_8': 'position', 'lw_9': 'lw', '6_10': '6'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'nationality_6': [0], 'canada_7': [0], 'position_8': [1], 'lw_9': [1], '6_10': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'lucien deblois', 'rw', 'canada', 'sorel black hawks ( qmjhl )'], ['1', 'ron duguay', 'c', 'canada', 'sudbury wolves ( oha )'], ['2', 'mike keating', 'lw', 'canada', 'st catharines fincups ( oha )'], ['3', 'steve baker', 'g', 'united states', 'union college ( ncaa )'], ['4', 'mario marois', 'd', 'canada', 'quebec remparts ( qmjhl )'], ['5', 'benoit gosselin', 'lw', 'canada', 'trois - rivières draveurs ( qmjhl )'], ['6', 'john bethel', 'lw', 'canada', 'boston university ( ncaa )'], ['7', 'bob sullivan', 'lw', 'canada', 'chicoutimi saguenéens ( qmjhl )'], ['8', 'lance nethery', 'c', 'canada', 'cornell university ( ncaa )'], ['9', 'alex jeans', 'c', 'canada', 'university of toronto ( ciau )'], ['10', 'pete raps', 'lw', 'canada', 'western michigan university ( ncaa )'], ['11', 'mike brown', 'rw', 'united states', 'western michigan university ( ncaa )'], ['12', 'mark miller', 'lw', 'canada', 'university of michigan ( ncaa )']] |
united states house of representatives elections , 1868 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1868 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1434788-5.html.csv | ordinal | john thomas wilson recorded the highest percentage ratio among all candidates of the 1868 house of representatives elections . | {'row': '4', 'col': '6', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'candidates', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; candidates ; 1 }'}, 'incumbent'], 'result': 'john thomas wilson', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent }'}, 'john thomas wilson'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; john thomas wilson } = true', 'tointer': 'select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is john thomas wilson .'} | eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; john thomas wilson } = true | select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is john thomas wilson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, '1_6': 6, 'incumbent_7': 7, 'john thomas wilson_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', 'candidates_5': 'candidates', '1_6': '1', 'incumbent_7': 'incumbent', 'john thomas wilson_8': 'john thomas wilson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], '1_6': [0], 'incumbent_7': [1], 'john thomas wilson_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['ohio 7', 'samuel shellabarger', 'republican', '1864', 'retired republican hold', 'james j winans ( r ) 50.2 % john h thomas ( d ) 49.8 %'], ['ohio 8', 'john beatty', 'republican', '1868 ( s )', 're - elected', 'john beatty ( r ) 52.0 % john h benson ( d ) 48.0 %'], ['ohio 10', 'james m ashley', 'republican', '1862', 'lost re - election democratic gain', 'truman h hoag ( d ) 51.5 % james m ashley ( d ) 48.5 %'], ['ohio 11', 'john thomas wilson', 'republican', '1866', 're - elected', 'john thomas wilson ( r ) 54.2 % john sands ( d ) 45.8 %'], ['ohio 16', 'john bingham', 'republican', '1864', 're - elected', 'john bingham ( r ) 50.8 % josiah m estep ( d ) 49.2 %']] |
texas 's 5th congressional district | https://en.wikipedia.org/wiki/Texas%27s_5th_congressional_district | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140249-1.html.csv | comparative | pete sessions took office in the 5th district after jim mattox had been in office . | {'row_1': '17', 'row_2': '15', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'pete sessions'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to pete sessions .', 'tostr': 'filter_eq { all_rows ; name ; pete sessions }'}, 'took office'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; pete sessions } ; took office }', 'tointer': 'select the rows whose name record fuzzily matches to pete sessions . take the took office record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'jim mattox'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to jim mattox .', 'tostr': 'filter_eq { all_rows ; name ; jim mattox }'}, 'took office'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; jim mattox } ; took office }', 'tointer': 'select the rows whose name record fuzzily matches to jim mattox . take the took office record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; pete sessions } ; took office } ; hop { filter_eq { all_rows ; name ; jim mattox } ; took office } } = true', 'tointer': 'select the rows whose name record fuzzily matches to pete sessions . take the took office record of this row . select the rows whose name record fuzzily matches to jim mattox . take the took office record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; pete sessions } ; took office } ; hop { filter_eq { all_rows ; name ; jim mattox } ; took office } } = true | select the rows whose name record fuzzily matches to pete sessions . take the took office record of this row . select the rows whose name record fuzzily matches to jim mattox . take the took office record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'pete sessions_8': 8, 'took office_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'jim mattox_12': 12, 'took office_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'pete sessions_8': 'pete sessions', 'took office_9': 'took office', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'jim mattox_12': 'jim mattox', 'took office_13': 'took office'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'pete sessions_8': [0], 'took office_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'jim mattox_12': [1], 'took office_13': [3]} | ['name', 'took office', 'left office', 'party', 'district residence'] | [['district created march 4 , 1875', 'district created march 4 , 1875', 'district created march 4 , 1875', 'district created march 4 , 1875', 'district created march 4 , 1875'], ['john hancock', 'march 4 , 1875', 'march 3 , 1877', 'democrat', 'austin'], ['dewitt clinton giddings', 'march 4 , 1877', 'march 3 , 1879', 'democrat', 'brenham'], ['george washington jones', 'march 4 , 1879', 'march 3 , 1883', 'greenback', 'bastrop'], ['james w throckmorton', 'march 4 , 1883', 'march 3 , 1887', 'democrat', 'mckinney'], ['silas hare', 'march 4 , 1887', 'march 3 , 1891', 'democrat', 'sherman'], ['joseph w bailey', 'march 4 , 1891', 'march 3 , 1901', 'democrat', 'gainesville'], ['choice b randell', 'march 4 , 1901', 'march 3 , 1903', 'democrat', 'sherman'], ['james andrew beall', 'march 4 , 1903', 'march 3 , 1915', 'democrat', 'waxahachie'], ['hatton w sumners', 'march 4 , 1915', 'january 3 , 1947', 'democrat', 'dallas'], ['joseph franklin wilson', 'january 3 , 1947', 'january 3 , 1955', 'democrat', 'dallas'], ['bruce reynolds alger', 'january 3 , 1955', 'january 3 , 1965', 'republican', 'dallas'], ['earle cabell', 'january 3 , 1965', 'january 3 , 1973', 'democrat', 'dallas'], ['alan steelman', 'january 3 , 1973', 'january 3 , 1977', 'republican', 'dallas'], ['jim mattox', 'january 3 , 1977', 'january 3 , 1983', 'democrat', 'dallas'], ['john w bryant', 'january 3 , 1983', 'january 3 , 1997', 'democrat', 'dallas'], ['pete sessions', 'january 3 , 1997', 'january 3 , 2003', 'republican', 'dallas'], ['jeb hensarling', 'january 3 , 2003', 'present', 'republican', 'dallas']] |
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 | majority | the majority of lt & sr 37 class locomotives were withdrawn in the year 1951 . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1951', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'withdrawn', '1951'], 'result': True, 'ind': 0, 'tointer': 'for the withdrawn records of all rows , most of them are equal to 1951 .', 'tostr': 'most_eq { all_rows ; withdrawn ; 1951 } = true'} | most_eq { all_rows ; withdrawn ; 1951 } = true | for the withdrawn records of all rows , most of them are equal to 1951 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'withdrawn_3': 3, '1951_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'withdrawn_3': 'withdrawn', '1951_4': '1951'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'withdrawn_3': [0], '1951_4': [0]} | ['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']] |
usa today all - usa high school baseball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-18.html.csv | count | there were 2 players picked in the 1st round of the 2012 mlb draft on the usa today all-usa high school baseball team . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '1st round', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mlb draft', '1st round'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mlb draft record fuzzily matches to 1st round .', 'tostr': 'filter_eq { all_rows ; mlb draft ; 1st round }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; mlb draft ; 1st round } }', 'tointer': 'select the rows whose mlb draft record fuzzily matches to 1st round . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; mlb draft ; 1st round } } ; 2 } = true', 'tointer': 'select the rows whose mlb draft record fuzzily matches to 1st round . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; mlb draft ; 1st round } } ; 2 } = true | select the rows whose mlb draft record fuzzily matches to 1st round . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'mlb draft_5': 5, '1st round_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'mlb draft_5': 'mlb draft', '1st round_6': '1st round', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'mlb draft_5': [0], '1st round_6': [0], '2_7': [2]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['byron buxton', 'pitcher / outfielder', 'appling county high school', 'baxley , ga', '1st round - 2nd pick of the 2012 draft ( twins )'], ['gavin cecchini', 'infielder', 'barbe high school', 'lake charles , la', '1st round - 12th pick of the 2012 draft ( mets )'], ['james kaprelian', 'pitcher', 'beckman high school', 'irvine , ca', 'attended ucla'], ['rob kaminsky', 'pitcher', 'saint joseph regional high school', 'montvale , nj', 'kaminsky was only a junior'], ['taylor hawkins', 'infielder', 'carl albert high school', 'midwest city , ok', 'attended oklahoma']] |
state assembly elections in india , 2008 | https://en.wikipedia.org/wiki/State_Assembly_elections_in_India%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15329030-1.html.csv | unique | mizoram is the only state with exactly 40 seats in its state assembly . | {'scope': 'all', 'row': '8', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '40', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'seats ( acs )', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose seats ( acs ) record is equal to 40 .', 'tostr': 'filter_eq { all_rows ; seats ( acs ) ; 40 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; seats ( acs ) ; 40 } }', 'tointer': 'select the rows whose seats ( acs ) record is equal to 40 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'seats ( acs )', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose seats ( acs ) record is equal to 40 .', 'tostr': 'filter_eq { all_rows ; seats ( acs ) ; 40 }'}, 'state'], 'result': 'mizoram', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; seats ( acs ) ; 40 } ; state }'}, 'mizoram'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; seats ( acs ) ; 40 } ; state } ; mizoram }', 'tointer': 'the state record of this unqiue row is mizoram .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; seats ( acs ) ; 40 } } ; eq { hop { filter_eq { all_rows ; seats ( acs ) ; 40 } ; state } ; mizoram } } = true', 'tointer': 'select the rows whose seats ( acs ) record is equal to 40 . there is only one such row in the table . the state record of this unqiue row is mizoram .'} | and { only { filter_eq { all_rows ; seats ( acs ) ; 40 } } ; eq { hop { filter_eq { all_rows ; seats ( acs ) ; 40 } ; state } ; mizoram } } = true | select the rows whose seats ( acs ) record is equal to 40 . there is only one such row in the table . the state record of this unqiue row is mizoram . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'seats (acs)_7': 7, '40_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'state_9': 9, 'mizoram_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'seats (acs)_7': 'seats ( acs )', '40_8': '40', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'state_9': 'state', 'mizoram_10': 'mizoram'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'seats (acs)_7': [0], '40_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'state_9': [2], 'mizoram_10': [3]} | ['state', 'seats ( acs )', 'date of counting', 'incumbent', 'election winner'] | [['tripura', '60', 'friday , 7 mar 2008', 'cpi ( m )', 'cpi ( m )'], ['meghalaya', '60', 'friday , 7 mar 2008', 'inc', 'mpa 1'], ['nagaland', '60', 'saturday , 8 march 2008', 'dan', 'dan 2'], ['karnataka', '240', 'sunday , 25 may 2008', 'inc', 'bjp'], ['chhattisgarh', '90', 'monday , 08 dec 2008', 'bjp', 'bjp'], ['madhya pradesh', '230', 'monday , 8 december 2008', 'bjp', 'bjp'], ['delhi', '70', 'monday , 8 december 2008', 'inc', 'inc'], ['mizoram', '40', 'monday , 08 dec 2008', 'mnf', 'inc'], ['rajasthan', '200', 'monday , 8 december 2008', 'bjp', 'inc'], ['jammu and kashmir', '87', 'sunday , 28 december 2008', 'pdp + inc', 'nc + inc']] |
sheffield and hallamshire association cup | https://en.wikipedia.org/wiki/Sheffield_and_Hallamshire_Association_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14909105-1.html.csv | majority | the majority of events took place at the belle vue site in the sheffield and hallamshire association cup from 2002-2013 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'belle vue', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'final venue', 'belle vue'], 'result': True, 'ind': 0, 'tointer': 'for the final venue records of all rows , most of them fuzzily match to belle vue .', 'tostr': 'most_eq { all_rows ; final venue ; belle vue } = true'} | most_eq { all_rows ; final venue ; belle vue } = true | for the final venue records of all rows , most of them fuzzily match to belle vue . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'final venue_3': 3, 'belle vue_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'final venue_3': 'final venue', 'belle vue_4': 'belle vue'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'final venue_3': [0], 'belle vue_4': [0]} | ['season', 'winner', 'result', 'runner - up', 'final venue'] | [['2002 - 03', 'elm tree', '1 - 0', 'stocksbridge park steels reserves', 'belle vue'], ['2003 - 04', 'hsbc', '3 - 2', 'athersley recreation', 'belle vue'], ['2004 - 05', 'kiveton park', '2 - 2', 'athersley recreation', 'sandy lane'], ['2005 - 06', 'kiveton park', '5 - 0', 'sheffield lane top', 'belle vue'], ['2006 - 07', 'stocksbridge park steels reserves', '3 - 1', 'hemsworth miners welfare', 'millmoor'], ['2007 - 08', 'athersley recreation', '1 - 0', 'hollinsend amateurs', 'oakwell'], ['2008 - 09', 'hall green united', '2 - 1', 'kirkburton', 'keepmoat stadium ( pitch 2 )'], ['2009 - 10', 'sheffield reserves', '2 - 1', 'dearne colliery miners welfare', 'inkersall road'], ['2010 - 11', 'stocksbridge park steels reserves', '3 - 0', 'kirkburton', 'green lane'], ['2012 - 13', 'swinton athletic', '3 - 0', 'kirkburton', 'sandy lane']] |
list of government schools in new south wales : q - z | https://en.wikipedia.org/wiki/List_of_Government_schools_in_New_South_Wales%3A_Q%E2%80%93Z | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18155481-6.html.csv | unique | in list of government schools in new south wales : q - z , the only one k-6 in villawood was founded in 1955 . | {'scope': 'subset', 'row': '7', 'col': '2', 'col_other': '4', 'criterion': 'equal', 'value': 'villawood', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'k - 6'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'years', 'k - 6'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; years ; k - 6 }', 'tointer': 'select the rows whose years record fuzzily matches to k - 6 .'}, 'suburb / town', 'villawood'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose years record fuzzily matches to k - 6 . among these rows , select the rows whose suburb / town record fuzzily matches to villawood .', 'tostr': 'filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood } }', 'tointer': 'select the rows whose years record fuzzily matches to k - 6 . among these rows , select the rows whose suburb / town record fuzzily matches to villawood . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'years', 'k - 6'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; years ; k - 6 }', 'tointer': 'select the rows whose years record fuzzily matches to k - 6 .'}, 'suburb / town', 'villawood'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose years record fuzzily matches to k - 6 . among these rows , select the rows whose suburb / town record fuzzily matches to villawood .', 'tostr': 'filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood }'}, 'founded'], 'result': '1955', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood } ; founded }'}, '1955'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood } ; founded } ; 1955 }', 'tointer': 'the founded record of this unqiue row is 1955 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood } } ; eq { hop { filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood } ; founded } ; 1955 } } = true', 'tointer': 'select the rows whose years record fuzzily matches to k - 6 . among these rows , select the rows whose suburb / town record fuzzily matches to villawood . there is only one such row in the table . the founded record of this unqiue row is 1955 .'} | and { only { filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood } } ; eq { hop { filter_eq { filter_eq { all_rows ; years ; k - 6 } ; suburb / town ; villawood } ; founded } ; 1955 } } = true | select the rows whose years record fuzzily matches to k - 6 . among these rows , select the rows whose suburb / town record fuzzily matches to villawood . there is only one such row in the table . the founded record of this unqiue row is 1955 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'years_8': 8, 'k - 6_9': 9, 'suburb / town_10': 10, 'villawood_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'founded_12': 12, '1955_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'years_8': 'years', 'k - 6_9': 'k - 6', 'suburb / town_10': 'suburb / town', 'villawood_11': 'villawood', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'founded_12': 'founded', '1955_13': '1955'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'years_8': [0], 'k - 6_9': [0], 'suburb / town_10': [1], 'villawood_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'founded_12': [3], '1955_13': [4]} | ['school', 'suburb / town', 'years', 'founded', 'website'] | [['vacy public school', 'vacy', 'k - 6', '1859', 'website'], ['valentine public school', 'valentine', 'k - 6', '1958', 'website'], ['valley view public school', 'wyoming', 'k - 6', '1980', 'website'], ['vardys road public school', 'seven hills', 'k - 6', '1960', 'website'], ['vaucluse public school', 'vaucluse', 'k - 6', '1858', 'website'], ['verona school', 'fairfield east', 'k - 6', '1882', 'website'], ['villawood east public school', 'villawood', 'k - 6', '1955', 'website'], ['villawood north public school', 'fairfield east', 'k - 6', '1953', 'website'], ['vincentia high school', 'vincentia', '712', '1993', 'website'], ['vincentia public school', 'vincentia', 'k - 6', '1992', 'website'], ['vineyard public school', 'vineyard', 'k - 6', '1872', 'website']] |
