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saturn aura | https://en.wikipedia.org/wiki/Saturn_Aura | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1373768-1.html.csv | comparative | both the saturn aura xe ( 2009 ) and the saturn aura xr ( 2009 ) have a 6 speed transmission . | {'row_1': '3', 'row_2': '5', 'col': '6', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'trim', 'xe ( 2009 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose trim record fuzzily matches to xe ( 2009 ) .', 'tostr': 'filter_eq { all_rows ; trim ; xe ( 2009 ) }'}, 'transmission'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission }', 'tointer': 'select the rows whose trim record fuzzily matches to xe ( 2009 ) . take the transmission record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'trim', 'xr ( 2009 )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose trim record fuzzily matches to xr ( 2009 ) .', 'tostr': 'filter_eq { all_rows ; trim ; xr ( 2009 ) }'}, 'transmission'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission }', 'tointer': 'select the rows whose trim record fuzzily matches to xr ( 2009 ) . take the transmission record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission } ; hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission } }', 'tointer': 'select the rows whose trim record fuzzily matches to xe ( 2009 ) . take the transmission record of this row . select the rows whose trim record fuzzily matches to xr ( 2009 ) . take the transmission record of this row . the first record fuzzily matches to the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'trim', 'xe ( 2009 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose trim record fuzzily matches to xe ( 2009 ) .', 'tostr': 'filter_eq { all_rows ; trim ; xe ( 2009 ) }'}, 'transmission'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission }', 'tointer': 'select the rows whose trim record fuzzily matches to xe ( 2009 ) . take the transmission record of this row .'}, '6 - speed 6t40'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission } ; 6 - speed 6t40 }', 'tointer': 'the transmission record of the first row is 6 - speed 6t40 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'trim', 'xr ( 2009 )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose trim record fuzzily matches to xr ( 2009 ) .', 'tostr': 'filter_eq { all_rows ; trim ; xr ( 2009 ) }'}, 'transmission'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission }', 'tointer': 'select the rows whose trim record fuzzily matches to xr ( 2009 ) . take the transmission record of this row .'}, '6 - speed 6t40'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission } ; 6 - speed 6t40 }', 'tointer': 'the transmission record of the second row is 6 - speed 6t40 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission } ; 6 - speed 6t40 } ; eq { hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission } ; 6 - speed 6t40 } }', 'tointer': 'the transmission record of the first row is 6 - speed 6t40 . the transmission record of the second row is 6 - speed 6t40 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission } ; hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission } } ; and { eq { hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission } ; 6 - speed 6t40 } ; eq { hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission } ; 6 - speed 6t40 } } } = true', 'tointer': 'select the rows whose trim record fuzzily matches to xe ( 2009 ) . take the transmission record of this row . select the rows whose trim record fuzzily matches to xr ( 2009 ) . take the transmission record of this row . the first record fuzzily matches to the second record . the transmission record of the first row is 6 - speed 6t40 . the transmission record of the second row is 6 - speed 6t40 .'} | and { eq { hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission } ; hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission } } ; and { eq { hop { filter_eq { all_rows ; trim ; xe ( 2009 ) } ; transmission } ; 6 - speed 6t40 } ; eq { hop { filter_eq { all_rows ; trim ; xr ( 2009 ) } ; transmission } ; 6 - speed 6t40 } } } = true | select the rows whose trim record fuzzily matches to xe ( 2009 ) . take the transmission record of this row . select the rows whose trim record fuzzily matches to xr ( 2009 ) . take the transmission record of this row . the first record fuzzily matches to the second record . the transmission record of the first row is 6 - speed 6t40 . the transmission record of the second row is 6 - speed 6t40 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'trim_11': 11, 'xe (2009)_12': 12, 'transmission_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'trim_15': 15, 'xr (2009)_16': 16, 'transmission_17': 17, 'and_7': 7, 'str_eq_5': 5, '6 - speed 6t40_18': 18, 'str_eq_6': 6, '6 - speed 6t40_19': 19} | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'trim_11': 'trim', 'xe (2009)_12': 'xe ( 2009 )', 'transmission_13': 'transmission', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'trim_15': 'trim', 'xr (2009)_16': 'xr ( 2009 )', 'transmission_17': 'transmission', 'and_7': 'and', 'str_eq_5': 'str_eq', '6 - speed 6t40_18': '6 - speed 6t40', 'str_eq_6': 'str_eq', '6 - speed 6t40_19': '6 - speed 6t40'} | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'trim_11': [0], 'xe (2009)_12': [0], 'transmission_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'trim_15': [1], 'xr (2009)_16': [1], 'transmission_17': [3], 'and_7': [8], 'str_eq_5': [7], '6 - speed 6t40_18': [5], 'str_eq_6': [7], '6 - speed 6t40_19': [6]} | ['trim', 'engine', 'displacement', 'power', 'torque', 'transmission', 'fuel mileage ( latest epa mpg - us )'] | [['green line', '2.4 l lat i4 ( bas hybrid )', 'cc ( cuin )', '164hp ( 124 kw )', 'n / a', '4 - speed 4t45 - e', '26 city , 34 hwy , 29 comb'], ['xe ( 2008 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '4 - speed 4t45 - e', '22 city , 30 hwy , 25 comb'], ['xe ( 2009 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '6 - speed 6t40', '22 city , 33 hwy , 26 comb'], ['xe ( 2007 - 08 )', '3.5 l lz4 v6', 'cc ( cuin )', '219hp ( 162 kw )', 'n / a', '4 - speed 4t45 - e', '18 city , 29 hwy , 22 comb'], ['xr ( 2009 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '6 - speed 6t40', '22 city , 33 hwy , 26 comb']] |
united states house of representatives elections , 1880 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1880 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431558-4.html.csv | comparative | john h evins was first elected to the united states house of representatives earlier than john s richardson . | {'row_1': '4', 'row_2': '1', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'john h evins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to john h evins .', 'tostr': 'filter_eq { all_rows ; incumbent ; john h evins }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; john h evins } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to john h evins . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'john s richardson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to john s richardson .', 'tostr': 'filter_eq { all_rows ; incumbent ; john s richardson }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; john s richardson } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to john s richardson . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; john h evins } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; john s richardson } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to john h evins . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to john s richardson . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; john h evins } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; john s richardson } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to john h evins . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to john s richardson . take the first elected record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'john h evins_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'john s richardson_12': 12, 'first elected_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'john h evins_8': 'john h evins', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'john s richardson_12': 'john s richardson', 'first elected_13': 'first elected'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'john h evins_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'john s richardson_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['south carolina 1', 'john s richardson', 'democratic', '1878', 're - elected'], ['south carolina 2', "michael p o'connor", 'democratic', '1878', 're - elected'], ['south carolina 3', 'd wyatt aiken', 'democratic', '1876', 're - elected'], ['south carolina 4', 'john h evins', 'democratic', '1876', 're - elected'], ['south carolina 5', 'george d tillman', 'democratic', '1878', 're - elected']] |