downer edi rail gt46c ace | https://en.wikipedia.org/wiki/Downer_EDI_Rail_GT46C_ACe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17557270-1.html.csv | count | 3 of the trains were at least partially built some time in 2011 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2011', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'built', '2011'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose built record fuzzily matches to 2011 .', 'tostr': 'filter_eq { all_rows ; built ; 2011 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; built ; 2011 } }', 'tointer': 'select the rows whose built record fuzzily matches to 2011 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; built ; 2011 } } ; 3 } = true', 'tointer': 'select the rows whose built record fuzzily matches to 2011 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; built ; 2011 } } ; 3 } = true | select the rows whose built record fuzzily matches to 2011 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'built_5': 5, '2011_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'built_5': 'built', '2011_6': '2011', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'built_5': [0], '2011_6': [0], '3_7': [2]} | ['owner', 'class', 'number in class', 'road numbers', 'built'] | [['sct logistics', 'sct class', '15', 'sct001 - sct015', '2007 - 2008'], ['downer rail', 'ldp class', '9', 'ldp001 - ldp009', '2009'], ['pacific national', 'tt class', '34', 'tt01 - tt08 , tt101 - tt126', '2009 - 2011'], ['whitehaven coal', 'wh class', '3', 'wh001 - wh003', '2011'], ['genesee & wyoming australia', 'gwa class', '10', 'gwa001 - gwa010', '2011 - 2012']] |
2008 - 09 montreal canadiens season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Montreal_Canadiens_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17206737-28.html.csv | count | in the 2008 - 2009 montreal canadiens draft pick , two of the players from the usa were right wings . | {'scope': 'subset', 'criterion': 'equal', 'value': 'rw', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'usa'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'usa'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nationality ; usa }', 'tointer': 'select the rows whose nationality record fuzzily matches to usa .'}, 'position', 'rw'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nationality record fuzzily matches to usa . among these rows , select the rows whose position record fuzzily matches to rw .', 'tostr': 'filter_eq { filter_eq { all_rows ; nationality ; usa } ; position ; rw }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; nationality ; usa } ; position ; rw } }', 'tointer': 'select the rows whose nationality record fuzzily matches to usa . among these rows , select the rows whose position record fuzzily matches to rw . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; nationality ; usa } ; position ; rw } } ; 2 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to usa . among these rows , select the rows whose position record fuzzily matches to rw . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; nationality ; usa } ; position ; rw } } ; 2 } = true | select the rows whose nationality record fuzzily matches to usa . among these rows , select the rows whose position record fuzzily matches to rw . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'nationality_6': 6, 'usa_7': 7, 'position_8': 8, 'rw_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'nationality_6': 'nationality', 'usa_7': 'usa', 'position_8': 'position', 'rw_9': 'rw', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'nationality_6': [0], 'usa_7': [0], 'position_8': [1], 'rw_9': [1], '2_10': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['2', 'danny kristo', 'rw', 'usa', 'us national under - 18 team ( usdp )'], ['3', 'steve quailer', 'rw', 'usa', 'northeastern university ( hockey east )'], ['4', 'jason missiaen', 'g', 'canada', 'peterborough petes ( ohl )'], ['5', 'maxim trunev', 'f', 'russia', 'severstal cherepovets - 2 ( rus3 )'], ['7', 'patrick johnson', 'f', 'usa', 'university of wisconsin ( ncaa )']] |
junior assun \ xc3 \ xa7 \ xc3 \ xa3o | https://en.wikipedia.org/wiki/Junior_Assun%C3%A7%C3%A3o | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17441410-2.html.csv | count | eight of junior assunção 's fights took place in the location of georgia , united states . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'georgia', 'result': '8', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'georgia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to georgia .', 'tostr': 'filter_eq { all_rows ; location ; georgia }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; georgia } }', 'tointer': 'select the rows whose location record fuzzily matches to georgia . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; georgia } } ; 8 } = true', 'tointer': 'select the rows whose location record fuzzily matches to georgia . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; location ; georgia } } ; 8 } = true | select the rows whose location record fuzzily matches to georgia . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'georgia_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'georgia_6': 'georgia', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'georgia_6': [0], '8_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '14 - 5', 'guilherme faria de souza', 'submission ( kimura )', 'premium fight championship 2', '4', '2:05', 'campinas , sao paulo , brazil'], ['loss', '13 - 5', 'ross pearson', 'decision ( unanimous )', 'ufc 141', '3', '5:00', 'las vegas , nevada , united states'], ['win', '13 - 4', 'eddie yagin', 'decision ( unanimous )', 'ufc 135', '3', '5:00', 'denver , colorado , united states'], ['win', '12 - 4', 'wesley murch', 'submission ( rear naked choke )', 'recife fc 4', '1', '5:00', 'recife , brazil'], ['win', '11 - 4', 'mark miller', 'ko ( punch )', 'recife fc 3', '1', '4:03', 'recife , brazil'], ['win', '10 - 4', 'john mahlow', 'submission ( guillotine choke )', 'xfc 10 : night of champions', '1', '4:02', 'florida , united states'], ['win', '9 - 4', 'pete grimes', 'decision ( split )', 'shinefights 2', '3', '5:00', 'florida , united states'], ['win', '8 - 4', 'kamrin naville', 'decision ( unanimous )', 'kotc - invincible', '3', '3:00', 'georgia , united states'], ['win', '7 - 4', 'kalvin hackney', 'decision ( unanimous )', "wild bill 's full throttle", '3', '5:00', 'georgia , united states'], ['loss', '6 - 4', 'torrance taylor', 'decision ( unanimous )', 'afl - bulletproof', '3', '5:00', 'georgia , united states'], ['win', '6 - 3', 'steve sharp', 'submission ( guillotine choke )', 'afl : erupption', '3', '4:26', 'kentucky , united states'], ['loss', '5 - 3', 'nate diaz', 'submission ( guillotine choke )', 'ufc fight night 11', '1', '4:10', 'nevada , united states'], ['win', '5 - 2', 'david lee', 'submission ( rear naked choke )', 'ufc 70', '2', '1:55', 'manchester , england'], ['loss', '4 - 2', 'kurt pellegrino', 'submission ( rear naked choke )', 'ufc 64', '1', '2:04', 'nevada , united states'], ['win', '4 - 1', 'scott hope', 'tko ( punches )', 'iscf - knuckle up 4', '1', '1:43', 'georgia , united states'], ['win', '3 - 1', 'dustin hazelett', 'tko ( punches )', 'ft 3 - full throttle 3', '1', '4:27', 'georgia , united states'], ['win', '2 - 1', 'danny payne', 'submission ( rear naked choke )', 'ft 2 - full throttle 2', '1', '0:50', 'georgia , united states'], ['win', '1 - 1', 'will bradford', 'submission ( guillotine choke )', 'iscf - compound fracture 2', '1', '1:55', 'georgia , united states'], ['loss', '0 - 1', 'andrew chappelle', 'decision ( unanimous )', 'iscf - fight party', '3', '3:00', 'georgia , united states']] |
list of royal pains episodes | https://en.wikipedia.org/wiki/List_of_Royal_Pains_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23117208-3.html.csv | comparative | more people watched the first episode of royal pains than watched the last episode . | {'row_1': '1', 'row_2': '14', 'col': '8', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'no in season', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no in season record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; no in season ; 1 }'}, 'viewers ( millions )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; no in season ; 1 } ; viewers ( millions ) }', 'tointer': 'select the rows whose no in season record fuzzily matches to 1 . take the viewers ( millions ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'no in season', '16'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose no in season record fuzzily matches to 16 .', 'tostr': 'filter_eq { all_rows ; no in season ; 16 }'}, 'viewers ( millions )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; no in season ; 16 } ; viewers ( millions ) }', 'tointer': 'select the rows whose no in season record fuzzily matches to 16 . take the viewers ( millions ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; no in season ; 1 } ; viewers ( millions ) } ; hop { filter_eq { all_rows ; no in season ; 16 } ; viewers ( millions ) } } = true', 'tointer': 'select the rows whose no in season record fuzzily matches to 1 . take the viewers ( millions ) record of this row . select the rows whose no in season record fuzzily matches to 16 . take the viewers ( millions ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; no in season ; 1 } ; viewers ( millions ) } ; hop { filter_eq { all_rows ; no in season ; 16 } ; viewers ( millions ) } } = true | select the rows whose no in season record fuzzily matches to 1 . take the viewers ( millions ) record of this row . select the rows whose no in season record fuzzily matches to 16 . take the viewers ( millions ) record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'no in season_7': 7, '1_8': 8, 'viewers (millions)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'no in season_11': 11, '16_12': 12, 'viewers (millions)_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'no in season_7': 'no in season', '1_8': '1', 'viewers (millions)_9': 'viewers ( millions )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'no in season_11': 'no in season', '16_12': '16', 'viewers (millions)_13': 'viewers ( millions )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'no in season_7': [0], '1_8': [0], 'viewers (millions)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'no in season_11': [1], '16_12': [1], 'viewers (millions)_13': [3]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'prod code', 'viewers ( millions )'] | [['13', '1', 'spasticity', 'constantine makris', 'andrew lenchewski', 'june 3 , 2010', 'rp201', '5.84'], ['14', '2', 'lovesick', 'allison liddi - brown', 'michael rauch', 'june 10 , 2010', 'rp202', '5.60'], ['15', '3', 'keeping the faith', 'dennis smith', 'jack bernstein & michael rauch', 'june 17 , 2010', 'rp203', '5.51'], ['16', '4', 'medusa', 'matthew penn', 'andrew lenchewski & constance m burge', 'june 24 , 2010', 'rp204', '5.30'], ['17', '5', 'mano a mano', 'matthew penn', 'carol flint & jon sherman', 'july 1 , 2010', 'rp205', '5.32'], ['18', '6', 'in vino veritas', 'michael w watkins', 'jessica ball', 'july 15 , 2010', 'rp206', '5.20'], ['19', '7', "comfort 's overrated", 'ed fraiman', 'constance m burge', 'july 22 , 2010', 'rp207', '5.28'], ['20', '8', 'the hankover', 'jay chandrasekhar', 'carol flint & jon sherman', 'july 29 , 2010', 'rp208', '5.01'], ['21', '9', 'frenemies', 'wendey stanzler', 'jack bernstein', 'august 5 , 2010', 'rp209', '5.53'], ['22', '10', 'whole lotto love', 'tawnia mckiernan', 'michael rauch & jessica ball', 'august 12 , 2010', 'rp210', '5.39'], ['23', '11', 'big whoop', 'michael w watkins', 'michael rauch & contance m burge', 'august 19 , 2010', 'rp211', '5.27'], ['24', '12', 'open up your yenta mouth and say ah', 'ken whittingham', 'andrew lenchewski', 'august 26 , 2010', 'rp212', '6.08'], ['25', '13', 'mulligan', 'michael rauch', 'michael rauch & jon sherman', 'january 20 , 2011', 'rp213', '4.43'], ['28', '16', 'astraphobia', 'ed fraiman', 'andrew lenchewski & stuart feldman', 'february 10 , 2011', 'rp216', '3.86']] |
1998 - 99 philadelphia flyers season | https://en.wikipedia.org/wiki/1998%E2%80%9399_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14344807-6.html.csv | comparative | for the 1998-99 philadelphia flyers ' season , the flyers scored more points against their opponents in game 49 as opposed to game 55 . | {'row_1': '2', 'row_2': '8', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game', '49'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game record fuzzily matches to 49 .', 'tostr': 'filter_eq { all_rows ; game ; 49 }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; game ; 49 } ; score }', 'tointer': 'select the rows whose game record fuzzily matches to 49 . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game', '55'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose game record fuzzily matches to 55 .', 'tostr': 'filter_eq { all_rows ; game ; 55 }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; game ; 55 } ; score }', 'tointer': 'select the rows whose game record fuzzily matches to 55 . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; game ; 49 } ; score } ; hop { filter_eq { all_rows ; game ; 55 } ; score } } = true', 'tointer': 'select the rows whose game record fuzzily matches to 49 . take the score record of this row . select the rows whose game record fuzzily matches to 55 . take the score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; game ; 49 } ; score } ; hop { filter_eq { all_rows ; game ; 55 } ; score } } = true | select the rows whose game record fuzzily matches to 49 . take the score record of this row . select the rows whose game record fuzzily matches to 55 . take the score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'game_7': 7, '49_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'game_11': 11, '55_12': 12, 'score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'game_7': 'game', '49_8': '49', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'game_11': 'game', '55_12': '55', 'score_13': 'score'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'game_7': [0], '49_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'game_11': [1], '55_12': [1], 'score_13': [3]} | ['game', 'february', 'opponent', 'score', 'record', 'points'] | [['48', '1', 'los angeles kings', '4 - 2', '27 - 10 - 11', '65'], ['49', '4', 'montreal canadiens', '5 - 2', '28 - 10 - 11', '67'], ['50', '6', 'boston bruins', '2 - 2 ot', '28 - 10 - 12', '68'], ['51', '10', 'mighty ducks of anaheim', '4 - 5', '28 - 11 - 12', '68'], ['52', '11', 'los angeles kings', '3 - 4', '28 - 12 - 12', '68'], ['53', '14', 'colorado avalanche', '4 - 4 ot', '28 - 12 - 13', '69'], ['54', '16', 'phoenix coyotes', '4 - 1', '29 - 12 - 13', '71'], ['55', '18', 'montreal canadiens', '1 - 3', '29 - 13 - 13', '71'], ['56', '20', 'ottawa senators', '1 - 4', '29 - 14 - 13', '71'], ['57', '21', 'pittsburgh penguins', '2 - 1', '30 - 14 - 13', '73'], ['58', '24', 'florida panthers', '3 - 5', '30 - 15 - 13', '73'], ['59', '26', 'tampa bay lightning', '1 - 4', '30 - 16 - 13', '73'], ['60', '28', 'new york rangers', '5 - 6', '30 - 17 - 13', '73']] |
2007 - 08 guildford flames season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Guildford_Flames_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15213262-8.html.csv | majority | for the 2007-08 guildford flames season , when it was a league competition , the majority of the time the venue was away . | {'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'away', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'league'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'league'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competition ; league }', 'tointer': 'select the rows whose competition record fuzzily matches to league .'}, 'venue', 'away'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose competition record fuzzily matches to league . for the venue records of these rows , most of them fuzzily match to away .', 'tostr': 'most_eq { filter_eq { all_rows ; competition ; league } ; venue ; away } = true'} | most_eq { filter_eq { all_rows ; competition ; league } ; venue ; away } = true | select the rows whose competition record fuzzily matches to league . for the venue records of these rows , most of them fuzzily match to away . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'competition_4': 4, 'league_5': 5, 'venue_6': 6, 'away_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'competition_4': 'competition', 'league_5': 'league', 'venue_6': 'venue', 'away_7': 'away'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'competition_4': [0], 'league_5': [0], 'venue_6': [1], 'away_7': [1]} | ['date', 'opponent', 'venue', 'result', 'attendance', 'competition'] | [['3', 'sheffield scimitars', 'away', 'lost 2 - 3 ( so )', '425', 'league'], ['4', 'milton keynes lightning', 'home', 'lost 2 - 5', '1268', 'premier cup'], ['10', 'bracknell bees', 'home', 'lost 2 - 3 ( so )', '1748', 'league'], ['11', 'peterborough phantoms', 'away', 'lost 1 - 2', 'unknown', 'league'], ['17', 'milton keynes lightning', 'away', 'won 4 - 2', '1075', 'league'], ['18', 'wightlink raiders', 'home', 'won 14 - 4', '1636', 'league'], ['24', 'chelmsford chieftains', 'home', 'won 7 - 3', '1238', 'premier cup'], ['25', 'romford raiders', 'away', 'won 5 - 2', 'unknown', 'league']] |
sweeney todd : the demon barber of fleet street | https://en.wikipedia.org/wiki/Sweeney_Todd%3A_The_Demon_Barber_of_Fleet_Street | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1794747-7.html.csv | unique | outstanding featured actor in a musical was the only award that sweeney todd actor alexander gemignani was nominated for . | {'scope': 'all', 'row': '10', 'col': '3', 'col_other': '4', 'criterion': 'equal', 'value': 'outstanding featured actor in a musical', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'outstanding featured actor in a musical'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to outstanding featured actor in a musical .', 'tostr': 'filter_eq { all_rows ; category ; outstanding featured actor in a musical }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; category ; outstanding featured actor in a musical } }', 'tointer': 'select the rows whose category record fuzzily matches to outstanding featured actor in a musical . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'outstanding featured actor in a musical'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to outstanding featured actor in a musical .', 'tostr': 'filter_eq { all_rows ; category ; outstanding featured actor in a musical }'}, 'nominee'], 'result': 'alexander gemignani', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; category ; outstanding featured actor in a musical } ; nominee }'}, 'alexander gemignani'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; category ; outstanding featured actor in a musical } ; nominee } ; alexander gemignani }', 'tointer': 'the nominee record of this unqiue row is alexander gemignani .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; category ; outstanding featured actor in a musical } } ; eq { hop { filter_eq { all_rows ; category ; outstanding featured actor in a musical } ; nominee } ; alexander gemignani } } = true', 'tointer': 'select the rows whose category record fuzzily matches to outstanding featured actor in a musical . there is only one such row in the table . the nominee record of this unqiue row is alexander gemignani .'} | and { only { filter_eq { all_rows ; category ; outstanding featured actor in a musical } } ; eq { hop { filter_eq { all_rows ; category ; outstanding featured actor in a musical } ; nominee } ; alexander gemignani } } = true | select the rows whose category record fuzzily matches to outstanding featured actor in a musical . there is only one such row in the table . the nominee record of this unqiue row is alexander gemignani . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'category_7': 7, 'outstanding featured actor in a musical_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nominee_9': 9, 'alexander gemignani_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'category_7': 'category', 'outstanding featured actor in a musical_8': 'outstanding featured actor in a musical', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nominee_9': 'nominee', 'alexander gemignani_10': 'alexander gemignani'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'category_7': [0], 'outstanding featured actor in a musical_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nominee_9': [2], 'alexander gemignani_10': [3]} | ['year', 'award ceremony', 'category', 'nominee', 'result'] | [['2006', 'tony award', 'best revival of a musical', 'best revival of a musical', 'nominated'], ['2006', 'tony award', 'best performance by a leading actor in a musical', 'michael cerveris', 'nominated'], ['2006', 'tony award', 'best performance by a leading actress in a musical', 'patti lupone', 'nominated'], ['2006', 'tony award', 'best performance by a featured actor in a musical', 'manoel felciano', 'nominated'], ['2006', 'tony award', 'best direction of a musical', 'john doyle', 'won'], ['2006', 'tony award', 'best orchestrations', 'sarah travis', 'won'], ['2006', 'drama desk award', 'outstanding revival of a musical', 'outstanding revival of a musical', 'won'], ['2006', 'drama desk award', 'outstanding actor in a musical', 'michael cerveris', 'nominated'], ['2006', 'drama desk award', 'outstanding actress in a musical', 'patti lupone', 'nominated'], ['2006', 'drama desk award', 'outstanding featured actor in a musical', 'alexander gemignani', 'nominated'], ['2006', 'drama desk award', 'outstanding orchestrations', 'sarah travis', 'won'], ['2006', 'drama desk award', 'outstanding director of a musical', 'john doyle', 'won'], ['2006', 'drama desk award', 'outstanding set design', 'john doyle', 'nominated'], ['2006', 'drama desk award', 'outstanding lighting design', 'richard g jones', 'won'], ['2006', 'drama desk award', 'outstanding sound design', 'dan moses schreier', 'nominated']] |
paul di resta | https://en.wikipedia.org/wiki/Paul_di_Resta | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1746765-1.html.csv | aggregation | paul di resta took part in a total of 198 races during his racing career . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '198', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'races'], 'result': '198', 'ind': 0, 'tostr': 'sum { all_rows ; races }'}, '198'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; races } ; 198 } = true', 'tointer': 'the sum of the races record of all rows is 198 .'} | round_eq { sum { all_rows ; races } ; 198 } = true | the sum of the races record of all rows is 198 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'races_4': 4, '198_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'races_4': 'races', '198_5': '198'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'races_4': [0], '198_5': [1]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2003', 'formula renault uk', 'eurotek motorsport', '17', '1', '2', '1', '2', '233', '7th'], ['2003', 'formula renault uk', 'team jva', '17', '1', '2', '1', '2', '233', '7th'], ['2004', 'formula renault uk', 'manor motorsport', '20', '4', '4', '2', '9', '415', '3rd'], ['2004', 'formula renault 2000 eurocup', 'manor motorsport', '3', '0', '0', '0', '1', '0', 'nc'], ['2004', 'bahrain superprix', 'manor motorsport', '1', '0', '0', '0', '0', 'n / a', 'nc'], ['2005', 'formula 3 euro series', 'manor motorsport', '19', '0', '3', '2', '1', '32', '10th'], ['2005', 'masters of formula 3', 'manor motorsport', '1', '0', '0', '0', '0', 'n / a', '4th'], ['2006', 'formula 3 euro series', 'asm formule 3', '20', '5', '5', '1', '9', '86', '1st'], ['2006', 'masters of formula 3', 'asm formule 3', '1', '1', '0', '0', '0', 'n / a', '1st'], ['2006', 'macau grand prix', 'asm formule 3', '1', '0', '0', '0', '0', 'n / a', 'nc'], ['2007', 'deutsche tourenwagen masters', 'persson motorsport', '10', '0', '0', '0', '4', '32', '5th'], ['2008', 'deutsche tourenwagen masters', 'hwa team', '11', '2', '1', '4', '7', '71', '2nd'], ['2009', 'deutsche tourenwagen masters', 'hwa team', '10', '1', '1', '2', '3', '45', '3rd'], ['2010', 'deutsche tourenwagen masters', 'hwa team', '11', '3', '3', '1', '7', '71', '1st'], ['2010', 'formula one', 'force india f1 team', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver'], ['2011', 'formula one', 'force india f1 team', '19', '0', '0', '0', '0', '27', '13th'], ['2012', 'formula one', 'sahara force india f1 team', '20', '0', '0', '0', '0', '46', '14th'], ['2013', 'formula one', 'sahara force india f1 team', '17', '0', '0', '0', '0', '48', '10th']] |
adam lambert | https://en.wikipedia.org/wiki/Adam_Lambert | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21501511-1.html.csv | majority | for adam lambert the result in most of the weeks was that he was safe . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'safe', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'safe'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to safe .', 'tostr': 'most_eq { all_rows ; result ; safe } = true'} | most_eq { all_rows ; result ; safe } = true | for the result records of all rows , most of them fuzzily match to safe . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'safe_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'safe_4': 'safe'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'safe_4': [0]} | ['week', 'theme', 'song choice', 'original artist', 'order', 'result'] | [['audition', "auditioner 's choice", 'rock with you bohemian rhapsody', 'michael jackson queen', 'n / a', 'advanced'], ['hollywood', 'first solo', "what 's up", '4 non blondes', 'n / a', 'advanced'], ['hollywood', 'group performance', 'some kind of wonderful', 'soul brothers six', 'n / a', 'advanced'], ['hollywood', 'second solo', 'believe', 'cher', 'n / a', 'advanced'], ['top 36 / semi - final 2', 'billboard hot 100 hits to date', "( i ca n't get no ) satisfaction", 'the rolling stones', '12', 'advanced'], ['top 13', 'michael jackson', 'black or white', 'michael jackson', '11', 'safe'], ['top 11', 'grand ole opry', 'ring of fire', 'anita carter', '5', 'safe'], ['top 10', 'motown', 'the tracks of my tears', 'the miracles', '8', 'safe'], ['top 9', 'top downloads', 'play that funky music', 'wild cherry', '8', 'safe'], ['top 8', 'year they were born ( 1982 )', 'mad world', 'tears for fears', '8', 'safe'], ['top 7', 'songs from the cinema', 'born to be wild easy rider', 'steppenwolf', '3', 'safe'], ['top 7', 'disco', "if i ca n't have you", 'yvonne elliman', '5', 'safe']] |
indiana high school athletics conferences : allen county - metropolitan | https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Allen_County_%E2%80%93_Metropolitan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13986492-13.html.csv | unique | yorktown was the only school who had the tiger as its mascot . | {'scope': 'all', 'row': '8', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'tigers', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mascot', 'tigers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mascot record fuzzily matches to tigers .', 'tostr': 'filter_eq { all_rows ; mascot ; tigers }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; mascot ; tigers } }', 'tointer': 'select the rows whose mascot record fuzzily matches to tigers . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mascot', 'tigers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mascot record fuzzily matches to tigers .', 'tostr': 'filter_eq { all_rows ; mascot ; tigers }'}, 'school'], 'result': 'yorktown', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; mascot ; tigers } ; school }'}, 'yorktown'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; mascot ; tigers } ; school } ; yorktown }', 'tointer': 'the school record of this unqiue row is yorktown .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; mascot ; tigers } } ; eq { hop { filter_eq { all_rows ; mascot ; tigers } ; school } ; yorktown } } = true', 'tointer': 'select the rows whose mascot record fuzzily matches to tigers . there is only one such row in the table . the school record of this unqiue row is yorktown .'} | and { only { filter_eq { all_rows ; mascot ; tigers } } ; eq { hop { filter_eq { all_rows ; mascot ; tigers } ; school } ; yorktown } } = true | select the rows whose mascot record fuzzily matches to tigers . there is only one such row in the table . the school record of this unqiue row is yorktown . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'mascot_7': 7, 'tigers_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'school_9': 9, 'yorktown_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'mascot_7': 'mascot', 'tigers_8': 'tigers', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'school_9': 'school', 'yorktown_10': 'yorktown'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'mascot_7': [0], 'tigers_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'school_9': [2], 'yorktown_10': [3]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'ihsaa football class', 'county'] | [['muncie delta', 'muncie', 'eagles', '863', 'aaa', 'aaaa', '18 delaware'], ['greenfield central', 'greenfield', 'cougars', '1410', 'aaaa', 'aaaa', '30 hancock'], ['mount vernon fortville', 'fortville', 'marauders', '1077', 'aaa', 'aaaa', '30 hancock'], ['new palestine', 'new palestine', 'dragons', '1092', 'aaaa', 'aaaa', '30 hancock'], ['pendleton heights', 'pendleton', 'arabians', '1235', 'aaaa', 'aaaa', '48 madison'], ['rushville consolidated', 'rushville', 'lions', '815', 'aaa', 'aaa', '70 rush'], ['shelbyville', 'shelbyville', 'golden bears', '1153', 'aaaa', 'aaaa', '73 shelby'], ['yorktown', 'yorktown', 'tigers', '755', 'aaa', 'aaa', '18 delaware']] |
usa today all - usa high school baseball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-4.html.csv | unique | the only outfielder on the usa today all-usa team was chip ambres . | {'scope': 'all', 'row': '8', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'outfielder', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'outfielder'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to outfielder .', 'tostr': 'filter_eq { all_rows ; position ; outfielder }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; outfielder } }', 'tointer': 'select the rows whose position record fuzzily matches to outfielder . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'outfielder'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to outfielder .', 'tostr': 'filter_eq { all_rows ; position ; outfielder }'}, 'player'], 'result': 'chip ambres', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; outfielder } ; player }'}, 'chip ambres'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; outfielder } ; player } ; chip ambres }', 'tointer': 'the player record of this unqiue row is chip ambres .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; outfielder } } ; eq { hop { filter_eq { all_rows ; position ; outfielder } ; player } ; chip ambres } } = true', 'tointer': 'select the rows whose position record fuzzily matches to outfielder . there is only one such row in the table . the player record of this unqiue row is chip ambres .'} | and { only { filter_eq { all_rows ; position ; outfielder } } ; eq { hop { filter_eq { all_rows ; position ; outfielder } ; player } ; chip ambres } } = true | select the rows whose position record fuzzily matches to outfielder . there is only one such row in the table . the player record of this unqiue row is chip ambres . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'outfielder_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'chip ambres_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'outfielder_8': 'outfielder', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'chip ambres_10': 'chip ambres'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'outfielder_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'chip ambres_10': [3]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['drew henson', 'infielder', 'brighton high school', 'brighton , mi', '3rd round - 97th pick of 1998 draft ( yankees )'], ['josh beckett', 'pitcher', 'spring high school', 'spring , tx', 'beckett was a junior in the 1998 season'], ['j m gold', 'pitcher', 'toms river high school north', 'toms river , nj', '1st round - 13th pick of 1998 draft ( brewers )'], ['gerald laird', 'catcher', 'la quinta high school', 'westminster , ca', "2nd round - 45th pick of 1998 draft ( a 's )"], ['sean burroughs', 'infielder', 'wilson high school', 'long beach , ca', '1st round - 9th pick of 1998 draft ( padres )'], ['felipe lã cubicpez', 'infielder', 'lake brantley high school', 'altamonte springs , fl', '1st round - 8th pick of 1998 draft ( blue jays )'], ['mark teixeira', 'infielder', 'mount saint joseph high school', 'baltimore , md', 'attended georgia tech'], ['chip ambres', 'outfielder', 'west brook senior high school', 'beaumont , tx', '1st round - 27th pick of 1998 draft ( marlins )']] |
miami dade college | https://en.wikipedia.org/wiki/Miami_Dade_College | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1860065-2.html.csv | ordinal | the kendall campus of the miami dade college is the second largest in area size . | {'row': '4', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'size', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; size ; 2 }'}, 'campus'], 'result': 'kendall campus', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; size ; 2 } ; campus }'}, 'kendall campus'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; size ; 2 } ; campus } ; kendall campus } = true', 'tointer': 'select the row whose size record of all rows is 2nd maximum . the campus record of this row is kendall campus .'} | eq { hop { nth_argmax { all_rows ; size ; 2 } ; campus } ; kendall campus } = true | select the row whose size record of all rows is 2nd maximum . the campus record of this row is kendall campus . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'size_5': 5, '2_6': 6, 'campus_7': 7, 'kendall campus_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', 'size_5': 'size', '2_6': '2', 'campus_7': 'campus', 'kendall campus_8': 'kendall campus'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'size_5': [0], '2_6': [0], 'campus_7': [1], 'kendall campus_8': [2]} | ['campus', 'year opened', 'students', 'size', 'location'] | [['hialeah campus', '1980 2005 ( official designation )', 'na', '8 acres', 'hialeah'], ['homestead campus', '1990', 'na', '18 acres', 'downtown homestead'], ['interamerican campus', '1986 2001 ( official designation )', '6500', '4 acres', 'little havana , miami'], ['kendall campus', '1967', '66500', '185 acres', 'kendall , miami'], ['medical campus', '1977', 'na', '4.3 acres', 'civic center , miami'], ['north campus', '1960', '41000', '245 acres', 'westview , miami'], ['west campus', '2005', 'na', '10 acres', 'doral , miami'], ['wolfson campus ( main campus )', '1970', '27000', '15 acres', 'downtown miami']] |