1921 grand prix season | https://en.wikipedia.org/wiki/1921_Grand_Prix_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18269311-2.html.csv | ordinal | eugenio silvani was the earliest racing winner in the 1921 grand prix season . | {'row': '1', 'col': '3', 'order': '1', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'winning driver'], 'result': 'eugenio silvani', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; winning driver }'}, 'eugenio silvani'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 1 } ; winning driver } ; eugenio silvani } = true', 'tointer': 'select the row whose date record of all rows is 1st minimum . the winning driver record of this row is eugenio silvani .'} | eq { hop { nth_argmin { all_rows ; date ; 1 } ; winning driver } ; eugenio silvani } = true | select the row whose date record of all rows is 1st minimum . the winning driver record of this row is eugenio silvani . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'winning driver_7': 7, 'eugenio silvani_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '1_6': '1', 'winning driver_7': 'winning driver', 'eugenio silvani_8': 'eugenio silvani'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'winning driver_7': [1], 'eugenio silvani_8': [2]} | ['name', 'circuit', 'date', 'winning driver', 'winning constructor', 'report'] | [['garda circuit', 'salã square', '22 may', 'eugenio silvani', 'bugatti', 'report'], ['targa florio', 'madonie', '29 may', 'giulio masetti', 'fiat', 'report'], ['coppa della cascine', 'florence', '6 june', 'deo', 'chiribiri', 'report'], ['mugello circuit', 'mugello', '24 july', 'giuseppe campari', 'alfa romeo', 'report'], ['coppa florio', 'brescia', '4 september', 'jules goux', 'ballot', 'report'], ['gentlemen grand prix', 'brescia', '11 september', 'giulio masetti', 'mercedes', 'report'], ['coppa montenero', 'montenero', '25 september', 'corrado lotti', 'ansaldo', 'report']] |
2007 - 08 san antonio spurs season | https://en.wikipedia.org/wiki/2007%E2%80%9308_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963601-10.html.csv | aggregation | the average number of high rebounds by the san antonio spurs was 13.8 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '13.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'high rebounds'], 'result': '13.8', 'ind': 0, 'tostr': 'avg { all_rows ; high rebounds }'}, '13.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; high rebounds } ; 13.8 } = true', 'tointer': 'the average of the high rebounds record of all rows is 13.8 .'} | round_eq { avg { all_rows ; high rebounds } ; 13.8 } = true | the average of the high rebounds record of all rows is 13.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'high rebounds_4': 4, '13.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'high rebounds_4': 'high rebounds', '13.8_5': '13.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'high rebounds_4': [0], '13.8_5': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 19', 'phoenix', '117 - 115 ( 2ot )', 'duncan ( 40 )', 'duncan ( 15 )', 'duncan , ginóbili , parker ( 5 )', 'at & t center 18797', '1 - 0'], ['2', 'april 22', 'phoenix', '102 - 96', 'parker ( 32 )', 'duncan ( 17 )', 'parker ( 7 )', 'at & t center 18797', '2 - 0'], ['3', 'april 25', 'phoenix', '115 - 99', 'parker ( 41 )', 'duncan ( 10 )', 'parker ( 12 )', 'us airways center 18422', '3 - 0'], ['4', 'april 27', 'phoenix', '86 - 105', 'parker ( 18 )', 'duncan ( 10 )', 'parker ( 3 )', 'us airways center 18422', '3 - 1'], ['5', 'april 29', 'phoenix', '92 - 87', 'parker ( 31 )', 'duncan ( 17 )', 'parker ( 8 )', 'at & t center 18797', '4 - 1']] |
cho kwang - rae | https://en.wikipedia.org/wiki/Cho_Kwang-Rae | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12513368-1.html.csv | count | cho kwang-rae played three games in the kuala lumpur venue . | {'scope': 'all', 'criterion': 'equal', 'value': 'kuala lumpur', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'kuala lumpur'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to kuala lumpur .', 'tostr': 'filter_eq { all_rows ; venue ; kuala lumpur }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; kuala lumpur } }', 'tointer': 'select the rows whose venue record fuzzily matches to kuala lumpur . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; kuala lumpur } } ; 3 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to kuala lumpur . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; venue ; kuala lumpur } } ; 3 } = true | select the rows whose venue record fuzzily matches to kuala lumpur . 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, 'venue_5': 5, 'kuala lumpur_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', 'venue_5': 'venue', 'kuala lumpur_6': 'kuala lumpur', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'kuala lumpur_6': [0], '3_7': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['july 22 , 1977', 'kuala lumpur', '1 goal', '5 - 1', '1977 merdeka cup'], ['july 26 , 1977', 'kuala lumpur', '1 goal', '4 - 0', '1977 merdeka cup'], ['july 12 , 1978', 'kuala lumpur', '1 goal', '4 - 0', '1978 merdeka cup'], ['december 10 , 1978', 'bangkok', '2 goals', '5 - 1', '1978 asian games'], ['september 8 , 1979', 'seoul', '1 goal', '8 - 0', "1979 president 's cup"], ['september 16 , 1979', 'incheon', '3 goals', '9 - 0', "1979 president 's cup"], ['august 29 , 1980', 'gwangju', '1 goal', '5 - 0', "1980 president 's cup"], ['june 10 , 1986', 'puebla', '1 goal ( og )', '2 - 3', '1986 fifa world cup'], ['october 3 , 1986', 'seoul', '1 goal', '4 - 0', '1986 asian games'], ['october 5 , 1986', 'seoul', '1 goal', '2 - 0', '1986 asian games']] |
miss namibia 2009 | https://en.wikipedia.org/wiki/Miss_Namibia_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23576576-2.html.csv | superlative | happie ntelamo is the tallest contestant in the miss namibia 2009 pageant . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'height ( in )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; height ( in ) }'}, 'contestant'], 'result': 'happie ntelamo', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; height ( in ) } ; contestant }'}, 'happie ntelamo'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; height ( in ) } ; contestant } ; happie ntelamo } = true', 'tointer': 'select the row whose height ( in ) record of all rows is maximum . the contestant record of this row is happie ntelamo .'} | eq { hop { argmax { all_rows ; height ( in ) } ; contestant } ; happie ntelamo } = true | select the row whose height ( in ) record of all rows is maximum . the contestant record of this row is happie ntelamo . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'height (in)_5': 5, 'contestant_6': 6, 'happie ntelamo_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'height (in)_5': 'height ( in )', 'contestant_6': 'contestant', 'happie ntelamo_7': 'happie ntelamo'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'height (in)_5': [0], 'contestant_6': [1], 'happie ntelamo_7': [2]} | ['represented', 'contestant', 'age', 'height ( in )', 'height ( cm )', 'hometown'] | [['caprivi', 'happie ntelamo', '21', "6 ' 1", '185', 'katima mulilo'], ['erongo', 'theodora amutjira', '18', "5 ' 8", '176', 'walvis bay'], ['karas', 'mari venter', '23', "5 ' 10", '179', 'swakopmund'], ['kavango', 'albertina shigwedha', '26', "5 ' 9", '177', 'rundu'], ['khomas', 'tanya schemmer', '19', "6 ' 0", '183', 'windhoek'], ['ohangwena', 'jayne david', '24', "5 ' 5", '166', 'eenhana'], ['omusati', 'susan van zyl', '20', "5 ' 11", '182', 'oshakati'], ['oshikoto', 'selma usiku', '22', "6 ' 0", '184', 'omuthiya'], ['swakopmund', 'daniella filipovic', '25', "5 ' 7", '172', 'swakopmund']] |
luca badoer | https://en.wikipedia.org/wiki/Luca_Badoer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226492-2.html.csv | unique | 1993 was the only year that luca badoer drove using a lola type chassis . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'lola', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'lola'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to lola .', 'tostr': 'filter_eq { all_rows ; chassis ; lola }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; chassis ; lola } }', 'tointer': 'select the rows whose chassis record fuzzily matches to lola . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'lola'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to lola .', 'tostr': 'filter_eq { all_rows ; chassis ; lola }'}, 'year'], 'result': '1993', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; chassis ; lola } ; year }'}, '1993'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; chassis ; lola } ; year } ; 1993 }', 'tointer': 'the year record of this unqiue row is 1993 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; chassis ; lola } } ; eq { hop { filter_eq { all_rows ; chassis ; lola } ; year } ; 1993 } } = true', 'tointer': 'select the rows whose chassis record fuzzily matches to lola . there is only one such row in the table . the year record of this unqiue row is 1993 .'} | and { only { filter_eq { all_rows ; chassis ; lola } } ; eq { hop { filter_eq { all_rows ; chassis ; lola } ; year } ; 1993 } } = true | select the rows whose chassis record fuzzily matches to lola . there is only one such row in the table . the year record of this unqiue row is 1993 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'chassis_7': 7, 'lola_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1993_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'chassis_7': 'chassis', 'lola_8': 'lola', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1993_10': '1993'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'chassis_7': [0], 'lola_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1993_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1993', 'lola bms scuderia italia', 'lola t93 / 30', 'ferrari 040 3.5 v12', '0'], ['1995', 'minardi scuderia italia', 'minardi m195', 'ford edm 3.0 v8', '0'], ['1996', 'forti grand prix', 'forti fg01b', 'ford eca zetec - r 3.0 v10', '0'], ['1996', 'forti grand prix', 'forti fg03', 'ford eca zetec - r 3.0 v10', '0'], ['1999', 'fondmetal minardi ford', 'minardi m01', 'ford vjm1 / vjm2 zetec - r 3.0 v10', '0'], ['2009', 'scuderia ferrari marlboro', 'ferrari f60', 'ferrari 056 2.4 v8', '0']] |
bernard ackah | https://en.wikipedia.org/wiki/Bernard_Ackah | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11690636-2.html.csv | aggregation | the average number of points bernard ackah scored in tokyo , japan is 3.5 . | {'scope': 'subset', 'col': '2', 'type': 'average', 'result': '3.5', 'subset': {'col': '8', 'criterion': 'equal', 'value': 'tokyo , japan'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'tokyo , japan'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; tokyo , japan }', 'tointer': 'select the rows whose location record fuzzily matches to tokyo , japan .'}, 'record'], 'result': '3.5', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; location ; tokyo , japan } ; record }'}, '3.5'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; location ; tokyo , japan } ; record } ; 3.5 } = true', 'tointer': 'select the rows whose location record fuzzily matches to tokyo , japan . the average of the record record of these rows is 3.5 .'} | round_eq { avg { filter_eq { all_rows ; location ; tokyo , japan } ; record } ; 3.5 } = true | select the rows whose location record fuzzily matches to tokyo , japan . the average of the record record of these rows is 3.5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'tokyo, japan_6': 6, 'record_7': 7, '3.5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'tokyo, japan_6': 'tokyo , japan', 'record_7': 'record', '3.5_8': '3.5'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'tokyo, japan_6': [0], 'record_7': [1], '3.5_8': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '5 - 3', 'minoru kato', 'decision ( unanimous )', 'deep : 47th impact', '2', '5:00', 'tokyo , japan'], ['win', '4 - 3', 'shunji kosaka', 'tko ( punches )', 'deep : cage impact 2009', '1', '0:34', 'tokyo , japan'], ['win', '3 - 3', 'ryåshi yanagisawa', 'tko ( head kick and punches )', 'deep : 43rd impact', '1', '0:07', 'tokyo , japan'], ['loss', '2 - 3', 'young choi', 'decision ( unanimous )', 'deep : 42nd impact', '2', '5:00', 'tokyo , japan'], ['loss', '2 - 2', "po'ai suganuma", 'submission ( armbar )', "hero 's 2007 in korea", '1', '3:05', 'seoul , south korea'], ['loss', '2 - 1', 'melvin manhoef', 'ko ( punches )', "hero 's 9", '1', '2:13', 'yokohama , japan'], ['win', '2 - 0', 'johnnie morton', 'ko ( punch )', 'dynamite !! usa', '1', '0:38', 'los angeles , california , usa'], ['win', '1 - 0', 'hyun pyo shin', 'tko ( punches )', "hero 's 8", '1', '1:11', 'nagoya , japan']] |
delaware valley collegiate hockey conference | https://en.wikipedia.org/wiki/Delaware_Valley_Collegiate_Hockey_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16432543-1.html.csv | count | there are 8 institutions which participated in the delaware valley collegiate hockey conference . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '8', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'institution'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record is arbitrary .', 'tostr': 'filter_all { all_rows ; institution }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; institution } }', 'tointer': 'select the rows whose institution record is arbitrary . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; institution } } ; 8 } = true', 'tointer': 'select the rows whose institution record is arbitrary . the number of such rows is 8 .'} | eq { count { filter_all { all_rows ; institution } } ; 8 } = true | select the rows whose institution record is arbitrary . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'institution_5': 5, '8_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'institution_5': 'institution', '8_6': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'institution_5': [0], '8_6': [2]} | ['institution', 'location', 'nickname', 'enrollment', 'established'] | [['university of delaware', 'newark , de', 'blue hens', '19391', '1743'], ['dickinson college', 'carlisle , pa', 'red devils', '2300', '1773'], ["mount saint mary 's university", 'emmitsburg , md', 'mountaineers', '2100', '1808'], ['penn state harrisburg', 'lower swatara township , pa', 'nittany lions', '4700', '1966'], ['rowan university', 'glassboro , nj', 'profs', '10483', '1923'], ['rutgers university - camden', 'camden , nj', 'raptors', '4497', '1766'], ['shippensburg university', 'shippensburg , pa', 'raiders', '6579', '1871'], ['widener university', 'philadelphia , pa', 'pride', '3204', '1862']] |
list of geological features on ganymede | https://en.wikipedia.org/wiki/List_of_geological_features_on_Ganymede | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16768245-5.html.csv | unique | arbera sulcus was the only geological feature on ganymede named after the assyrian town where ishtar was worshipped . | {'scope': 'all', 'row': '3', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'assyrian town where ishtar was worshipped', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'namesake', 'assyrian town where ishtar was worshipped'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose namesake record fuzzily matches to assyrian town where ishtar was worshipped .', 'tostr': 'filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped } }', 'tointer': 'select the rows whose namesake record fuzzily matches to assyrian town where ishtar was worshipped . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'namesake', 'assyrian town where ishtar was worshipped'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose namesake record fuzzily matches to assyrian town where ishtar was worshipped .', 'tostr': 'filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped }'}, 'name'], 'result': 'arbela sulcus', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped } ; name }'}, 'arbela sulcus'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped } ; name } ; arbela sulcus }', 'tointer': 'the name record of this unqiue row is arbela sulcus .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped } } ; eq { hop { filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped } ; name } ; arbela sulcus } } = true', 'tointer': 'select the rows whose namesake record fuzzily matches to assyrian town where ishtar was worshipped . there is only one such row in the table . the name record of this unqiue row is arbela sulcus .'