united states house of representatives elections , 1940 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1940 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342270-43.html.csv | count | there are 15 incumbents that were re - elected in the 1940 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '15', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; result ; re - elected }'}], 'result': '15', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re - elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 15 .'}, '15'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re - elected } } ; 15 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 15 .'} | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 15 } = true | select the rows whose result record fuzzily matches to re - elected . the number of such rows is 15 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're - elected_6': 6, '15_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're - elected_6': 're - elected', '15_7': '15'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '15_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) unopposed'], ['texas 2', 'martin dies , jr', 'democratic', '1930', 're - elected', 'martin dies , jr ( d ) unopposed'], ['texas 3', 'lindley beckworth', 'democratic', '1938', 're - elected', 'lindley beckworth ( d ) unopposed'], ['texas 4', 'sam rayburn', 'democratic', '1912', 're - elected', 'sam rayburn ( d ) unopposed'], ['texas 6', 'luther a johnson', 'democratic', '1922', 're - elected', 'luther a johnson ( d ) unopposed'], ['texas 7', 'nat patton', 'democratic', '1934', 're - elected', 'nat patton ( d ) 98.2 % dudley lawson ( r ) 1.8 %'], ['texas 9', 'joseph j mansfield', 'democratic', '1916', 're - elected', 'joseph j mansfield ( d ) unopposed'], ['texas 10', 'lyndon b johnson', 'democratic', '1937', 're - elected', 'lyndon b johnson ( d ) unopposed'], ['texas 11', 'william r poage', 'democratic', '1936', 're - elected', 'william r poage ( d ) unopposed'], ['texas 12', 'fritz g lanham', 'democratic', '1919', 're - elected', 'fritz g lanham ( d ) unopposed'], ['texas 13', 'ed gossett', 'democratic', '1938', 're - elected', 'ed gossett ( d ) 96.4 % louis n gould ( r ) 3.6 %'], ['texas 14', 'richard m kleberg', 'democratic', '1931', 're - elected', 'richard m kleberg ( d ) unopposed'], ['texas 15', 'milton h west', 'democratic', '1933', 're - elected', 'milton h west ( d ) 92.4 % j a simpson ( r ) 7.6 %'], ['texas 16', 'r ewing thomason', 'democratic', '1930', 're - elected', 'r ewing thomason ( d ) unopposed'], ['texas 17', 'clyde l garrett', 'democratic', '1936', 'lost renomination democratic hold', 'sam m russell ( d ) unopposed'], ['texas 19', 'george h mahon', 'democratic', '1934', 're - elected', 'george h mahon ( d ) unopposed']] |
list of lancashire county cricket club records | https://en.wikipedia.org/wiki/List_of_Lancashire_County_Cricket_Club_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14176339-7.html.csv | ordinal | 1985 is the 4th earliest year in which a lancashire county cricked record was recorded . | {'row': '4', 'col': '5', 'order': '4', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'year', '4'], 'result': '1985', 'ind': 0, 'tostr': 'nth_min { all_rows ; year ; 4 }', 'tointer': 'the 4th minimum year record of all rows is 1985 .'}, '1985'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; year ; 4 } ; 1985 } = true', 'tointer': 'the 4th minimum year record of all rows is 1985 .'} | eq { nth_min { all_rows ; year ; 4 } ; 1985 } = true | the 4th minimum year record of all rows is 1985 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'year_4': 4, '4_5': 5, '1985_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'year_4': 'year', '4_5': '4', '1985_6': '1985'} | {'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'year_4': [0], '4_5': [0], '1985_6': [1]} | ['score', 'opposition', 'venue', 'city', 'year'] | [['423 runs', 'somerset', 'aigurth', 'liverpool', '1911'], ['385 runs', 'somerset', 'aigburth', 'liverpool', '1908'], ['372 runs', 'worcestershire', 'amblecote', 'stourbridge', '1911'], ['370 runs', 'oxford university', 'the university parks', 'oxford', '1985'], ['361 runs', 'middlesex', 'old trafford', 'manchester', '1994'], ['350 runs', 'durham', 'riverside ground', 'chester - le - street', '1998'], ['345 runs', 'durham', 'riverside ground', 'chester - le - street', '1996'], ['336 runs', 'somerset', 'stanley park', 'blackpool', '2002']] |
list of how it 's made episodes | https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15187735-9.html.csv | unique | the only time how it 's made featured cheesecake in the ninth season was in the first episode . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'cheesecake', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment b', 'cheesecake'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment b record fuzzily matches to cheesecake .', 'tostr': 'filter_eq { all_rows ; segment b ; cheesecake }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; segment b ; cheesecake } }', 'tointer': 'select the rows whose segment b record fuzzily matches to cheesecake . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment b', 'cheesecake'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment b record fuzzily matches to cheesecake .', 'tostr': 'filter_eq { all_rows ; segment b ; cheesecake }'}, 'series ep'], 'result': '9 - 01', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; segment b ; cheesecake } ; series ep }'}, '9 - 01'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; segment b ; cheesecake } ; series ep } ; 9 - 01 }', 'tointer': 'the series ep record of this unqiue row is 9 - 01 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; segment b ; cheesecake } } ; eq { hop { filter_eq { all_rows ; segment b ; cheesecake } ; series ep } ; 9 - 01 } } = true', 'tointer': 'select the rows whose segment b record fuzzily matches to cheesecake . there is only one such row in the table . the series ep record of this unqiue row is 9 - 01 .'} | and { only { filter_eq { all_rows ; segment b ; cheesecake } } ; eq { hop { filter_eq { all_rows ; segment b ; cheesecake } ; series ep } ; 9 - 01 } } = true | select the rows whose segment b record fuzzily matches to cheesecake . there is only one such row in the table . the series ep record of this unqiue row is 9 - 01 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'segment b_7': 7, 'cheesecake_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'series ep_9': 9, '9 - 01_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'segment b_7': 'segment b', 'cheesecake_8': 'cheesecake', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'series ep_9': 'series ep', '9 - 01_10': '9 - 01'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'segment b_7': [0], 'cheesecake_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'series ep_9': [2], '9 - 01_10': [3]} | ['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d'] | [['9 - 01', '105', 's05e01', 'solid tires', 'cheesecake', 'canoe paddles', 's globe'], ['9 - 02', '106', 's05e02', 'boomerangs', 'barbecues', 'pinball machines', 'strobe lights'], ['9 - 03', '107', 's05e03', 'wooden bowls', 'chainsaws', 'stackable potato chips', 'jet compressor blades'], ['9 - 04', '108', 's05e04', 'steel wool', 'ranges', 'carved candles', 'slot machines'], ['9 - 05', '109', 's05e05', 'ccd semiconductors', 'airline meals', 'paper cups', 's trumpet'], ['9 - 06', '110', 's05e06', 's padlock', 'hair clippers', 'wooden shoes', 'synthetic leather'], ['9 - 07', '111', 's05e07', 'racing shells', 'stainless steel sinks', 'leather', 'pedal steel guitars'], ['9 - 08', '112', 's05e08', 'swords', 'pontoons', 'grandfather clocks', 'fuses'], ['9 - 09', '113', 's05e09', 'bumpers', 'lighting gels & camera filters', 'steam - powered models', 'candy canes'], ['9 - 10', '114', 's05e10', 'umbrellas', 'outboard motors', 'silver cutlery', 'tape measures'], ['9 - 11', '115', 's05e11', 'scalpels', 'oil paint', 'british police helmets', 'ice axes'], ['9 - 12', '116', 's05e12', 'bacon', 's snowblower', 'luxury cars ( part 1 )', 'luxury cars ( part 2 )']] |
special cities of japan | https://en.wikipedia.org/wiki/Special_cities_of_Japan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1585609-2.html.csv | count | two of the special cities of japan belong to the kansai region . | {'scope': 'all', 'criterion': 'equal', 'value': 'kansai', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'kansai'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose region record fuzzily matches to kansai .', 'tostr': 'filter_eq { all_rows ; region ; kansai }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; region ; kansai } }', 'tointer': 'select the rows whose region record fuzzily matches to kansai . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; region ; kansai } } ; 2 } = true', 'tointer': 'select the rows whose region record fuzzily matches to kansai . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; region ; kansai } } ; 2 } = true | select the rows whose region record fuzzily matches to kansai . 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, 'region_5': 5, 'kansai_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', 'region_5': 'region', 'kansai_6': 'kansai', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'region_5': [0], 'kansai_6': [0], '2_7': [2]} | ['name', 'japanese', 'date of designation', 'date of reclassification', 'region', 'prefecture'] | [['hakodate', '函館', '2000 - 11 - 01', '2005 - 10 - 01 ( core city )', 'hokkaido', 'hokkaido'], ['shimizu', '清水', '2001 - 04 - 01', '2003 - 04 - 01 ( merge into shizuoka )', 'chūbu', 'shizuoka'], ['shimonoseki', '下関', '2002 - 04 - 01', '2005 - 02 - 12 ( core city )', 'chūgoku', 'yamaguchi'], ['morioka', '盛岡', '2000 - 11 - 01', '2008 - 04 - 01 ( core city )', 'tōhoku', 'iwate'], ['kurume', '久留米', '2001 - 04 - 01', '2008 - 04 - 01 ( core city )', 'kyushu', 'fukuoka'], ['maebashi', '前橋', '2001 - 04 - 01', '2009 - 04 - 01 ( core city )', 'kantō', 'gunma'], ['ōtsu', '大津', '2001 - 04 - 01', '2009 - 04 - 01 ( core city )', 'kansai', 'shiga'], ['amagasaki', '尼崎', '2001 - 04 - 01', '2009 - 04 - 01 ( core city )', 'kansai', 'hyōgo'], ['takasaki', '高崎', '2001 - 04 - 01', '2011 - 04 - 01 ( core city )', 'kantō', 'gunma']] |
1927 vfl season | https://en.wikipedia.org/wiki/1927_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10747009-9.html.csv | superlative | the highest away team score during this round of the 1927 vfl season was 15.9 ( 99 ) . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'away team score'], 'result': '15.9 ( 99 )', 'ind': 0, 'tostr': 'max { all_rows ; away team score }', 'tointer': 'the maximum away team score record of all rows is 15.9 ( 99 ) .'}, '15.9 ( 99 )'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; away team score } ; 15.9 ( 99 ) } = true', 'tointer': 'the maximum away team score record of all rows is 15.9 ( 99 ) .'} | eq { max { all_rows ; away team score } ; 15.9 ( 99 ) } = true | the maximum away team score record of all rows is 15.9 ( 99 ) . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'away team score_4': 4, '15.9 (99)_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'away team score_4': 'away team score', '15.9 (99)_5': '15.9 ( 99 )'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'away team score_4': [0], '15.9 (99)_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '9.6 ( 60 )', 'richmond', '9.20 ( 74 )', 'glenferrie oval', '10000', '25 june 1927'], ['essendon', '12.12 ( 84 )', 'south melbourne', '15.9 ( 99 )', 'windy hill', '17000', '25 june 1927'], ['st kilda', '15.7 ( 97 )', 'north melbourne', '13.10 ( 88 )', 'junction oval', '13000', '25 june 1927'], ['melbourne', '10.13 ( 73 )', 'footscray', '7.9 ( 51 )', 'mcg', '15171', '25 june 1927'], ['geelong', '12.15 ( 87 )', 'fitzroy', '12.8 ( 80 )', 'corio oval', '13500', '25 june 1927'], ['collingwood', '13.5 ( 83 )', 'carlton', '14.11 ( 95 )', 'victoria park', '33000', '25 june 1927']] |
1980 los angeles rams season | https://en.wikipedia.org/wiki/1980_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11157290-2.html.csv | ordinal | in the 1980 los angeles rams season , the 3rd game played in october was a win against the san francisco 49ers . | {'scope': 'subset', 'row': '7', 'col': '1', 'order': '3', 'col_other': '3,4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'week', '3'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 }'}, 'opponent'], 'result': 'san francisco 49ers', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 } ; opponent }'}, 'san francisco 49ers'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 } ; opponent } ; san francisco 49ers }', 'tointer': 'select the rows whose date record fuzzily matches to october . select the row whose week record of these rows is 3rd minimum . the opponent record of this row is san francisco 49ers .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'week', '3'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 }'}, 'result'], 'result': 'w 31 - 17', 'ind': 4, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 } ; result }'}, 'w 31 - 17'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 } ; result } ; w 31 - 17 }', 'tointer': 'the result record of this row is w 31 - 17 .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 } ; opponent } ; san francisco 49ers } ; eq { hop { nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 } ; result } ; w 31 - 17 } } = true', 'tointer': 'select the rows whose date record fuzzily matches to october . select the row whose week record of these rows is 3rd minimum . the opponent record of this row is san francisco 49ers . the result record of this row is w 31 - 17 .'} | and { eq { hop { nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 } ; opponent } ; san francisco 49ers } ; eq { hop { nth_argmin { filter_eq { all_rows ; date ; october } ; week ; 3 } ; result } ; w 31 - 17 } } = true | select the rows whose date record fuzzily matches to october . select the row whose week record of these rows is 3rd minimum . the opponent record of this row is san francisco 49ers . the result record of this row is w 31 - 17 . | 9 | 7 | {'and_6': 6, 'result_7': 7, 'str_eq_3': 3, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_8': 8, 'date_9': 9, 'october_10': 10, 'week_11': 11, '3_12': 12, 'opponent_13': 13, 'san francisco 49ers_14': 14, 'str_eq_5': 5, 'str_hop_4': 4, 'result_15': 15, 'w 31 - 17_16': 16} | {'and_6': 'and', 'result_7': 'true', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_8': 'all_rows', 'date_9': 'date', 'october_10': 'october', 'week_11': 'week', '3_12': '3', 'opponent_13': 'opponent', 'san francisco 49ers_14': 'san francisco 49ers', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'result_15': 'result', 'w 31 - 17_16': 'w 31 - 17'} | {'and_6': [7], 'result_7': [], 'str_eq_3': [6], 'str_hop_2': [3], 'nth_argmin_1': [2, 4], 'filter_str_eq_0': [1], 'all_rows_8': [0], 'date_9': [0], 'october_10': [0], 'week_11': [1], '3_12': [1], 'opponent_13': [2], 'san francisco 49ers_14': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'result_15': [4], 'w 31 - 17_16': [5]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 7 , 1980', 'detroit lions', 'l 41 - 20', '64892'], ['2', 'september 11 , 1980', 'tampa bay buccaneers', 'l 10 - 9', '66576'], ['3', 'september 21 , 1980', 'green bay packers', 'w 51 - 21', '63850'], ['4', 'september 28 , 1980', 'new york giants', 'w 28 - 7', '73414'], ['5', 'october 5 , 1980', 'san francisco 49ers', 'w 48 - 26', '62188'], ['6', 'october 12 , 1980', 'st louis cardinals', 'w 21 - 13', '50230'], ['7', 'october 19 , 1980', 'san francisco 49ers', 'w 31 - 17', '55360'], ['8', 'october 26 , 1980', 'atlanta falcons', 'l 13 - 10', '57401'], ['9', 'november 2 , 1980', 'new orleans saints', 'w 45 - 31', '59909'], ['10', 'november 9 , 1980', 'miami dolphins', 'l 35 - 14', '62198'], ['11', 'november 16 , 1980', 'new england patriots', 'w 17 - 14', '60609'], ['12', 'november 24 , 1980', 'new orleans saints', 'w 27 - 7', '53448'], ['13', 'november 30 , 1980', 'new york jets', 'w 38 - 13', '59743'], ['14', 'december 7 , 1980', 'buffalo bills', 'l 10 - 7 ( ot )', '77133'], ['15', 'december 15 , 1980', 'dallas cowboys', 'w 38 - 14', '65154'], ['16', 'december 21 , 1980', 'atlanta falcons', 'w 20 - 17 ( ot )', '62469']] |