} | and { only { filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped } } ; eq { hop { filter_eq { all_rows ; namesake ; assyrian town where ishtar was worshipped } ; name } ; arbela sulcus } } = true | select the rows whose namesake record fuzzily matches to assyrian town where ishtar was worshipped . there is only one such row in the table . the name record of this unqiue row is arbela sulcus . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'namesake_7': 7, 'assyrian town where ishtar was worshipped_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'arbela sulcus_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'namesake_7': 'namesake', 'assyrian town where ishtar was worshipped_8': 'assyrian town where ishtar was worshipped', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'arbela sulcus_10': 'arbela sulcus'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'namesake_7': [0], 'assyrian town where ishtar was worshipped_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'arbela sulcus_10': [3]} | ['name', 'latitude', 'longitude', 'diameter', 'year named', 'namesake'] | [['akitu sulcus', '38.9 n', '194.3 w', '365.0', '1997', "where marduk 's statue was carried each year"], ['apsu sulci', '39.4 s', '234.7 w', '1950.0', '1979', 'sumero - akkadian , primordial ocean'], ['arbela sulcus', '21.1 s', '349.8 w', '1940.0', '1985', 'assyrian town where ishtar was worshipped'], ['bubastis sulci', '72.3 s', '282.9 w', '2651.0', '1988', 'town in egypt where bast was worshipped'], ['dukug sulcus', '83.5 n', '3.8 w', '385.0', '1985', 'sumerian holy cosmic chamber of the gods'], ['erech sulcus', '7.3 s', '179.2 w', '953.0', '1985', 'akkadian town that was built by marduk'], ['harpagia sulcus', '11.7 s', '318.7 w', '1792.0', '1985', 'greek , where ganymede was abducted an eagle'], ['hursag sulcus', '9.7 s', '233.1 w', '750.0', '1985', 'sumerian mountain where winds dwell'], ['lagash sulcus', '10.9 s', '163.2 w', '1575.0', '1985', 'early babylonian town'], ['larsa sulcus', '3.8 n', '248.7 w', '1000.0', '2000', 'sumerian town'], ['mysia sulci', '7.0 s', '7.9 w', '5066.0', '1979', 'greek , where ganymede was abducted by an eagle'], ['nineveh sulcus', '23.5 n', '53.1 w', '1700.0', '1997', 'city where ishtar was worshipped'], ['nippur sulcus', '36.9 n', '185.0 w', '1425.0', '1985', 'sumerian city'], ['philae sulcus', '65.5 n', '169.0 w', '900.0', '1997', 'temple that was the chief sanctuary of isis'], ['sippar sulcus', '15.4 s', '189.3 w', '1508.0', '1985', 'ancient babylonian town'], ['umma sulcus', '4.1 n', '250.0 w', '1270.0', '2000', 'sumerian town'], ['ur sulcus', '49.8 n', '177.5 w', '1145.0', '1985', 'ancient sumerian seat of moon worship']] |
1954 vfl season | https://en.wikipedia.org/wiki/1954_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-11.html.csv | count | in the 1954 vfl season , when the away team 's score is over 11 , there were 4 times when the crowd size was under 20000 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '20000', 'result': '4', 'col': '6', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '11'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'away team score', '11'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; away team score ; 11 }', 'tointer': 'select the rows whose away team score record is greater than 11 .'}, 'crowd', '20000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose away team score record is greater than 11 . among these rows , select the rows whose crowd record is less than 20000 .', 'tostr': 'filter_less { filter_greater { all_rows ; away team score ; 11 } ; crowd ; 20000 }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_less { filter_greater { all_rows ; away team score ; 11 } ; crowd ; 20000 } }', 'tointer': 'select the rows whose away team score record is greater than 11 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_greater { all_rows ; away team score ; 11 } ; crowd ; 20000 } } ; 4 } = true', 'tointer': 'select the rows whose away team score record is greater than 11 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 4 .'} | eq { count { filter_less { filter_greater { all_rows ; away team score ; 11 } ; crowd ; 20000 } } ; 4 } = true | select the rows whose away team score record is greater than 11 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'away team score_6': 6, '11_7': 7, 'crowd_8': 8, '20000_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'away team score_6': 'away team score', '11_7': '11', 'crowd_8': 'crowd', '20000_9': '20000', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'away team score_6': [0], '11_7': [0], 'crowd_8': [1], '20000_9': [1], '4_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '15.15 ( 105 )', 'north melbourne', '11.6 ( 72 )', 'mcg', '18180', '3 july 1954'], ['essendon', '13.9 ( 87 )', 'richmond', '13.6 ( 84 )', 'windy hill', '28000', '3 july 1954'], ['collingwood', '12.10 ( 82 )', 'footscray', '10.12 ( 72 )', 'victoria park', '40000', '3 july 1954'], ['carlton', '9.16 ( 70 )', 'st kilda', '12.10 ( 82 )', 'princes park', '15000', '3 july 1954'], ['south melbourne', '9.10 ( 64 )', 'geelong', '17.12 ( 114 )', 'lake oval', '18000', '3 july 1954'], ['hawthorn', '11.15 ( 81 )', 'fitzroy', '11.10 ( 76 )', 'glenferrie oval', '12000', '3 july 1954']] |
forbes global 2000 | https://en.wikipedia.org/wiki/Forbes_Global_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1682026-1.html.csv | count | two of the companies on the forbes global 2000 are headquartered in the united kingdom . | {'scope': 'all', 'criterion': 'equal', 'value': 'united kingdom', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'headquarters', 'united kingdom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose headquarters record fuzzily matches to united kingdom .', 'tostr': 'filter_eq { all_rows ; headquarters ; united kingdom }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; headquarters ; united kingdom } }', 'tointer': 'select the rows whose headquarters record fuzzily matches to united kingdom . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; headquarters ; united kingdom } } ; 2 } = true', 'tointer': 'select the rows whose headquarters record fuzzily matches to united kingdom . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; headquarters ; united kingdom } } ; 2 } = true | select the rows whose headquarters record fuzzily matches to united kingdom . 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, 'headquarters_5': 5, 'united kingdom_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', 'headquarters_5': 'headquarters', 'united kingdom_6': 'united kingdom', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'headquarters_5': [0], 'united kingdom_6': [0], '2_7': [2]} | ['rank', 'company', 'headquarters', 'industry', 'sales ( billion )', 'profits ( billion )', 'assets ( billion )', 'market value ( billion )'] | [['01 1', 'icbc', 'china', 'banking', '134.8', '37.8', '2813.5', '237.3'], ['02 2', 'china construction bank', 'china', 'banking', '113.1', '30.6', '2241.0', '202.0'], ['03 3', 'jpmorgan chase', 'united states', 'banking', '108.2', '21.3', '2359.1', '191.4'], ['04 4', 'general electric', 'united states', 'conglomerate', '147.4', '13.6', '685.3', '243.7'], ['05 5', 'exxon mobil', 'united states', 'oil and gas', '420.7', '44.9', '333.8', '400.4'], ['06 6', 'hsbc', 'united kingdom', 'banking', '104.9', '14.3', '2684.1', '201.3'], ['07 7', 'royal dutch shell', 'netherlands', 'oil and gas', '467.2', '26.6', '360.3', '213.1'], ['08 8', 'agricultural bank of china', 'china', 'banking', '103.0', '23.0', '2124.2', '150.8'], ['09 9', 'berkshire hathaway', 'united states', 'conglomerate', '162.5', '14.8', '427.5', '252.8'], ['09 9', 'petrochina', 'china', 'oil and gas', '308.9', '18.3', '347.8', '261.2'], ['11 11', 'bank of china', 'china', 'banking', '98.1', '22.1', '2033.8', '131.7'], ['12 12', 'wells fargo', 'united states', 'banking', '91.2', '18.9', '1423.0', '201.3'], ['13 13', 'chevron', 'united states', 'oil and gas', '222.6', '26.2', '233.0', '232.5'], ['14 14', 'volkswagen group', 'germany', 'automotive', '254.0', '28.6', '408.2', '94.4'], ['15 15', 'apple', 'united states', 'computer hardware', '164.7', '41.7', '196.1', '416.6'], ['15 15', 'wal - mart stores', 'united states', 'retail', '469.2', '17.0', '203.1', '242.5'], ['17 17', 'gazprom', 'russia', 'oil and gas', '144.0', '40.6', '339.3', '111.4'], ['18 18', 'bp', 'united kingdom', 'oil and gas', '370.9', '11.6', '301.0', '130.4'], ['19 19', 'citigroup', 'united states', 'banking', '90.7', '7.5', '1864.7', '143.6'], ['20 20', 'petrobras', 'brazil', 'oil and gas', '144.1', '11.0', '331.6', '120.7']] |