95th united states congress | https://en.wikipedia.org/wiki/95th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1013168-3.html.csv | comparative | bob livingston was seated as a successor earlier than robert garcia in the 95th united states congress . | {'row_1': '1', 'row_2': '2', 'col': '5', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'bob livingston ( r )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to bob livingston ( r ) .', 'tostr': 'filter_eq { all_rows ; successor ; bob livingston ( r ) }'}, 'date successor seated'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; successor ; bob livingston ( r ) } ; date successor seated }', 'tointer': 'select the rows whose successor record fuzzily matches to bob livingston ( r ) . take the date successor seated record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'robert garcía ( d )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose successor record fuzzily matches to robert garcía ( d ) .', 'tostr': 'filter_eq { all_rows ; successor ; robert garcía ( d ) }'}, 'date successor seated'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; successor ; robert garcía ( d ) } ; date successor seated }', 'tointer': 'select the rows whose successor record fuzzily matches to robert garcía ( d ) . take the date successor seated record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; successor ; bob livingston ( r ) } ; date successor seated } ; hop { filter_eq { all_rows ; successor ; robert garcía ( d ) } ; date successor seated } } = true', 'tointer': 'select the rows whose successor record fuzzily matches to bob livingston ( r ) . take the date successor seated record of this row . select the rows whose successor record fuzzily matches to robert garcía ( d ) . take the date successor seated record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; successor ; bob livingston ( r ) } ; date successor seated } ; hop { filter_eq { all_rows ; successor ; robert garcía ( d ) } ; date successor seated } } = true | select the rows whose successor record fuzzily matches to bob livingston ( r ) . take the date successor seated record of this row . select the rows whose successor record fuzzily matches to robert garcía ( d ) . take the date successor seated 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, 'successor_7': 7, 'bob livingston (r)_8': 8, 'date successor seated_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'successor_11': 11, 'robert garcía (d)_12': 12, 'date successor seated_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', 'successor_7': 'successor', 'bob livingston (r)_8': 'bob livingston ( r )', 'date successor seated_9': 'date successor seated', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'successor_11': 'successor', 'robert garcía (d)_12': 'robert garcía ( d )', 'date successor seated_13': 'date successor seated'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'successor_7': [0], 'bob livingston (r)_8': [0], 'date successor seated_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'successor_11': [1], 'robert garcía (d)_12': [1], 'date successor seated_13': [3]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['louisiana 1st', 'richard a tonry ( d )', 'forced to resign may 4 , 1977', 'bob livingston ( r )', 'august 27 , 1977'], ['new york 21st', 'robert garcía ( r - l )', 'changed parties february 21 , 1978', 'robert garcía ( d )', 'february 21 , 1978'], ['tennessee 5th', 'clifford allen ( d )', 'died june 18 , 1978', 'vacant', 'not filled this term'], ['california 18th', 'william m ketchum ( r )', 'died june 24 , 1978', 'vacant', 'not filled this term'], ['illinois 1st', 'ralph metcalfe ( d )', 'died october 10 , 1978', 'vacant', 'not filled this term'], ['maryland 6th', 'goodloe byron ( d )', 'died october 11 , 1978', 'vacant', 'not filled this term'], ['wisconsin 6th', 'william a steiger ( r )', 'died december 4 , 1978', 'vacant', 'not filled this term'], ['wyoming at - large', 'teno roncalio ( d )', 'resigned december 30 , 1978', 'vacant', 'not filled this term'], ['california 3rd', 'john e moss ( d )', 'resigned december 31 , 1978', 'vacant', 'not filled this term'], ['california 14th', 'john j mcfall ( d )', 'resigned december 31 , 1978', 'vacant', 'not filled this term'], ['california 33rd', 'del m clawson ( r )', 'resigned december 31 , 1978', 'vacant', 'not filled this term'], ['kansas 5th', 'joe skubitz ( r )', 'resigned december 31 , 1978', 'vacant', 'not filled this term'], ['michigan 10th', 'elford a cederberg ( r )', 'resigned december 31 , 1978', 'vacant', 'not filled this term'], ['new jersey 14th', 'joseph a lefante ( d )', 'resigned december 31 , 1978', 'vacant', 'not filled this term'], ['new york 9th', 'james delaney ( d )', 'resigned december 31 , 1978', 'vacant', 'not filled this term'], ['texas 6th', 'olin e teague ( d )', 'resigned december 31 , 1978', 'vacant', 'not filled this term'], ['texas 11th', 'william r poage ( d )', 'resigned december 31 , 1978', 'vacant', 'not filled this term']] |
2010 f \ xc3 \ xb3rmula truck season | https://en.wikipedia.org/wiki/2010_F%C3%B3rmula_Truck_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29361707-2.html.csv | count | roberval andrade was the winning driver 4 times in the 2010 formula truck season . | {'scope': 'all', 'criterion': 'equal', 'value': 'roberval andrade', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning driver', 'roberval andrade'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning driver record fuzzily matches to roberval andrade .', 'tostr': 'filter_eq { all_rows ; winning driver ; roberval andrade }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; winning driver ; roberval andrade } }', 'tointer': 'select the rows whose winning driver record fuzzily matches to roberval andrade . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; winning driver ; roberval andrade } } ; 4 } = true', 'tointer': 'select the rows whose winning driver record fuzzily matches to roberval andrade . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; winning driver ; roberval andrade } } ; 4 } = true | select the rows whose winning driver record fuzzily matches to roberval andrade . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'winning driver_5': 5, 'roberval andrade_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'winning driver_5': 'winning driver', 'roberval andrade_6': 'roberval andrade', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winning driver_5': [0], 'roberval andrade_6': [0], '4_7': [2]} | ['round', 'circuit', 'date', 'pole position', 'fastest lap', 'winning driver', 'winning team'] | [['1', 'autódromo internacional de guaporé', 'march 7', 'roberval andrade', 'felipe giaffone', 'felipe giaffone', 'rm competições'], ['2', 'autódromo internacional nelson piquet', 'april 18', 'danilo dirani', 'danilo dirani', 'roberval andrade', 'rvr corinthians motorsport'], ['3', 'autódromo ayrton senna , caruaru', 'may 16', 'valmir benavides', 'valmir benavides', 'valmir benavides', 'rm competições'], ['4', 'autódromo internacional orlando moura', 'june 26', 'leandro reis', 'roberval andrade', 'wellington cirino', 'abf mercedes - benz'], ['5', 'autódromo josé carlos pace', 'july 25', 'roberval andrade', 'leandro reis', 'roberval andrade', 'rvr corinthians motorsport'], ['6', 'autódromo internacional ayrton senna', 'august 22', 'danilo dirani', 'felipe giaffone', 'roberval andrade', 'rvr corinthians motorsport'], ['7', 'autódromo juan y oscar gálvez', 'september 19', 'roberval andrade', 'valmir benavides', 'geraldo piquet', 'abf mercedes - benz'], ['8', 'velopark , nova santa rita', 'october 10', 'beto monteiro', 'roberval andrade', 'beto monteiro', 'scuderia iveco'], ['9', 'autódromo internacional de curitiba', 'november 14', 'roberval andrade', 'felipe giaffone', 'roberval andrade', 'rvr corinthians motorsport']] |
united states house of representatives elections , 1828 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1828 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668243-25.html.csv | ordinal | john roane is the incumbent with the earliest first elected year among the incumbents of the 1828 house of representatives elections . | {'row': '9', 'col': '4', 'order': '1', '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', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'john roane', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent }'}, 'john roane'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; john roane } = true', 'tointer': 'select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is john roane .'} | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; john roane } = true | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is john roane . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'john roane_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', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'john roane_8': 'john roane'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'john roane_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['virginia 2', 'james trezvant', 'jacksonian', '1825', 're - elected', 'james trezvant ( j ) 100 %'], ['virginia 3', 'william s archer', 'jacksonian', '1820 ( special )', 're - elected', 'william s archer ( j ) 100 %'], ['virginia 4', 'mark alexander', 'jacksonian', '1819', 're - elected', 'mark alexander ( j ) 100 %'], ['virginia 6', 'thomas davenport', 'jacksonian', '1825', 're - elected', 'thomas davenport ( j ) 100 %'], ['virginia 7', 'nathaniel h claiborne', 'jacksonian', '1825', 're - elected', 'nathaniel h claiborne ( j ) 100 %'], ['virginia 9', 'andrew stevenson', 'jacksonian', '1821', 're - elected', 'andrew stevenson ( j ) 100 %'], ['virginia 10', 'william c rives', 'jacksonian', '1823', 're - elected', 'william c rives ( j ) 100 %'], ['virginia 11', 'philip p barbour', 'jacksonian', '1815 1827', 're - elected', 'philip p barbour ( j ) 100 %'], ['virginia 12', 'john roane', 'jacksonian', '1809 1827', 're - elected', 'john roane ( j ) 100 %'], ['virginia 13', 'john taliaferro', 'anti - jacksonian', '1824 ( special )', 're - elected', 'john taliaferro ( aj ) 61.8 % willoughby newton 38.2 %'], ['virginia 14', 'charles f mercer', 'anti - jacksonian', '1817', 're - elected', 'charles f mercer ( aj ) 82.0 % john gibson 18.0 %'], ['virginia 15', 'john s barbour', 'jacksonian', '1823', 're - elected', 'john s barbour ( j ) 100 %'], ['virginia 16', 'william armstrong', 'anti - jacksonian', '1825', 're - elected', 'william armstrong ( aj ) 100 %'], ['virginia 17', 'robert allen', 'jacksonian', '1827', 're - elected', 'robert allen ( j ) 61.5 % samuel kerceval 38.5 %'], ['virginia 19', 'william mccoy', 'jacksonian', '1811', 're - elected', 'william mccoy ( j ) 100 %'], ['virginia 20', 'john floyd', 'jacksonian', '1817', 'retired jacksonian hold', 'robert craig ( j ) 55.0 % fleming b miller 45.0 %']] |
iron fist ( album ) | https://en.wikipedia.org/wiki/Iron_Fist_%28album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1620364-2.html.csv | count | there were three versions of the album iron fist that were released by the label bronze . | {'scope': 'all', 'criterion': 'equal', 'value': 'bronze', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'bronze'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to bronze .', 'tostr': 'filter_eq { all_rows ; label ; bronze }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; label ; bronze } }', 'tointer': 'select the rows whose label record fuzzily matches to bronze . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; label ; bronze } } ; 4 } = true', 'tointer': 'select the rows whose label record fuzzily matches to bronze . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; label ; bronze } } ; 4 } = true | select the rows whose label record fuzzily matches to bronze . 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, 'label_5': 5, 'bronze_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', 'label_5': 'label', 'bronze_6': 'bronze', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'label_5': [0], 'bronze_6': [0], '4_7': [2]} | ['date', 'region', 'label', 'catalogue', 'format'] | [['17 april 1982', 'uk', 'bronze', 'bron 539', 'vinyl'], ['17 april 1982', 'north america', 'mercury', 'srm - 1 - 4042', 'vinyl'], ['1982', 'france', 'wea filipacchi music', '893048', 'vinyl'], ['1982', 'germany', 'bronze', '204 636', 'vinyl'], ['21 / dec / 1982', 'yugoslavia', 'jugoton', 'lsbro 11019', 'vinyl'], ['1982', 'australia / nz', 'bronze', 'l - 37841', 'vinyl'], ['1982', 'brazil', 'bronze', '6328444', 'vinyl'], ['1987', 'france', 'castle communications', 'clacd 123', 'cd'], ['1996', 'uk', 'essential , castle music', 'esm cd 372', 'cd'], ['1999', 'us', 'castle music america', 'cdx cmacd - 523', 'cd'], ['2001', 'north america', 'metal - is', 'cdx 85211', 'cd'], ['2003', 'italy', 'earmark', 'lppic 41017', '180 g vinyl picture disc , gatefold cover'], ['2005', 'uk', 'sanctuary', 'smed - 244', '2cd']] |
1996 - 97 atlanta hawks season | https://en.wikipedia.org/wiki/1996%E2%80%9397_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18493040-9.html.csv | superlative | in april of the 1996-97 season , the atlanta hawks ' april 2 game had the highest attendance . | {'scope': 'all', 'col_superlative': '5', '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', 'location attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; location attendance }'}, 'date'], 'result': 'april 2', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; location attendance } ; date }'}, 'april 2'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; location attendance } ; date } ; april 2 } = true', 'tointer': 'select the row whose location attendance record of all rows is maximum . the date record of this row is april 2 .'} | eq { hop { argmax { all_rows ; location attendance } ; date } ; april 2 } = true | select the row whose location attendance record of all rows is maximum . the date record of this row is april 2 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'date_6': 6, 'april 2_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'date_6': 'date', 'april 2_7': 'april 2'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'date_6': [1], 'april 2_7': [2]} | ['game', 'date', 'opponent', 'score', 'location attendance', 'record'] | [['73', 'april 2', 'charlotte hornets', 'l 84 - 95', 'charlotte coliseum 24042', '50 - 23'], ['game', 'date', 'opponent', 'score', 'location attendance', 'record'], ['74', 'april 4', 'detroit pistons', 'w 103 - 89', 'omni coliseum 16378', '51 - 23'], ['75', 'april 5', 'new york knicks', 'l 97 - 102', 'omni coliseum 16378', '51 - 24'], ['76', 'april 9', 'philadelphia 76ers', 'w 116 - 101', 'corestates center 16549', '52 - 24'], ['77', 'april 11', 'indiana pacers', 'w 104 - 92', 'market square arena 16403', '53 - 24'], ['78', 'april 12', 'minnesota timberwolves', 'w 80 - 66', 'target center 18874', '54 - 24'], ['79', 'april 15', 'new jersey nets', 'w 109 - 101', 'omni coliseum 14458', '55 - 24'], ['80', 'april 16', 'new york knicks', 'l 92 - 96', 'madison square garden 19763', '55 - 25'], ['81', 'april 19', 'philadelphia 76ers', 'w 136 - 104', 'omni coliseum 16457', '56 - 25'], ['82', 'april 20', 'new jersey nets', 'l 92 - 108', 'continental airlines arena 18702', '56 - 26']] |
1996 - 97 segunda división | https://en.wikipedia.org/wiki/1996%E2%80%9397_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12090729-2.html.csv | majority | most of the clubs among the 1996-97 segunda division had wins below 20 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '20', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'wins', '20'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , most of them are less than 20 .', 'tostr': 'most_less { all_rows ; wins ; 20 } = true'} | most_less { all_rows ; wins ; 20 } = true | for the wins records of all rows , most of them are less than 20 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '20_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '20_4': '20'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '20_4': [0]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'cp mérida', '38', '72', '21', '9', '8', '57', '35', '+ 22'], ['2', 'ud salamanca', '38', '71', '20', '11', '7', '72', '33', '+ 39'], ['3', 'rcd mallorca', '38', '70', '20', '10', '8', '59', '38', '+ 21'], ['4', 'albacete', '38', '66', '19', '9', '10', '51', '32', '+ 19'], ['5', 'sd eibar', '38', '66', '17', '15', '6', '44', '26', '+ 18'], ['6', 'cd badajoz', '38', '60', '15', '15', '8', '38', '26', '+ 12'], ['7', 'ud las palmas', '38', '52', '13', '13', '12', '54', '46', '+ 8'], ['8', 'cd leganés', '38', '52', '13', '13', '12', '43', '39', '+ 4'], ['9', 'levante ud', '38', '50', '13', '11', '14', '53', '46', '+ 7'], ['10', 'villarreal cf', '38', '48', '13', '9', '16', '38', '52', '- 14'], ['11', 'ue lleida', '38', '48', '12', '12', '14', '48', '41', '+ 7'], ['12', 'atlético de madrid b', '38', '47', '12', '11', '15', '57', '61', '- 4'], ['13', 'deportivo alavés', '38', '47', '12', '11', '15', '43', '47', '- 4'], ['14', 'cd toledo', '38', '45', '12', '9', '17', '37', '53', '- 16'], ['15', 'cd ourense', '38', '44', '11', '11', '16', '35', '46', '- 11'], ['16', 'ca osasuna', '38', '44', '11', '11', '16', '34', '42', '- 8'], ['17', 'almería cf', '38', '41', '9', '14', '15', '40', '51', '- 11'], ['18', 'real madrid b', '38', '41', '11', '8', '19', '40', '69', '- 29'], ['19', 'barcelona b', '38', '34', '7', '13', '18', '40', '63', '- 23'], ['20', 'écija', '38', '30', '7', '9', '22', '27', '64', '- 37']] |
zakspeed | https://en.wikipedia.org/wiki/Zakspeed | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219581-1.html.csv | majority | the zakspeed motor racing team used g type tyres in the majority of the years . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'g', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'tyres', 'g'], 'result': True, 'ind': 0, 'tointer': 'for the tyres records of all rows , most of them fuzzily match to g .', 'tostr': 'most_eq { all_rows ; tyres ; g } = true'} | most_eq { all_rows ; tyres ; g } = true | for the tyres records of all rows , most of them fuzzily match to g . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tyres_3': 3, 'g_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tyres_3': 'tyres', 'g_4': 'g'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tyres_3': [0], 'g_4': [0]} | ['year', 'chassis', 'engine ( s )', 'tyres', 'points'] | [['1985', 'zakspeed 841', 'zakspeed s4 t / c', 'g', '0'], ['1986', 'zakspeed 861', 'zakspeed s4 t / c', 'g', '0'], ['1987', 'zakspeed 861 zakspeed 871', 'zakspeed s4 t / c', 'g', '2'], ['1988', 'zakspeed 881', 'zakspeed s4 t / c', 'g', '0'], ['1989', 'zakspeed 891', 'yamaha v8', 'p', '0']] |
list of top 10 singles in 2010 ( scotland ) | https://en.wikipedia.org/wiki/List_of_Top_10_singles_in_2010_%28Scotland%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27813010-2.html.csv | count | 4 of the singles in the top 10 singles in 2010 peaked at number 1 . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'peak', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose peak record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; peak ; 1 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; peak ; 1 } }', 'tointer': 'select the rows whose peak record is equal to 1 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; peak ; 1 } } ; 4 } = true', 'tointer': 'select the rows whose peak record is equal to 1 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; peak ; 1 } } ; 4 } = true | select the rows whose peak record is equal to 1 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'peak_5': 5, '1_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'peak_5': 'peak', '1_6': '1', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'peak_5': [0], '1_6': [0], '4_7': [2]} | ['entry date', 'single', 'artist', 'peak', 'peak reached', 'weeks in top 10'] | [['31 october', 'meet me halfway', 'the black eyed peas', '1', '21 november', '11'], ['7 november', 'bad romance', 'lady gaga', '1', '19 december', '12'], ['5 december', 'the official bbc children in need medley', 'peter kay', '1', '5 december', '5'], ['5 december', 'russian roulette', 'rihanna', '3', '12 december', '6'], ['26 december', 'the climb', 'joe mcelderry', '1', '26 december', '2'], ['26 december', 'killing in the name', 'rage against the machine', '2', '26 december', '2']] |
bangladesh navy | https://en.wikipedia.org/wiki/Bangladesh_Navy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1348246-3.html.csv | majority | for the serial & branch numbered 1 through 8 for the bangladesh navy , the majority of the seaman have a title that includes the words petty officer . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'petty officer', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'seaman', 'petty officer'], 'result': True, 'ind': 0, 'tointer': 'for the seaman records of all rows , most of them fuzzily match to petty officer .', 'tostr': 'most_eq { all_rows ; seaman ; petty officer } = true'} | most_eq { all_rows ; seaman ; petty officer } = true | for the seaman records of all rows , most of them fuzzily match to petty officer . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'seaman_3': 3, 'petty officer_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'seaman_3': 'seaman', 'petty officer_4': 'petty officer'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'seaman_3': [0], 'petty officer_4': [0]} | ['serial & branch', 'seaman', 'mechanical', 'secretariat', 'supply', 'electrical', 'radio electrical', 'regulating', 'medical'] | [['1', 'od ( ordinary seaman )', 'me ii', 'wtr ii', 'sa ii', 'en ii', 'ren ii', 'pm ii', 'ma ii'], ['2', 'ab ( able seaman )', 'me i', 'wtr i', 'sa i', 'en i', 'ren i', 'pm i', 'ma i'], ['3', 'ls ( leading seaman )', 'lme', 'lwtr', 'lsa', 'len', 'lren', 'lpm', 'lma'], ['4', 'po ( petty officer )', 'era - iv', 'po ( w )', 'po ( s )', 'ea - iv', 'rea - iv', 'po ( r )', 'po ( med )'], ['5', 'cpo ( chief petty officer )', 'era - i / ii / iii', 'cpo ( w )', 'cpo ( s )', 'ea - i / ii / iii', 'rea - i / ii / iii', 'cpo ( reg )', 'cpo ( med )'], ['6', 'scpo ( senior chief petty officer )', 'scpo ( e ) , cera', 'scpo ( w )', 'scpo ( s )', 'scpo ( l ) , cea', 'scpo ( r ) , crea', 'scpo ( reg )', 'scpo ( med )'], ['7', 'mcpo ( master chief petty officer )', 'mcpo ( e )', 'mcpo ( s )', 'mcpo ( s )', 'mcpo ( l )', 'mcpo ( r )', 'mcpo ( reg )', 'mcpo ( med )'], ['8', 'honorary sub lieutenant ( x )', 'hon s lt ( e )', 'hon s lt ( s )', 'hon s lt ( s )', 'hon s lt ( l )', 'hon s lt ( r )', 'hon s lt ( reg )', 'hon s lt ( w / m )']] |
locomotives of the north british railway | https://en.wikipedia.org/wiki/Locomotives_of_the_North_British_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16062061-3.html.csv | aggregation | there were 14 locomotives of the north british railway fully built during the year 1873 . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '14', 'subset': {'col': '6', 'criterion': 'equal', 'value': '1873'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '1873'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 1873 }', 'tointer': 'select the rows whose date record is equal to 1873 .'}, 'no built'], 'result': '14', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; 1873 } ; no built }'}, '14'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; 1873 } ; no built } ; 14 } = true', 'tointer': 'select the rows whose date record is equal to 1873 . the sum of the no built record of these rows is 14 .'} | round_eq { sum { filter_eq { all_rows ; date ; 1873 } ; no built } ; 14 } = true | select the rows whose date record is equal to 1873 . the sum of the no built record of these rows is 14 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '1873_6': 6, 'no built_7': 7, '14_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '1873_6': '1873', 'no built_7': 'no built', '14_8': '14'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '1873_6': [0], 'no built_7': [1], '14_8': [2]} | ['1st built', '1913 class', 'wa', 'no built', 'builder', 'date', 'lner class'] | [['141', '-', '2 - 4 - 0', '2', 'nbr cowlairs', '1869', '-'], ['418', 'p', '2 - 4 - 0', '8', 'nbr cowlairs', '1873', 'e7'], ['40', '-', '2 - 4 - 0', '2', 'nbr cowlairs', '1873', '-'], ['224', '-', '4 - 4 - 0', '2', 'nbr cowlairs', '1871', '-'], ['420', '-', '4 - 4 - 0', '4', 'nbr cowlairs', '1873', '-'], ['17', '-', '0 - 6 - 0', '1', 'nbr stmargarets', '1868', '-'], ['251', 'e', '0 - 6 - 0', '38', 'nbr cowlairs', '1867 - 74', 'j84'], ['396', 'e', '0 - 6 - 0', '26', 'neilson & co ( 12 ) , dübs & co ( 14 )', '1867 - 69', 'j31'], ['56', '-', '0 - 6 - 0', '8', 'nbr stmargarets', '1868 - 69', '-'], ['115', 'e', '0 - 6 - 0', '62', 'nbr cowlairs', '1869 - 75', 'j31'], ['226', 'e', '0 - 6 - 0st', '2', 'nbr cowlairs', '1870', 'j86'], ['220', '-', '0 - 6 - 0st', '1', 'nbr cowlairs', '1870', '-'], ['130', 'e', '0 - 6 - 0st', '9', 'nbr cowlairs', '1870 - 73', 'j85'], ['229', 'e', '0 - 6 - 0st', '15', 'nbr cowlairs', '1871 - 73', 'j81'], ['32', '-', '0 - 6 - 0st', '6', 'nbr cowlairs', '1874', '-'], ['394', '-', '0 - 4 - 0', '2', 'neilson & co', '1867', '-'], ['357', '-', '0 - 4 - 0', '2', 'nbr cowlairs', '1868', 'y10'], ['18', '-', '0 - 4 - 0st', '2', 'nbr cowlairs', '1872', '-']] |
eurovision dance contest 2007 | https://en.wikipedia.org/wiki/Eurovision_Dance_Contest_2007 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10530468-1.html.csv | count | among the dance styles in eurovision dance contest 2007 , rumba was used 5 times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'rumba', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'dance styles', 'rumba'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose dance styles record fuzzily matches to rumba .', 'tostr': 'filter_eq { all_rows ; dance styles ; rumba }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; dance styles ; rumba } }', 'tointer': 'select the rows whose dance styles record fuzzily matches to rumba . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; dance styles ; rumba } } ; 5 } = true', 'tointer': 'select the rows whose dance styles record fuzzily matches to rumba . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; dance styles ; rumba } } ; 5 } = true | select the rows whose dance styles record fuzzily matches to rumba . 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, 'dance styles_5': 5, 'rumba_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', 'dance styles_5': 'dance styles', 'rumba_6': 'rumba', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'dance styles_5': [0], 'rumba_6': [0], '5_7': [2]} | ['draw', 'dancers', 'dance styles', 'place', 'points'] | [['01', 'denise biellmann & sven ninnemann', 'paso doble and swing', '16', '0'], ['02', 'mariya sittel & vladislav borodinov', 'rumba and paso doble', '7', '72'], ['03', 'alexandra matteman & redmond valk', 'cha - cha - cha and rumba', '12', '34'], ['04', 'camilla dallerup & brendan cole', 'rumba and freestyle', '15', '18'], ['05', 'kelly & andy kainz', 'jive and paso doble', '5', '74'], ['06', 'wolke hegenbarth & oliver seefeldt', 'samba dance and freestyle', '8', '59'], ['07', 'ourania kolliou & spiros pavlidis', 'jive and sirtaki', '13', '31'], ['08', 'gabrielė valiukaitė & gintaras svistunavičius', 'paso doble and traditional lithuanian folk dance', '11', '35'], ['09', 'amagoya benlloch & abraham martinez', 'cha - cha - cha and paso doble', '10', '38'], ['10', 'nicola byrne & mick donegan', 'jive and fandango', '3', '95'], ['11', 'katarzyna cichopek & marcin hakiel', 'cha - cha - cha and showdance', '4', '84'], ['12', 'mette skou elkjær & david jørgensen', 'rumba and showdance', '9', '38'], ['13', 'sónia araújo & ricardo silva', 'jive and tango', '5', '74'], ['14', 'yulia okropiridze & illya sydorenko', 'quickstep and showdance', '2', '121'], ['15', 'cecilia ehrling & martin lidberg', 'paso doble and disco fusion', '14', '23'], ['16', 'katja koukkula & jussi väänänen', 'rumba and paso doble', '1', '132']] |
roman catholic archdiocese of santa fe | https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Santa_Fe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1656555-1.html.csv | superlative | of the archbishops in the roman catholic archdiocese of santa fe , the one who was born the earliest was jean baptiste lamy . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'born'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; born }'}, 'archbishop'], 'result': 'jean baptiste lamy', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; born } ; archbishop }'}, 'jean baptiste lamy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; born } ; archbishop } ; jean baptiste lamy } = true', 'tointer': 'select the row whose born record of all rows is minimum . the archbishop record of this row is jean baptiste lamy .'} | eq { hop { argmin { all_rows ; born } ; archbishop } ; jean baptiste lamy } = true | select the row whose born record of all rows is minimum . the archbishop record of this row is jean baptiste lamy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'born_5': 5, 'archbishop_6': 6, 'jean baptiste lamy_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'born_5': 'born', 'archbishop_6': 'archbishop', 'jean baptiste lamy_7': 'jean baptiste lamy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'born_5': [0], 'archbishop_6': [1], 'jean baptiste lamy_7': [2]} | ['archbishop', 'born', 'ordained priest', 'ordained bishop', 'appointed archbishop', 'vacated throne', 'died'] | [['jean baptiste lamy', 'october 11 , 1814', 'december 1838', 'november 24 , 1850', 'february 12 , 1875', 'august 18 , 1885', 'february 13 , 1888'], ['jean baptiste salpointe', 'february 22 , 1825', 'december 20 , 1851', 'june 20 , 1869', 'august 18 , 1885', 'january 7 , 1894', 'july 15 , 1898'], ['placide louis chapelle', 'august 28 , 1843', 'june 28 , 1866', 'november 1 , 1891', 'january 7 , 1895', 'december 7 , 1898', 'august 8 , 1906'], ['peter bourgade', 'october 17 , 1846', 'november 30 , 1869', 'may 1 , 1886', 'january 7 , 1899', 'may 17 , 1907', 'may 17 , 1907'], ['john baptist pitaval', 'february 10 , 1858', 'december 24 , 1881', 'july 25 , 1902', 'january 3 , 1909', 'july 29 , 1918', 'may 23 , 1928'], ['albert daeger', 'march 5 , 1872', 'july 25 , 1896', 'may 7 , 1919', 'march 10 , 1919', 'december 2 , 1932', 'december 2 , 1932'], ['rudolph gerken', 'march 7 , 1887', 'july 10 , 1917', 'april 26 , 1927', 'june 2 , 1933', 'march 2 , 1943', 'march 2 , 1943'], ['edwin byrne', 'august 9 , 1891', 'may 22 , 1915', 'november 30 , 1925', 'june 12 , 1943', 'july 26 , 1963', 'july 26 , 1963'], ['james peter davis', 'june 9 , 1904', 'may 19 , 1929', 'october 6 , 1943', 'january 3 , 1964', 'june 1 , 1974', 'march 4 , 1988'], ['robert fortune sanchez', 'march 20 , 1934', 'december 20 , 1959', 'july 25 , 1974', 'june 1 , 1974', 'april 6 , 1993', 'january 20 , 2012'], ['michael jarboe sheehan', 'july 9 , 1939', 'july 12 , 1964', 'june 17 , 1983', 'august 16 , 1993', 'still serving', 'still living']] |
doctor who ( series 1 ) | https://en.wikipedia.org/wiki/Doctor_Who_%28series_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18012738-1.html.csv | count | five episodes of doctor who ( series 1 ) were aired in april 2005 . | {'scope': 'all', 'criterion': 'equal', 'value': 'april 2005', 'result': '5', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'april 2005'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to april 2005 .', 'tostr': 'filter_eq { all_rows ; original air date ; april 2005 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; original air date ; april 2005 } }', 'tointer': 'select the rows whose original air date record fuzzily matches to april 2005 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; original air date ; april 2005 } } ; 5 } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to april 2005 . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; original air date ; april 2005 } } ; 5 } = true | select the rows whose original air date record fuzzily matches to april 2005 . 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, 'original air date_5': 5, 'april 2005_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', 'original air date_5': 'original air date', 'april 2005_6': 'april 2005', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'april 2005_6': [0], '5_7': [2]} | ['story no', 'episode', 'title', 'directed by', 'written by', 'uk viewers ( million )', 'ai ( % )', 'original air date', 'production code'] | [['157', '1', 'rose', 'keith boak', 'russell t davies', '10.81', '81', '26 march 2005', '1.1'], ['158', '2', 'the end of the world', 'euros lyn', 'russell t davies', '7.97', '79', '2 april 2005', '1.2'], ['159', '3', 'the unquiet dead', 'euros lyn', 'mark gatiss', '8.86', '80', '9 april 2005', '1.3'], ['160a', '4', 'aliens of london', 'keith boak', 'russell t davies', '7.63', '81', '16 april 2005', '1.4'], ['160b', '5', 'world war three', 'keith boak', 'russell t davies', '7.98', '82', '23 april 2005', '1.5'], ['161', '6', 'dalek', 'joe ahearne', 'robert shearman', '8.63', '84', '30 april 2005', '1.6'], ['162', '7', 'the long game', 'brian grant', 'russell t davies', '8.01', '81', '7 may 2005', '1.7'], ['163', '8', "father 's day", 'joe ahearne', 'paul cornell', '8.06', '83', '14 may 2005', '1.8'], ['164a', '9', 'the empty child', 'james hawes', 'steven moffat', '7.11', '84', '21 may 2005', '1.9'], ['164b', '10', 'the doctor dances', 'james hawes', 'steven moffat', '6.86', '85', '28 may 2005', '1.10'], ['165', '11', 'boom town', 'joe ahearne', 'russell t davies', '7.68', '82', '4 june 2005', '1.11'], ['166a', '12', 'bad wolf', 'joe ahearne', 'russell t davies', '6.81', '85', '11 june 2005', '1.12']] |
list of tvb series ( 1998 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%281998%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18493407-1.html.csv | ordinal | the tvb series " journey to the west ii " had the third highest number of episodes in 1998 . | {'row': '9', 'col': '3', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'number of episodes', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; number of episodes ; 3 }'}, 'english title ( chinese title )'], 'result': 'journey to the west ii 西遊記 ( 貳 )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; number of episodes ; 3 } ; english title ( chinese title ) }'}, 'journey to the west ii 西遊記 ( 貳 )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; number of episodes ; 3 } ; english title ( chinese title ) } ; journey to the west ii 西遊記 ( 貳 ) } = true', 'tointer': 'select the row whose number of episodes record of all rows is 3rd maximum . the english title ( chinese title ) record of this row is journey to the west ii 西遊記 ( 貳 ) .'} | eq { hop { nth_argmax { all_rows ; number of episodes ; 3 } ; english title ( chinese title ) } ; journey to the west ii 西遊記 ( 貳 ) } = true | select the row whose number of episodes record of all rows is 3rd maximum . the english title ( chinese title ) record of this row is journey to the west ii 西遊記 ( 貳 ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'number of episodes_5': 5, '3_6': 6, 'english title (chinese title)_7': 7, 'journey to the west ii 西遊記 (貳)_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'number of episodes_5': 'number of episodes', '3_6': '3', 'english title (chinese title)_7': 'english title ( chinese title )', 'journey to the west ii 西遊記 (貳)_8': 'journey to the west ii 西遊記 ( 貳 )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'number of episodes_5': [0], '3_6': [0], 'english title (chinese title)_7': [1], 'journey to the west ii 西遊記 (貳)_8': [2]} | ['airing date', 'english title ( chinese title )', 'number of episodes', 'genre', 'official website'] | [['12 jan - 6 feb', 'a tough side of a lady 花木蘭', '20', 'costume action', 'official website'], ['9 feb - 6 mar', "a place of one 's own 大澳的天空", '20', 'modern drama', 'official website'], ['9 mar - 1 may', 'dark tales ii 聊齋 ( 貳 )', '50', 'costume drama', 'official website'], ['4 may - 29 may', 'as sure as fate 師奶強人', '20', 'modern drama', 'official website'], ['1 jun - 31 jul', 'the duke of mount deer 鹿鼎記', '45', 'costume drama', 'official website'], ['3 aug - 4 sep', 'old time buddy - to catch a thief 難兄難弟之神探李奇', '25', 'period drama', 'official website'], ['7 sep - 25 sep', 'simply ordinary 林世榮', '15', 'costume drama', 'official website'], ['28 sep - 23 oct', 'web of love 網上有情人', '20', 'modern drama', 'official website'], ['26 oct - 18 dec', 'journey to the west ii 西遊記 ( 貳 )', '42', 'costume drama', 'official website'], ['21 dec 1998 - 15 jan 1999', 'moments of endearment 外父唔怕做', '20', 'modern drama', 'official website']] |