federal league ( ohsaa ) | https://en.wikipedia.org/wiki/Federal_League_%28OHSAA%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26466528-1.html.csv | comparative | in the federal league , jackson joined twenty three years before lake . | {'row_1': '4', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '23 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'jackson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to jackson .', 'tostr': 'filter_eq { all_rows ; school ; jackson }'}, 'join date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; jackson } ; join date }', 'tointer': 'select the rows whose school record fuzzily matches to jackson . take the join date record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'lake'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose school record fuzzily matches to lake .', 'tostr': 'filter_eq { all_rows ; school ; lake }'}, 'join date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; school ; lake } ; join date }', 'tointer': 'select the rows whose school record fuzzily matches to lake . take the join date record of this row .'}], 'result': '-23 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; school ; jackson } ; join date } ; hop { filter_eq { all_rows ; school ; lake } ; join date } }'}, '-23 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; school ; jackson } ; join date } ; hop { filter_eq { all_rows ; school ; lake } ; join date } } ; -23 years } = true', 'tointer': 'select the rows whose school record fuzzily matches to jackson . take the join date record of this row . select the rows whose school record fuzzily matches to lake . take the join date record of this row . the second record is 23 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; school ; jackson } ; join date } ; hop { filter_eq { all_rows ; school ; lake } ; join date } } ; -23 years } = true | select the rows whose school record fuzzily matches to jackson . take the join date record of this row . select the rows whose school record fuzzily matches to lake . take the join date record of this row . the second record is 23 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, 'school_8': 8, 'jackson_9': 9, 'join date_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'school_12': 12, 'lake_13': 13, 'join date_14': 14, '-23 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', 'school_8': 'school', 'jackson_9': 'jackson', 'join date_10': 'join date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'school_12': 'school', 'lake_13': 'lake', 'join date_14': 'join date', '-23 years_15': '-23 years'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'school_8': [0], 'jackson_9': [0], 'join date_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'school_12': [1], 'lake_13': [1], 'join date_14': [3], '-23 years_15': [5]} | ['school', 'nickname', 'location', 'colors', 'join date'] | [['canton mckinley', 'bulldogs', 'canton', 'red , black', '2003'], ['glenoak', 'golden eagles', 'canton', 'forest green , vegas gold', '1975'], ['hoover', 'vikings', 'north canton', 'black , orange', '1968'], ['jackson', 'polar bears', 'jackson township', 'purple , gold', '1964'], ['lake', 'blue streaks', 'uniontown', 'blue , red , white', '1987']] |
2005 texas rangers season | https://en.wikipedia.org/wiki/2005_Texas_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12125069-2.html.csv | ordinal | the game played on may 22 drew the second most attendance . | {'row': '3', 'col': '6', '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', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'may 22', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}, 'may 22'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; may 22 } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the date record of this row is may 22 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; may 22 } = true | select the row whose attendance record of all rows is 2nd maximum . the date record of this row is may 22 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'may 22_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'may 22_8': 'may 22'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'may 22_8': [2]} | ['date', 'winning team', 'score', 'winning pitcher', 'losing pitcher', 'attendance', 'location'] | [['may 20', 'texas', '7 - 3', 'kenny rogers', 'brandon backe', '38109', 'arlington'], ['may 21', 'texas', '18 - 3', 'chris young', 'ezequiel astacio', '35781', 'arlington'], ['may 22', 'texas', '2 - 0', 'chan ho park', 'roy oswalt', '40583', 'arlington'], ['june 24', 'houston', '5 - 2', 'roy oswalt', 'ricardo rodríguez', '36199', 'houston'], ['june 25', 'texas', '6 - 5', 'chris young', 'brandon backe', '41868', 'houston']] |
united states house of representatives elections , 1984 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1984 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341598-14.html.csv | majority | among the incumbent that were re-elected in the 1984 house of representative election , most of them were first elected after 1960 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1960', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'first elected', '1960'], 'result': True, 'ind': 0, 'tointer': 'for the first elected records of all rows , most of them are greater than 1960 .', 'tostr': 'most_greater { all_rows ; first elected ; 1960 } = true'} | most_greater { all_rows ; first elected ; 1960 } = true | for the first elected records of all rows , most of them are greater than 1960 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'first elected_3': 3, '1960_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'first elected_3': 'first elected', '1960_4': '1960'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'first elected_3': [0], '1960_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 2', 'gus savage', 'democratic', '1980', 're - elected', 'gus savage ( d ) 83.0 % dale f harman ( r ) 17.0 %'], ['illinois 3', 'marty russo', 'democratic', '1974', 're - elected', 'marty russo ( d ) 64.4 % richard d murphy ( r ) 35.6 %'], ['illinois 6', 'henry hyde', 'republican', '1974', 're - elected', 'henry hyde ( r ) 75.1 % robert h renshaw ( d ) 24.9 %'], ['illinois 7', 'cardiss collins', 'democratic', '1973', 're - elected', 'cardiss collins ( d ) 78.4 % james l bevel ( r ) 21.6 %'], ['illinois 9', 'sidney r yates', 'democratic', '1964', 're - elected', 'sidney r yates ( d ) 67.5 % herbert sohn ( r ) 32.5 %'], ['illinois 10', 'john e porter', 'republican', '1980', 're - elected', 'john e porter ( r ) 72.6 % ruth c braver ( d ) 27.4 %'], ['illinois 12', 'phil crane', 'republican', '1969', 're - elected', 'phil crane ( r ) 77.8 % edward j laflamme ( d ) 22.2 %'], ['illinois 14', 'tom corcoran', 'republican', '1976', 'retired to run for u s senate republican hold', 'john e grotberg ( r ) 62.2 % dan mcgrath ( d ) 37.8 %'], ['illinois 17', 'lane evans', 'democratic', '1982', 're - elected', 'lane evans ( d ) 56.7 % kenneth g mcmillan ( r ) 43.3 %'], ['illinois 19', 'dan crane', 'republican', '1978', 'lost re - election democratic gain', 'terry l bruce ( d ) 52.3 % dan crane ( r ) 47.7 %'], ['illinois 20', 'dick durbin', 'democratic', '1982', 're - elected', 'dick durbin ( d ) 61.3 % richard g austin ( r ) 38.7 %'], ['illinois 21', 'melvin price', 'democratic', '1944', 're - elected', 'melvin price ( d ) 60.2 % robert h gaffner ( r ) 39.8 %']] |
1999 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1999_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162128-2.html.csv | superlative | the highest total at the 1999 u.s. open belonged to tom kite . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'player'], 'result': 'tom kite', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; player }'}, 'tom kite'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; player } ; tom kite } = true', 'tointer': 'select the row whose total record of all rows is maximum . the player record of this row is tom kite .'} | eq { hop { argmax { all_rows ; total } ; player } ; tom kite } = true | select the row whose total record of all rows is maximum . the player record of this row is tom kite . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'player_6': 6, 'tom kite_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'player_6': 'player', 'tom kite_7': 'tom kite'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'player_6': [1], 'tom kite_7': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['payne stewart', 'united states', '1991', '279', '1', '1'], ['corey pavin', 'united states', '1995', '296', '+ 16', 't34'], ['lee janzen', 'united states', '1993 , 1998', '298', '+ 18', 't46'], ['tom watson', 'united states', '1982', '301', '+ 21', 't57'], ['tom kite', 'united states', '1992', '302', '+ 22', 't60']] |