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/1-1341690-13.html.csv | majority | most of the incumbents were from the republican party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'} | most_eq { all_rows ; party ; republican } = true | for the party records of all rows , most of them fuzzily match to republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 3', 'robert p hanrahan', 'republican', '1972', 'lost re - election democratic gain', 'marty russo ( d ) 52.6 % robert p hanrahan ( r ) 47.4 %'], ['illinois 4', 'ed derwinski', 'republican', '1958', 're - elected', 'ed derwinski ( r ) 59.2 % ronald a rodger ( d ) 40.8 %'], ['illinois 6', 'harold r collier', 'republican', '1956', 'retired republican hold', 'henry hyde ( r ) 53.4 % edward v hanrahan ( d ) 46.6 %'], ['illinois 9', 'sidney r yates', 'democratic', '1964', 're - elected', 'sidney r yates ( d ) unopposed'], ['illinois 10', 'samuel h young', 'republican', '1972', 'lost re - election democratic gain', 'abner j mikva ( d ) 50.9 % samuel h young ( r ) 49.1 %'], ['illinois 12', 'phil crane', 'republican', '1969', 're - elected', 'phil crane ( r ) 61.1 % betty c spence ( d ) 38.9 %'], ['illinois 19', 'tom railsback', 'republican', '1966', 're - elected', 'tom railsback ( r ) 65.3 % jim gende ( d ) 34.7 %'], ['illinois 20', 'paul findley', 'republican', '1960', 're - elected', 'paul findley ( r ) 54.8 % peter f mack ( d ) 45.2 %'], ['illinois 23', 'melvin price', 'democratic', '1944', 're - elected', 'melvin price ( d ) 80.5 % scott randolph ( r ) 19.5 %']] |
2007 grand rapids rampage season | https://en.wikipedia.org/wiki/2007_Grand_Rapids_Rampage_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11786440-4.html.csv | unique | in the 2007 grand rapids rampage 's season the only player with 12 touchdowns is jerome riley . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '12', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', "td 's", '12'], 'result': None, 'ind': 0, 'tointer': "select the rows whose td 's record is equal to 12 .", 'tostr': "filter_eq { all_rows ; td 's ; 12 }"}], 'result': True, 'ind': 1, 'tostr': "only { filter_eq { all_rows ; td 's ; 12 } }", 'tointer': "select the rows whose td 's record is equal to 12 . there is only one such row in the table ."}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', "td 's", '12'], 'result': None, 'ind': 0, 'tointer': "select the rows whose td 's record is equal to 12 .", 'tostr': "filter_eq { all_rows ; td 's ; 12 }"}, 'player'], 'result': 'jerome riley', 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; td 's ; 12 } ; player }"}, 'jerome riley'], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; td 's ; 12 } ; player } ; jerome riley }", 'tointer': 'the player record of this unqiue row is jerome riley .'}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; td 's ; 12 } } ; eq { hop { filter_eq { all_rows ; td 's ; 12 } ; player } ; jerome riley } } = true", 'tointer': "select the rows whose td 's record is equal to 12 . there is only one such row in the table . the player record of this unqiue row is jerome riley ."} | and { only { filter_eq { all_rows ; td 's ; 12 } } ; eq { hop { filter_eq { all_rows ; td 's ; 12 } ; player } ; jerome riley } } = true | select the rows whose td 's record is equal to 12 . there is only one such row in the table . the player record of this unqiue row is jerome riley . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, "td 's_7": 7, '12_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'jerome riley_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', "td 's_7": "td 's", '12_8': '12', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'jerome riley_10': 'jerome riley'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], "td 's_7": [0], '12_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'jerome riley_10': [3]} | ['player', 'rec', 'yards', 'avg', "td 's", 'long'] | [['cornelius bonner', '102', '1436', '14.1', '29', '49'], ['timon marshall', '102', '1134', '11.1', '27', '34'], ['jerome riley', '78', '845', '10.8', '12', '43'], ['scotty anderson', '31', '323', '10.4', '6', '33'], ['clarence coleman', '23', '253', '11', '3', '28'], ['ronney daniels', '23', '243', '10.6', '6', '30'], ['jermaine lewis', '23', '234', '10.2', '2', '30'], ['troy edwards', '27', '220', '8.1', '2', '24'], ['kenny solomon', '18', '201', '11.2', '3', '46'], ['chris ryan', '9', '70', '7.8', '1', '24'], ['winfield garnett', '1', '2', '2', '0', '2']] |
patty schnyder | https://en.wikipedia.org/wiki/Patty_Schnyder | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1547798-3.html.csv | unique | the tournament played on 23 october 2005 was the only tournament that patty schnyder played on a carpet surface . | {'scope': 'all', 'row': '7', 'col': '3', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'carpet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; carpet } }', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}, 'date'], 'result': '23 october 2005', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; carpet } ; date }'}, '23 october 2005'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; 23 october 2005 }', 'tointer': 'the date record of this unqiue row is 23 october 2005 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; 23 october 2005 } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the date record of this unqiue row is 23 october 2005 .'} | and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; 23 october 2005 } } = true | select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the date record of this unqiue row is 23 october 2005 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '23 october 2005_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'carpet_8': 'carpet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '23 october 2005_10': '23 october 2005'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '23 october 2005_10': [3]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['15 september 1996', 'karlovy vary , czech republic', 'clay', 'ruxandra dragomir', '6 - 2 , 3 - 6 , 6 - 4'], ['28 september 1998', 'munich , germany', 'hard ( i )', 'venus williams', '6 - 2 , 3 - 6 , 6 - 2'], ['16 july 2000', 'klagenfurt , austria', 'clay', 'barbara schett', '5 - 7 , 6 - 4 , 6 - 4'], ['12 july 2001', 'vienna , austria', 'clay', 'iroda tulyaganova', '6 - 3 , 6 - 2'], ['21 april 2002', 'hilton head , south carolina , usa', 'clay', 'iva majoli', '7 - 6 ( 5 ) , 6 - 4'], ['15 may 2005', 'rome , italy', 'clay', 'amélie mauresmo', '2 - 6 , 6 - 3 , 6 - 4'], ['23 october 2005', 'zürich , switzerland', 'carpet ( i )', 'lindsay davenport', '7 - 6 ( 5 ) , 6 - 3'], ['30 october 2005', 'linz , austria', 'hard ( i )', 'nadia petrova', '4 - 6 , 6 - 3 , 6 - 1'], ['16 april 2006', 'charleston , south carolina , usa', 'clay', 'nadia petrova', '6 - 3 , 4 - 6 , 6 - 1'], ['30 july 2006', 'stanford , california , usa', 'hard', 'kim clijsters', '6 - 4 , 6 - 2'], ['16 april 2007', 'san diego , california , usa', 'hard', 'maria sharapova', '6 - 2 , 3 - 6 , 6 - 0'], ['28 october 2007', 'linz , austria', 'hard ( i )', 'daniela hantuchová', '6 - 4 , 6 - 2'], ['9 march 2008', 'bangalore , india', 'hard', 'serena williams', '7 - 5 , 6 - 3'], ['12 july 2009', 'budapest , hungary', 'clay', 'ágnes szávay', '2 - 6 , 6 - 4 , 6 - 2'], ['11 july 2010', 'budapest , hungary', 'clay', 'ágnes szávay', '6 - 2 , 6 - 4'], ['17 october 2010', 'linz , austria', 'hard ( i )', 'ana ivanovic', '6 - 1 , 6 - 2']] |
list of active indonesian navy ships | https://en.wikipedia.org/wiki/List_of_active_Indonesian_Navy_ships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12232526-2.html.csv | unique | only the kri halim perdanakususma began its service years in 1989 . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': '1989', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'service years', '1989'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose service years record fuzzily matches to 1989 .', 'tostr': 'filter_eq { all_rows ; service years ; 1989 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; service years ; 1989 } }', 'tointer': 'select the rows whose service years record fuzzily matches to 1989 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'service years', '1989'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose service years record fuzzily matches to 1989 .', 'tostr': 'filter_eq { all_rows ; service years ; 1989 }'}, 'ship name'], 'result': 'kri halim perdanakususma', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; service years ; 1989 } ; ship name }'}, 'kri halim perdanakususma'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; service years ; 1989 } ; ship name } ; kri halim perdanakususma }', 'tointer': 'the ship name record of this unqiue row is kri halim perdanakususma .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; service years ; 1989 } } ; eq { hop { filter_eq { all_rows ; service years ; 1989 } ; ship name } ; kri halim perdanakususma } } = true', 'tointer': 'select the rows whose service years record fuzzily matches to 1989 . there is only one such row in the table . the ship name record of this unqiue row is kri halim perdanakususma .'} | and { only { filter_eq { all_rows ; service years ; 1989 } } ; eq { hop { filter_eq { all_rows ; service years ; 1989 } ; ship name } ; kri halim perdanakususma } } = true | select the rows whose service years record fuzzily matches to 1989 . there is only one such row in the table . the ship name record of this unqiue row is kri halim perdanakususma . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'service years_7': 7, '1989_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'ship name_9': 9, 'kri halim perdanakususma_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'service years_7': 'service years', '1989_8': '1989', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'ship name_9': 'ship name', 'kri halim perdanakususma_10': 'kri halim perdanakususma'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'service years_7': [0], '1989_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'ship name_9': [2], 'kri halim perdanakususma_10': [3]} | ['class', 'ship name', 'origin', 'hull numbers', 'service years', 'previously', 'note'] | [['ahmad yani class ( ffghm )', 'kri ahmad yani', 'netherlands', '351', '1986 - present', 'rnn hnlms tjerk hiddes ( f804 )', 'reportedly still active as of 2009'], ['ahmad yani class ( ffghm )', 'kri slamet riyadi', 'netherlands', '352', '1986 - present', 'rnn hnlms van speijk ( f802 )', 'reportedly still active as of 2009'], ['ahmad yani class ( ffghm )', 'kri yos sudarso', 'netherlands', '353', '1987 - present', 'rnn hnlms van galen ( f803 )', 'reportedly still active as of 2009'], ['ahmad yani class ( ffghm )', 'kri oswald siahaan', 'netherlands', '354', '1987 - present', 'rnn hnlms van nes ( f805 )', 'reportedly still active as of 2012'], ['ahmad yani class ( ffghm )', 'kri halim perdanakususma', 'netherlands', '355', '1989 - present', 'rnn hnlms evertsen ( f815 )', 'reportedly still active as of 2009']] |
1994 - 95 cleveland cavaliers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16188254-3.html.csv | superlative | the venue that had the highest attendance out of the games of the ' 94 - '95 cleveland cavaliers season is charlotte coliseum . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'attendance'], 'result': 'charlotte coliseum 23698', 'ind': 0, 'tostr': 'max { all_rows ; attendance }', 'tointer': 'the maximum attendance record of all rows is charlotte coliseum 23698 .'}, 'charlotte coliseum 23698'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; attendance } ; charlotte coliseum 23698 } = true', 'tointer': 'the maximum attendance record of all rows is charlotte coliseum 23698 .'} | eq { max { all_rows ; attendance } ; charlotte coliseum 23698 } = true | the maximum attendance record of all rows is charlotte coliseum 23698 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'attendance_4': 4, 'charlotte coliseum 23698_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', 'charlotte coliseum 23698_5': 'charlotte coliseum 23698'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'attendance_4': [0], 'charlotte coliseum 23698_5': [1]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['november 5', 'cleveland', '115 - 107', 'charlotte', 'mark price , 27 points', 'charlotte coliseum 23698', '1 - 0'], ['november 8', 'houston', '100 - 98', 'cleveland', 'terrell brandon , 19 points', 'gund arena 20562', '1 - 1'], ['november 10', 'milwaukee', '88 - 108', 'cleveland', 'mark price , 18 points', 'gund arena 19203', '2 - 1'], ['november 12', 'indiana', '93 - 86', 'cleveland', 'mark price , 15 points', 'gund arena 20401', '2 - 2'], ['november 15', 'charlotte', '86 - 89', 'cleveland', 'tyrone hill , 22 points', 'gund arena 19959', '3 - 2'], ['november 17', 'cleveland', '81 - 80', 'portland', 'mark price , 30 points', 'memorial coliseum 12888', '4 - 2'], ['november 18', 'cleveland', '80 - 82', 'la lakers', 'hot rod williams , 16 points', 'great western forum 10177', '4 - 3'], ['november 20', 'cleveland', '88 - 96', 'sacramento', 'hot rod williams , 17 points', 'arco arena 17317', '4 - 4'], ['november 22', 'minnesota', '79 - 112', 'cleveland', 'mark price , 17 points', 'gund arena 19125', '5 - 4'], ['november 23', 'cleveland', '87 - 100', 'miami', '2 way tie , 17 points', 'miami arena 14498', '5 - 5'], ['november 25', 'cleveland', '96 - 94', 'washington', 'tyrone hill , 25 points', 'usair arena 12756', '6 - 5'], ['november 26', 'golden state', '87 - 101', 'cleveland', 'mark price , 31 points', 'gund arena 20562', '7 - 5'], ['november 30', 'la lakers', '79 - 117', 'cleveland', '3 way tie , 16 points', 'gund arena 19014', '8 - 5']] |
2008 - 09 philadelphia flyers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17511295-5.html.csv | comparative | the philadelphia flyers game that took place on december 30 had a lower attendance than the game that occuered on december 26 . | {'row_1': '14', 'row_2': '12', 'col': '6', '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', 'date', 'december 30'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to december 30 .', 'tostr': 'filter_eq { all_rows ; date ; december 30 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; december 30 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 30 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december 26'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december 26 .', 'tostr': 'filter_eq { all_rows ; date ; december 26 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; december 26 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 26 . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; date ; december 30 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 26 } ; attendance } } = true', 'tointer': 'select the rows whose date record fuzzily matches to december 30 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 26 . take the attendance record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; date ; december 30 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 26 } ; attendance } } = true | select the rows whose date record fuzzily matches to december 30 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 26 . take the attendance 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, 'date_7': 7, 'december 30_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'december 26_12': 12, 'attendance_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', 'date_7': 'date', 'december 30_8': 'december 30', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'december 26_12': 'december 26', 'attendance_13': 'attendance'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'december 30_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'december 26_12': [1], 'attendance_13': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 2', 'tampa bay', '3 - 4', 'philadelphia', 'biron', '19227', '12 - 7 - 5'], ['december 4', 'new jersey', '3 - 2', 'philadelphia', 'biron', '19577', '12 - 7 - 6'], ['december 6', 'philadelphia', '2 - 1', 'carolina', 'niittymaki', '14061', '13 - 7 - 6'], ['december 9', 'ny islanders', '3 - 4', 'philadelphia', 'biron', '19037', '14 - 7 - 6'], ['december 11', 'carolina', '5 - 6', 'philadelphia', 'niittymaki', '19057', '15 - 7 - 6'], ['december 13', 'pittsburgh', '3 - 6', 'philadelphia', 'biron', '19811', '16 - 7 - 6'], ['december 16', 'colorado', '2 - 5', 'philadelphia', 'niittymaki', '19219', '17 - 7 - 6'], ['december 18', 'philadelphia', '2 - 5', 'montreal', 'niittymaki', '21273', '17 - 8 - 6'], ['december 20', 'washington', '1 - 7', 'philadelphia', 'niittymaki', '19897', '18 - 8 - 6'], ['december 21', 'philadelphia', '2 - 3', 'new jersey', 'niittymaki', '14426', '18 - 8 - 7'], ['december 23', 'ottawa', '4 - 6', 'philadelphia', 'nittymaki', '19578', '19 - 8 - 7'], ['december 26', 'philadelphia', '1 - 5', 'chicago', 'biron', '22712', '19 - 9 - 7'], ['december 27', 'philadelphia', '0 - 3', 'columbus', 'niittymaki', '18402', '19 - 10 - 7'], ['december 30', 'philadelphia', '3 - 2', 'vancouver', 'biron', '18630', '20 - 10 - 7']] |