2008 tennessee volunteers football team | https://en.wikipedia.org/wiki/2008_Tennessee_Volunteers_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15257210-5.html.csv | count | 7 players were selected as part of the 2008 tennessee volunteers football team . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '7', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'position'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record is arbitrary .', 'tostr': 'filter_all { all_rows ; position }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; position } }', 'tointer': 'select the rows whose position record is arbitrary . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; position } } ; 7 } = true', 'tointer': 'select the rows whose position record is arbitrary . the number of such rows is 7 .'} | eq { count { filter_all { all_rows ; position } } ; 7 } = true | select the rows whose position record is arbitrary . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'position_5': 5, '7_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'position_5': 'position', '7_6': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'position_5': [0], '7_6': [2]} | ['position', 'number', 'name', 'height', 'weight', 'class', 'hometown', 'games'] | [['p', '95', 'chad cunningham', "6 ' 3", '210lb', 'rs - so', 'dawsonville , georgia', '0'], ['p', '47', 'britton colquitt', "6 ' 3", '205lb', 'rs - sr', 'knoxville , tennessee', '0'], ['pr', '41', 'dennis rogan', "5 ' 10", '175lb', 'so', 'knoxville , tennessee', '0'], ['ko', '26', 'daniel lincoln', "6 ' 0", '204lb', 'so', 'ocala , florida', '0'], ['kr', '41', 'dennis rogan', "5 ' 10", '175lb', 'so', 'knoxville , tennessee', '0'], ['kr', '3', 'lennon creer', "6 ' 1", '202lb', 'so', 'tatum , texas', '0'], ['pk', '26', 'daniel lincoln', "6 ' 0", '204lb', 'so', 'ocala , florida', '0']] |
1975 vfl season | https://en.wikipedia.org/wiki/1975_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10883333-2.html.csv | count | in the 1975 vfl season , among the games when home team scored above 15.12 , 3 of them had attendance over 17,500 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '17500', 'result': '3', 'col': '6', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '15.12'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '15.12'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; home team score ; 15.12 }', 'tointer': 'select the rows whose home team score record is greater than 15.12 .'}, 'crowd', '17500'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team score record is greater than 15.12 . among these rows , select the rows whose crowd record is greater than 17500 .', 'tostr': 'filter_greater { filter_greater { all_rows ; home team score ; 15.12 } ; crowd ; 17500 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_greater { filter_greater { all_rows ; home team score ; 15.12 } ; crowd ; 17500 } }', 'tointer': 'select the rows whose home team score record is greater than 15.12 . among these rows , select the rows whose crowd record is greater than 17500 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_greater { all_rows ; home team score ; 15.12 } ; crowd ; 17500 } } ; 3 } = true', 'tointer': 'select the rows whose home team score record is greater than 15.12 . among these rows , select the rows whose crowd record is greater than 17500 . the number of such rows is 3 .'} | eq { count { filter_greater { filter_greater { all_rows ; home team score ; 15.12 } ; crowd ; 17500 } } ; 3 } = true | select the rows whose home team score record is greater than 15.12 . among these rows , select the rows whose crowd record is greater than 17500 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'home team score_6': 6, '15.12_7': 7, 'crowd_8': 8, '17500_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'home team score_6': 'home team score', '15.12_7': '15.12', 'crowd_8': 'crowd', '17500_9': '17500', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'home team score_6': [0], '15.12_7': [0], 'crowd_8': [1], '17500_9': [1], '3_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['carlton', '27.10 ( 172 )', 'collingwood', '10.19 ( 79 )', 'princes park', '38000', '12 april 1975'], ['north melbourne', '15.13 ( 103 )', 'melbourne', '16.9 ( 105 )', 'arden street oval', '14235', '12 april 1975'], ['st kilda', '11.15 ( 81 )', 'hawthorn', '17.19 ( 121 )', 'moorabbin oval', '18465', '12 april 1975'], ['richmond', '15.22 ( 112 )', 'geelong', '10.12 ( 72 )', 'mcg', '33600', '12 april 1975'], ['footscray', '17.14 ( 116 )', 'fitzroy', '11.17 ( 83 )', 'western oval', '17700', '12 april 1975'], ['south melbourne', '15.12 ( 102 )', 'essendon', '19.17 ( 131 )', 'lake oval', '17466', '12 april 1975']] |
fiba africa clubs champions cup | https://en.wikipedia.org/wiki/FIBA_Africa_Clubs_Champions_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12965873-1.html.csv | superlative | primeiro de agosto is the club that has the highest number of total finals in the fiba africa clubs champions cup . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total finals'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total finals }'}, 'clubs'], 'result': 'primeiro de agosto', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total finals } ; clubs }'}, 'primeiro de agosto'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total finals } ; clubs } ; primeiro de agosto } = true', 'tointer': 'select the row whose total finals record of all rows is maximum . the clubs record of this row is primeiro de agosto .'} | eq { hop { argmax { all_rows ; total finals } ; clubs } ; primeiro de agosto } = true | select the row whose total finals record of all rows is maximum . the clubs record of this row is primeiro de agosto . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total finals_5': 5, 'clubs_6': 6, 'primeiro de agosto_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total finals_5': 'total finals', 'clubs_6': 'clubs', 'primeiro de agosto_7': 'primeiro de agosto'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total finals_5': [0], 'clubs_6': [1], 'primeiro de agosto_7': [2]} | ['clubs', 'winners', 'runners - up', 'total finals', 'winnig years'] | [['primeiro de agosto', '7', '3', '10', '2002 , 2004 , 2007 , 2008 , 2009 , 2010 , 2012'], ['as forces armées', '3', '1', '4', '1975 , 1979 , 1981'], ['asec mimosas', '2', '2', '4', '1989 , 2000'], ['gezira sc', '2', '0', '2', '1994 , 1996'], ['hit trésor', '2', '0', '2', '1973 , 1976'], ['petro atlético', '1', '5', '6', '2006'], ['zamalek sc', '1', '3', '4', '1992'], ['es sahel', '1', '1', '2', '2011'], ['abidjan basket club', '1', '1', '2', '2005'], ["asc jeanne d'arc", '1', '1', '2', '1991'], ['as police', '1', '1', '2', '1983'], ['mas fez', '1', '0', '1', '1998'], ['al - ittihad alexandria', '1', '0', '1', '1987'], ['cd maxaquene', '1', '0', '1', '1985'], ['red star', '1', '0', '1', '1972']] |