1981 vfl season | https://en.wikipedia.org/wiki/1981_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-11.html.csv | ordinal | the match at mcg had the 3rd largest crowd in 1981 . | {'row': '1', 'col': '6', 'order': '3', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 3 }'}, 'away team score'], 'result': '14.10 ( 94 )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 3 } ; away team score }'}, '14.10 ( 94 )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; away team score } ; 14.10 ( 94 ) } = true', 'tointer': 'select the row whose crowd record of all rows is 3rd maximum . the away team score record of this row is 14.10 ( 94 ) .'} | eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; away team score } ; 14.10 ( 94 ) } = true | select the row whose crowd record of all rows is 3rd maximum . the away team score record of this row is 14.10 ( 94 ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '3_6': 6, 'away team score_7': 7, '14.10 (94)_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', 'crowd_5': 'crowd', '3_6': '3', 'away team score_7': 'away team score', '14.10 (94)_8': '14.10 ( 94 )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '3_6': [0], 'away team score_7': [1], '14.10 (94)_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '20.16 ( 136 )', 'melbourne', '14.10 ( 94 )', 'mcg', '31025', '6 june 1981'], ['st kilda', '14.15 ( 99 )', 'fitzroy', '7.17 ( 59 )', 'moorabbin oval', '21672', '6 june 1981'], ['hawthorn', '18.19 ( 127 )', 'collingwood', '12.9 ( 81 )', 'vfl park', '92935', '6 june 1981'], ['footscray', '12.10 ( 82 )', 'geelong', '17.15 ( 117 )', 'western oval', '24974', '8 june 1981'], ['carlton', '17.13 ( 115 )', 'north melbourne', '11.18 ( 84 )', 'princes park', '31808', '8 june 1981'], ['south melbourne', '12.8 ( 80 )', 'essendon', '15.18 ( 108 )', 'lake oval', '28588', '8 june 1981']] |
1928 army cadets football team | https://en.wikipedia.org/wiki/1928_Army_Cadets_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21091157-1.html.csv | ordinal | the game on october 20 resulted in the fourth lowest number of black knights points . | {'row': '4', 'col': '5', 'order': '4', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'black knights points', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; black knights points ; 4 }'}, 'date'], 'result': 'oct 20', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; black knights points ; 4 } ; date }'}, 'oct 20'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; black knights points ; 4 } ; date } ; oct 20 } = true', 'tointer': 'select the row whose black knights points record of all rows is 4th minimum . the date record of this row is oct 20 .'} | eq { hop { nth_argmin { all_rows ; black knights points ; 4 } ; date } ; oct 20 } = true | select the row whose black knights points record of all rows is 4th minimum . the date record of this row is oct 20 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'black knights points_5': 5, '4_6': 6, 'date_7': 7, 'oct 20_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', 'black knights points_5': 'black knights points', '4_6': '4', 'date_7': 'date', 'oct 20_8': 'oct 20'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'black knights points_5': [0], '4_6': [0], 'date_7': [1], 'oct 20_8': [2]} | ['game', 'date', 'opponent', 'result', 'black knights points', 'opponents', 'record'] | [['1', 'sept 29', 'boston university', 'win', '35', '0', '1 - 0'], ['2', 'oct 6', 'southern methodist', 'win', '14', '13', '2 - 0'], ['3', 'oct 13', 'providence college', 'win', '44', '0', '3 - 0'], ['4', 'oct 20', 'harvard', 'win', '15', '0', '4 - 0'], ['5', 'oct 27', 'yale', 'win', '18', '6', '5 - 0'], ['6', 'nov 3', 'depauw', 'win', '38', '12', '6 - 0'], ['7', 'nov 10', 'notre dame', 'loss', '6', '12', '6 - 1'], ['8', 'nov 17', 'carleton', 'win', '32', '7', '7 - 1'], ['9', 'nov 24', 'nebraska', 'win', '13', '3', '8 - 1']] |
karen kavaleryan | https://en.wikipedia.org/wiki/Karen_Kavaleryan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17632536-1.html.csv | unique | never let you go 2 is the only song that was composed by alexander lunyov . | {'scope': 'all', 'row': '2', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': 'alexander lunyov', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'composer', 'alexander lunyov'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose composer record fuzzily matches to alexander lunyov .', 'tostr': 'filter_eq { all_rows ; composer ; alexander lunyov }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; composer ; alexander lunyov } }', 'tointer': 'select the rows whose composer record fuzzily matches to alexander lunyov . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'composer', 'alexander lunyov'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose composer record fuzzily matches to alexander lunyov .', 'tostr': 'filter_eq { all_rows ; composer ; alexander lunyov }'}, 'song'], 'result': 'never let you go 2', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; composer ; alexander lunyov } ; song }'}, 'never let you go 2'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; composer ; alexander lunyov } ; song } ; never let you go 2 }', 'tointer': 'the song record of this unqiue row is never let you go 2 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; composer ; alexander lunyov } } ; eq { hop { filter_eq { all_rows ; composer ; alexander lunyov } ; song } ; never let you go 2 } } = true', 'tointer': 'select the rows whose composer record fuzzily matches to alexander lunyov . there is only one such row in the table . the song record of this unqiue row is never let you go 2 .'} | and { only { filter_eq { all_rows ; composer ; alexander lunyov } } ; eq { hop { filter_eq { all_rows ; composer ; alexander lunyov } ; song } ; never let you go 2 } } = true | select the rows whose composer record fuzzily matches to alexander lunyov . there is only one such row in the table . the song record of this unqiue row is never let you go 2 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'composer_7': 7, 'alexander lunyov_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'song_9': 9, 'never let you go 2_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'composer_7': 'composer', 'alexander lunyov_8': 'alexander lunyov', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'song_9': 'song', 'never let you go 2_10': 'never let you go 2'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'composer_7': [0], 'alexander lunyov_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'song_9': [2], 'never let you go 2_10': [3]} | ['year', 'song', 'artist', 'place', 'points', 'composer'] | [['2002', 'northern girl 1', 'prime minister', '10', '55', 'kim breitburg'], ['2006', 'never let you go 2', 'dima bilan', '2 ( sf : 3rd )', '248 ( sf : 217 )', 'alexander lunyov'], ['2007', 'work your magic', 'dmitry koldun', '6 ( sf : 4th )', '145 ( sf : 176 )', 'philipp kirkorov'], ['2007', 'anytime you need 3', 'hayko', '8 ( sf : - )', '138 ( sf : - )', 'hayko'], ['2008', 'shady lady', 'ani lorak', '2 ( sf : 1 )', '230 ( sf : 152 )', 'philipp kirkorov'], ['2008', 'peace will come', 'diana gurtskaya', '11 ( sf : 5 )', '83 ( sf : 107 )', 'kim breitburg'], ['2010', 'apricot stone', 'eva rivas', '7 ( sf :6 )', '141 ( sf :83 )', 'armen martirosyan'], ['2013', 'gravity', 'zlata ognevich', '3 ( sf :3 )', '214 ( sf :140 )', 'm nekrosov']] |
federal government college ikot ekpene | https://en.wikipedia.org/wiki/Federal_Government_College_Ikot_Ekpene | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11464746-1.html.csv | aggregation | the average foundation year of houses in the federal government college ikot ekpene is 1977 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1977', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'founded'], 'result': '1977', 'ind': 0, 'tostr': 'avg { all_rows ; founded }'}, '1977'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; founded } ; 1977 } = true', 'tointer': 'the average of the founded record of all rows is 1977 .'} | round_eq { avg { all_rows ; founded } ; 1977 } = true | the average of the founded record of all rows is 1977 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'founded_4': 4, '1977_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'founded_4': 'founded', '1977_5': '1977'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'founded_4': [0], '1977_5': [1]} | ['house name', 'composition', 'named after', 'founded', 'colours'] | [['benue', 'coed', 'river benue', '1973', 'yellow'], ['gongola', 'coed', 'gongola river', '1980', 'purple'], ['niger', 'coed', 'river niger', '1973', 'green'], ['rima', 'coed', 'rima river', '1980', 'brown'], ['ogun', 'coed', 'ogun river', '1980', 'blue']] |
matt baker ( television presenter ) | https://en.wikipedia.org/wiki/Matt_Baker_%28television_presenter%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1014319-1.html.csv | superlative | matt baker 's highest score from goodman was for the tango . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '12', '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', 'goodman'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; goodman }'}, 'dance / song'], 'result': 'tango / hung up', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; goodman } ; dance / song }'}, 'tango / hung up'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; goodman } ; dance / song } ; tango / hung up } = true', 'tointer': 'select the row whose goodman record of all rows is maximum . the dance / song record of this row is tango / hung up .'} | eq { hop { argmax { all_rows ; goodman } ; dance / song } ; tango / hung up } = true | select the row whose goodman record of all rows is maximum . the dance / song record of this row is tango / hung up . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'goodman_5': 5, 'dance / song_6': 6, 'tango / hung up_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'goodman_5': 'goodman', 'dance / song_6': 'dance / song', 'tango / hung up_7': 'tango / hung up'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'goodman_5': [0], 'dance / song_6': [1], 'tango / hung up_7': [2]} | ['week', 'dance / song', 'horwood', 'goodman', 'dixon', 'tonioli', 'total', 'result'] | [['1', "cha - cha - cha / ai n't no mountain high enough", '7', '8', '8', '8', '31', 'n / a'], ['2', 'foxtrot / she said', '7', '8', '8', '8', '31', 'safe'], ['3', 'quickstep / dreaming of you', '8', '7', '8', '8', '31', 'safe'], ['4', 'charleston / forty - second street', '9', '9', '9', '8', '35', 'safe'], ['5', 'argentine tango / bat out of hell', '8', '8', '9', '9', '34', 'safe'], ['6', 'viennese waltz / where the wild roses grow', '8', '9', '9', '9', '35', 'safe'], ['7', 'rumba / too lost in you', '8', '9', '9', '9', '35', 'safe'], ['8', 'samba / young hearts run free', '9', '9', '10', '10', '38', 'safe'], ['10', 'jive / soul bossa nova', '8', '9', '9', '9', '35', 'safe'], ['11', 'salsa / spinning around', '7', '7', '7', '7', '28', 'safe'], ['11', 'swing / in the mood', 'n / a', 'n / a', 'n / a', 'n / a', '2nd / 4 points', 'safe'], ['11', 'tango / hung up', '9', '10', '10', '9', '38', 'safe'], ['12', 'samba / young hearts run free', '9', '9', '10', '10', '38', 'second place'], ['12', 'showdance / i like the way ( you move )', '7', '9', '9', '9', '34', 'second place'], ['12', "paso doble / do n't let me be misunderstood", '9', '8', '9', '9', '35', 'second place']] |
sony xperia | https://en.wikipedia.org/wiki/Sony_Xperia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23556331-4.html.csv | ordinal | among sony xperia smartphone models sold under the sony brand , the one of the sixth-smallest display was released in mar. ' 12 . | {'row': '2', 'col': '9', 'order': '6', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'display', '6'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; display ; 6 }'}, 'release date'], 'result': '2012 - 03', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; display ; 6 } ; release date }'}, '2012 - 03'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; display ; 6 } ; release date } ; 2012 - 03 } = true', 'tointer': 'select the row whose display record of all rows is 6th minimum . the release date record of this row is 2012 - 03 .'} | eq { hop { nth_argmin { all_rows ; display ; 6 } ; release date } ; 2012 - 03 } = true | select the row whose display record of all rows is 6th minimum . the release date record of this row is 2012 - 03 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'display_5': 5, '6_6': 6, 'release date_7': 7, '2012 - 03_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', 'display_5': 'display', '6_6': '6', 'release date_7': 'release date', '2012 - 03_8': '2012 - 03'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'display_5': [0], '6_6': [0], 'release date_7': [1], '2012 - 03_8': [2]} | ['code name', 'market name', 'platform', 'release date', 'android version', 'system on chip', 'ram', 'rom', 'display', 'weight', 'battery ( mah )', 'bluetooth', 'wi - fi', 'nfc', 'camera', 'network'] | [['nozomi', 'xperia s', 'fuji', '2012 - 02', '2.3 / 4.0 / 4.1', '1.5 ghz qualcomm snapdragon s3 msm8260 , dual - core', '1 gb', '32 gb', '4.3 hd', '144 g', '1750', '2.1 + edr', '802.11 b / g / n', 'yes', 'rear : 12.1 mp front : 1.3 mp', 'gsm / hspa +'], ['aoba', 'xperia ion', 'fuji', '2012 - 03', '2.3 / 4.0 / 4.1', '1.5 ghz qualcomm snapdragon s3 apq8060 , dual - core', '1 gb', '16 gb', '4.55 hd', '144 g', '1900', '2.1 + edr', '802.11 b / g / n', 'yes', 'rear : 12 mp front : 1.3 mp', 'gsm / hspa + / lte'], ['hayate', 'xperia acro hd', 'fuji', '2013 - 03', '2.3 / 4.0', '1.5 ghz qualcomm snapdragon s3 msm8660 , dual - core', '1 gb', '11 gb', '4.3 hd', '149 g', '1900', '2.1', '802.11 b / g / n', 'no', 'rear : 12.1 mp front : 1.3 mp', 'cdma / gsm / hspa +'], ['hikari', 'xperia acro hd xperia acro s', 'fuji', '2013 - 03 ( hd ) 2012 - 08 ( s )', '2.3 / 4.0 / 4.1', '1.5 ghz qualcomm snapdragon s3 msm8260 , dual - core', '1 gb', '11 gb ( hd ) 16 gb ( s )', '4.3 hd', '149 g ( hd ) 147 g ( s )', '1910', '2.1 ( hd ) 3.0 ( s )', '802.11 b / g / n', 'yes', 'rear : 12.1 mp front : 1.3 mp', 'gsm / hspa +'], ['pepper', 'xperia sola', 'riogrande', '2012 - 03', '2.3 / 4.0', '1 ghz st - ericsson novathor u8500 , dual - core', '512 mb', '8 gb', '3.7 fwvga', '107 g', '1320', '2.1 + edr', '802.11 b / g / n', 'yes', '5 mp', 'gsm / w - cdma'], ['phoenix', 'xperia neo l', 'mogami', '2012 - 03', '4.0', '1 ghz qualcomm snapdragon s2 msm8255', '512 mb', '1 gb', '4 fwvga', '131.5 g', '1500', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 5 mp front : 0.3 mp', 'gsm / hspa'], ['nypon', 'xperia p', 'riogrande', '2012 - 04', '2.3 / 4.0 / 4.1', '1 ghz st - ericsson novathor u8500 , dual - core', '1 gb', '16 gb', '4 qhd', '126 g', '1305', '2.1 + edr', '802.11 b / g / n', 'yes', 'rear : 8 mp front : 0.3 mp', 'gsm / hspa +'], ['kumquat', 'xperia u', 'riogrande', '2012 - 05', '2.3 / 4.0', '1 ghz st - ericsson novathor u8500 , dual - core', '512 mb', '4 gb', '3.5 fwvga', '110 g', '1320', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 5 mp front : 0.3 mp', 'gsm / hspa +'], ['lotus', 'xperia go', 'riogrande', '2012 - 07', '2.3 / 4.0 / 4.1', '1 ghz st - ericsson novathor u8500 , dual - core', '512 mb', '8 gb', '3.5 hvga', '110 g', '1305', '3.0', '802.11 b / g / n', 'no', '5 mp', 'gsm / hspa +'], ['tapioca', 'xperia tipo xperia tipo dual', 'tamsui', '2012 - 08', '4.0', '800 mhz qualcomm snapdragon s1 msm7225a', '512 mb', '2.9 gb', '3.2 hvga', '0 99.4 g', '1500', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 3.2 mp front : 0.3 mp', 'gsm / hspa'], ['mesona', 'xperia miro', 'tamsui', '2012 - 09', '4.0', '800 mhz qualcomm snapdragon s1 msm7225a', '512 mb', '4 gb', '3.5 hvga', '110 g', '1500', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 5 mp front : 0.3 mp', 'gsm / hspa'], ['nozomi2', 'xperia sl', 'fuji', '2012 - 09', '2.3 / 4.0 / 4.1', '1.7 ghz qualcomm snapdragon s3 msm8260 , dual - core', '1 gb', '32 gb', '4.3 hd', '144 g', '1750', '3.0', '802.11 b / g / n', 'yes', 'rear : 12.1 mp front : 1.3 mp', 'gsm / hspa +'], ['jlo', 'xperia j', 'tamsui', '2012 - 10', '4.0 / 4.1', '1 ghz qualcomm snapdragon s1 msm7227a', '512 mb', '4 gb', '4 fwvga', '124 g', '1750', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 5 mp front : 0.3 mp', 'gsm / hspa'], ['nanhu', 'xperia e xperia e dual', 'tamsui', '2013 - 03', '4.0 / 4.1', '1 ghz qualcomm snapdragon s1 msm7227a', '512 mb', '4 gb', '3.5 hvga', '115.7 g', '1530', '2.1 + edr', '802.11 b / g / n', 'no', '3.2 mp', 'gsm / hspa']] |
sim kwon - ho | https://en.wikipedia.org/wiki/Sim_Kwon-Ho | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16680101-1.html.csv | majority | the majority of sim kwon-ho 's gold medal wins were at the 48 kg weight division . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '48 kg', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'class', '48 kg'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , most of them fuzzily match to 48 kg .', 'tostr': 'most_eq { all_rows ; class ; 48 kg } = true'} | most_eq { all_rows ; class ; 48 kg } = true | for the class records of all rows , most of them fuzzily match to 48 kg . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, '48 kg_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', '48 kg_4': '48 kg'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], '48 kg_4': [0]} | ['opponent', 'res', 'class', 'score', 'date', 'competition', 'notes'] | [['win', 'lã ¡ zaro rivas', '54 kg', '8:0', '2000 - 06 - 09', '2000 summer olympics', 'won second olympic gold medal'], ['win', 'shamseddin khudoyberdiev', '54 kg', '3:2', '1999 - 05 - 31', '1999 asian championships', 'won third asian championship gold medal'], ['win', 'kang yong - gyun', '54 kg', '5:5', '1998 - 12 - 13', '1998 asian games', 'won second asian games gold medal'], ['win', 'marian sandu', '54 kg', '5:3', '1998 - 08 - 30', '1998 world championships', 'won second world championship gold medal'], ['win', 'aleksandr pavlov', '48 kg', '4:0', '1996 - 07 - 21', '1996 summer olympics', 'won first olympic gold medal'], ['win', 'kang yong - gyun', '48 kg', '11:0', '1996 - 04 - 06', '1996 asian championships', 'won second asian championship gold medal'], ['win', 'hiroshi kado', '48 kg', '6:0', '1995 - 10 - 14', '1995 world championships', 'won first world championship gold medal'], ['win', 'dmitri korshunov', '48 kg', '12:0', '1995 - 06 - 28', '1995 asian championships', 'won first asian championship gold medal'], ['win', 'reza simkhah', '48 kg', '7:0', '1994 - 10 - 05', '1994 asian games', 'won first asian games gold medal']] |
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