1958 san francisco 49ers season | https://en.wikipedia.org/wiki/1958_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18589208-1.html.csv | comparative | the san francisco 49ers had a game against the green bay packers earlier than the baltimore colts . | {'row_1': '9', 'row_2': '10', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'green bay packers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers .', 'tostr': 'filter_eq { all_rows ; opponent ; green bay packers }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; green bay packers } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'baltimore colts'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to baltimore colts .', 'tostr': 'filter_eq { all_rows ; opponent ; baltimore colts }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; baltimore colts } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to baltimore colts . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; green bay packers } ; date } ; hop { filter_eq { all_rows ; opponent ; baltimore colts } ; date } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row . select the rows whose opponent record fuzzily matches to baltimore colts . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; green bay packers } ; date } ; hop { filter_eq { all_rows ; opponent ; baltimore colts } ; date } } = true | select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row . select the rows whose opponent record fuzzily matches to baltimore colts . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'green bay packers_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'baltimore colts_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'green bay packers_8': 'green bay packers', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'baltimore colts_12': 'baltimore colts', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'green bay packers_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'baltimore colts_12': [1], 'date_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 28 , 1958', 'pittsburgh steelers', 'w 23 - 20', '51856'], ['2', 'october 5 , 1958', 'los angeles rams', 'l 33 - 3', '59826'], ['3', 'october 12 , 1958', 'chicago bears', 'l 28 - 6', '45310'], ['4', 'october 19 , 1958', 'philadelphia eagles', 'w 30 - 24', '33110'], ['5', 'october 26 , 1958', 'chicago bears', 'l 27 - 14', '59441'], ['6', 'november 2 , 1958', 'detroit lions', 'w 24 - 21', '59350'], ['7', 'november 9 , 1958', 'los angeles rams', 'l 56 - 7', '95082'], ['8', 'november 16 , 1958', 'detroit lions', 'l 35 - 21', '54523'], ['9', 'november 23 , 1958', 'green bay packers', 'w 33 - 12', '43819'], ['10', 'november 30 , 1958', 'baltimore colts', 'l 35 - 27', '57557'], ['11', 'december 7 , 1958', 'green bay packers', 'w 48 - 21', '50793'], ['12', 'december 14 , 1958', 'baltimore colts', 'w 21 - 12', '58334']] |
f.c. halifax town | https://en.wikipedia.org/wiki/F.C._Halifax_Town | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18443295-5.html.csv | unique | for f.c. halifax town , the only time that ashley stott was the leading scorer was in 2008-09 . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'ashley stott', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'leading scorer', 'ashley stott'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose leading scorer record fuzzily matches to ashley stott .', 'tostr': 'filter_eq { all_rows ; leading scorer ; ashley stott }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; leading scorer ; ashley stott } }', 'tointer': 'select the rows whose leading scorer record fuzzily matches to ashley stott . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'leading scorer', 'ashley stott'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose leading scorer record fuzzily matches to ashley stott .', 'tostr': 'filter_eq { all_rows ; leading scorer ; ashley stott }'}, 'year'], 'result': '2008 - 09', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; leading scorer ; ashley stott } ; year }'}, '2008 - 09'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; leading scorer ; ashley stott } ; year } ; 2008 - 09 }', 'tointer': 'the year record of this unqiue row is 2008 - 09 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; leading scorer ; ashley stott } } ; eq { hop { filter_eq { all_rows ; leading scorer ; ashley stott } ; year } ; 2008 - 09 } } = true', 'tointer': 'select the rows whose leading scorer record fuzzily matches to ashley stott . there is only one such row in the table . the year record of this unqiue row is 2008 - 09 .'} | and { only { filter_eq { all_rows ; leading scorer ; ashley stott } } ; eq { hop { filter_eq { all_rows ; leading scorer ; ashley stott } ; year } ; 2008 - 09 } } = true | select the rows whose leading scorer record fuzzily matches to ashley stott . there is only one such row in the table . the year record of this unqiue row is 2008 - 09 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'leading scorer_7': 7, 'ashley stott_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'year_9': 9, '2008 - 09_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'leading scorer_7': 'leading scorer', 'ashley stott_8': 'ashley stott', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'year_9': 'year', '2008 - 09_10': '2008 - 09'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'leading scorer_7': [0], 'ashley stott_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'year_9': [2], '2008 - 09_10': [3]} | ['year', 'league', 'position', 'leading scorer', 'fa cup', 'fa trophy'] | [['2008 - 09', 'northern premier league division one north', '8 / 21', 'ashley stott ( 20 )', 'qr2', 'pr'], ['2009 - 10', 'northern premier league division one north', '1 / 22 promoted', 'james dean ( 27 )', 'qr4', 'qr3'], ['2010 - 11', 'northern premier league premier division', '1 / 22 promoted', 'jamie vardy ( 25 )', 'qr4', 'qr2'], ['2011 - 12', 'conference north', '3 / 22', 'lee gregory ( 20 )', 'r1', 'qr3'], ['2012 - 13', 'conference north', '5 / 22 promoted', 'lee gregory ( 22 )', 'qr4', 'qf'], ['2013 - 14', 'conference premier', '11 / 24', 'lee gregory ( 8 )', 'r1', 'n / a']] |
1972 san francisco 49ers season | https://en.wikipedia.org/wiki/1972_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16714074-2.html.csv | unique | in the 1972 san francisco 49ers season , when the 49ers won , the only time the opponent was the san diego chargers was on september 17 . | {'scope': 'subset', 'row': '1', 'col': '3', 'col_other': '2,4', 'criterion': 'equal', 'value': 'san diego chargers', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'w'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; w }', 'tointer': 'select the rows whose result record fuzzily matches to w .'}, 'opponent', 'san diego chargers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose result record fuzzily matches to w . among these rows , select the rows whose opponent record fuzzily matches to san diego chargers .', 'tostr': 'filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers } }', 'tointer': 'select the rows whose result record fuzzily matches to w . among these rows , select the rows whose opponent record fuzzily matches to san diego chargers . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; w }', 'tointer': 'select the rows whose result record fuzzily matches to w .'}, 'opponent', 'san diego chargers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose result record fuzzily matches to w . among these rows , select the rows whose opponent record fuzzily matches to san diego chargers .', 'tostr': 'filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers }'}, 'date'], 'result': 'september 17 , 1972', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers } ; date }'}, 'september 17 , 1972'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers } ; date } ; september 17 , 1972 }', 'tointer': 'the date record of this unqiue row is september 17 , 1972 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers } } ; eq { hop { filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers } ; date } ; september 17 , 1972 } } = true', 'tointer': 'select the rows whose result record fuzzily matches to w . among these rows , select the rows whose opponent record fuzzily matches to san diego chargers . there is only one such row in the table . the date record of this unqiue row is september 17 , 1972 .'} | and { only { filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers } } ; eq { hop { filter_eq { filter_eq { all_rows ; result ; w } ; opponent ; san diego chargers } ; date } ; september 17 , 1972 } } = true | select the rows whose result record fuzzily matches to w . among these rows , select the rows whose opponent record fuzzily matches to san diego chargers . there is only one such row in the table . the date record of this unqiue row is september 17 , 1972 . | 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, 'result_8': 8, 'w_9': 9, 'opponent_10': 10, 'san diego chargers_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'date_12': 12, 'september 17 , 1972_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', 'result_8': 'result', 'w_9': 'w', 'opponent_10': 'opponent', 'san diego chargers_11': 'san diego chargers', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'date_12': 'date', 'september 17 , 1972_13': 'september 17 , 1972'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'result_8': [0], 'w_9': [0], 'opponent_10': [1], 'san diego chargers_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'date_12': [3], 'september 17 , 1972_13': [4]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 17 , 1972', 'san diego chargers', 'w 34 - 3', '59438'], ['2', 'september 24 , 1972', 'buffalo bills', 'l 27 - 20', '45845'], ['3', 'october 1 , 1972', 'new orleans saints', 'w 37 - 2', '69840'], ['4', 'october 8 , 1972', 'los angeles rams', 'l 31 - 7', '77382'], ['5', 'october 15 , 1972', 'new york giants', 'l 23 - 17', '58606'], ['6', 'october 22 , 1972', 'new orleans saints', 't 20 - 20', '59167'], ['7', 'october 29 , 1972', 'atlanta falcons', 'w 49 - 14', '58850'], ['8', 'november 5 , 1972', 'green bay packers', 'l 34 - 24', '47897'], ['9', 'november 12 , 1972', 'baltimore colts', 'w 24 - 21', '61214'], ['10', 'november 19 , 1972', 'chicago bears', 'w 34 - 21', '55701'], ['11', 'november 23 , 1972', 'dallas cowboys', 'w 31 - 10', '65124'], ['12', 'december 4 , 1972', 'los angeles rams', 'l 26 - 16', '61214'], ['13', 'december 10 , 1972', 'atlanta falcons', 'w 20 - 0', '61214'], ['14', 'december 16 , 1972', 'minnesota vikings', 'w 20 - 17', '61214']] |
2008 - 09 denver nuggets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Denver_Nuggets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17355408-4.html.csv | unique | in the 2008 - 09 denver nuggets season , only one game played in pepsi center attracted more than 19,500 people . | {'scope': 'subset', 'row': '1', 'col': '8', 'col_other': 'n/a', 'criterion': 'greater_than', 'value': '19,500', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'pepsi center'}} | {'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'pepsi center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; pepsi center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to pepsi center .'}, 'location attendance', '19,500'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location attendance record fuzzily matches to pepsi center . among these rows , select the rows whose location attendance record is greater than 19,500 .', 'tostr': 'filter_greater { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance ; 19,500 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance ; 19,500 } } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to pepsi center . among these rows , select the rows whose location attendance record is greater than 19,500 . there is only one such row in the table .'} | only { filter_greater { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance ; 19,500 } } = true | select the rows whose location attendance record fuzzily matches to pepsi center . among these rows , select the rows whose location attendance record is greater than 19,500 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'pepsi center_6': 6, 'location attendance_7': 7, '19,500_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'pepsi center_6': 'pepsi center', 'location attendance_7': 'location attendance', '19,500_8': '19,500'} | {'only_2': [3], 'result_3': [], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'pepsi center_6': [0], 'location attendance_7': [1], '19,500_8': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['3', 'november 1', 'la lakers', 'l 97 - 104 ( ot )', 'anthony carter ( 20 )', 'chris andersen ( 7 )', 'allen iverson ( 7 )', 'pepsi center 19651', '1 - 2'], ['4', 'november 5', 'golden state', 'l 101 - 111 ( ot )', 'carmelo anthony ( 28 )', 'nenê ( 15 )', 'anthony carter ( 11 )', 'oracle arena 18194', '1 - 3'], ['5', 'november 7', 'dallas', 'w 108 - 105 ( ot )', 'carmelo anthony ( 28 )', 'carmelo anthony ( 8 )', 'anthony carter ( 7 )', 'pepsi center 19175', '2 - 3'], ['6', 'november 9', 'memphis', 'w 100 - 90 ( ot )', 'carmelo anthony ( 24 )', 'nenê ( 12 )', 'chauncey billups ( 10 )', 'pepsi center 14359', '3 - 3'], ['7', 'november 11', 'charlotte', 'w 88 - 80 ( ot )', 'carmelo anthony ( 25 )', 'nenê , linas kleiza ( 8 )', 'anthony carter ( 6 )', 'time warner cable arena 10753', '4 - 3'], ['8', 'november 13', 'cleveland', 'l 99 - 110 ( ot )', 'chauncey billups ( 26 )', 'kenyon martin ( 10 )', 'chauncey billups ( 6 )', 'quicken loans arena 20562', '4 - 4'], ['9', 'november 14', 'boston', 'w 94 - 85 ( ot )', 'chauncey billups , carmelo anthony ( 18 )', 'carmelo anthony ( 13 )', 'chauncey billups ( 7 )', 'td banknorth garden 18624', '5 - 4'], ['10', 'november 16', 'minnesota', 'w 90 - 84 ( ot )', 'chauncey billups ( 26 )', 'carmelo anthony ( 12 )', 'chauncey billups ( 5 )', 'pepsi center 16721', '6 - 4'], ['11', 'november 18', 'milwaukee', 'w 114 - 105 ( ot )', 'linas kleiza ( 25 )', 'nenê ( 6 )', 'chauncey billups ( 5 )', 'pepsi center 14413', '7 - 4'], ['12', 'november 19', 'san antonio', 'w 91 - 81 ( ot )', 'chauncey billups ( 22 )', 'carmelo anthony , nenê ( 9 )', 'carmelo anthony ( 7 )', 'at & t center 16559', '8 - 4'], ['13', 'november 21', 'la lakers', 'l 90 - 104 ( ot )', 'j r smith , nenê ( 18 )', 'carmelo anthony ( 10 )', 'chauncey billups ( 9 )', 'staples center 18997', '8 - 5'], ['14', 'november 23', 'chicago', 'w 114 - 101 ( ot )', 'kenyon martin ( 26 )', 'carmelo anthony ( 13 )', 'chauncey billups , carmelo anthony ( 8 )', 'pepsi center 16202', '9 - 5'], ['15', 'november 26', 'la clippers', 'w 106 - 105 ( ot )', 'carmelo anthony ( 30 )', 'carmelo anthony ( 11 )', 'chauncey billups ( 11 )', 'staples center 14934', '10 - 5'], ['16', 'november 27', 'new orleans', 'l 101 - 105 ( ot )', 'j r smith ( 32 )', 'chris andersen ( 8 )', 'anthony carter ( 8 )', 'pepsi center 15563', '10 - 6'], ['17', 'november 29', 'minnesota', 'w 106 - 97 ( ot )', 'chauncey billups ( 27 )', 'carmelo anthony ( 10 )', 'chucky atkins ( 5 )', 'target center 14197', '11 - 6']] |
new zealand general election , 1931 | https://en.wikipedia.org/wiki/New_Zealand_general_election%2C_1931 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1189910-1.html.csv | count | in the new zealand general election in 1931 , when there were over 100000 votes , there were 3 times when there were over 20 seats . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '20', 'result': '3', 'col': '5', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '100000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'votes', '100000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; votes ; 100000 }', 'tointer': 'select the rows whose votes record is greater than 100000 .'}, 'seats', '20'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose votes record is greater than 100000 . among these rows , select the rows whose seats record is greater than 20 .', 'tostr': 'filter_greater { filter_greater { all_rows ; votes ; 100000 } ; seats ; 20 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_greater { filter_greater { all_rows ; votes ; 100000 } ; seats ; 20 } }', 'tointer': 'select the rows whose votes record is greater than 100000 . among these rows , select the rows whose seats record is greater than 20 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_greater { all_rows ; votes ; 100000 } ; seats ; 20 } } ; 3 } = true', 'tointer': 'select the rows whose votes record is greater than 100000 . among these rows , select the rows whose seats record is greater than 20 . the number of such rows is 3 .'} | eq { count { filter_greater { filter_greater { all_rows ; votes ; 100000 } ; seats ; 20 } } ; 3 } = true | select the rows whose votes record is greater than 100000 . among these rows , select the rows whose seats record is greater than 20 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'votes_6': 6, '100000_7': 7, 'seats_8': 8, '20_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'votes_6': 'votes', '100000_7': '100000', 'seats_8': 'seats', '20_9': '20', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'votes_6': [0], '100000_7': [0], 'seats_8': [1], '20_9': [1], '3_10': [3]} | ['party', 'leader', 'votes', 'percentage', 'seats'] | [['reform', 'gordon coates', '190170', '54.03', '28'], ['united', 'george forbes', '120801', '54.03', '19'], ['28 independents ( in support of coalition )', '28 independents ( in support of coalition )', '75069', '54.03', '4'], ['labour', 'harry holland', '244867', '34.27', '24'], ['country party', 'harold rushworth', '16710', '2.34', '1'], ['41 independents ( including harry atmore )', '41 independents ( including harry atmore )', '66894', '9.36', '4'], ['coalition win', 'total votes', '714511', '100 %', '80']] |
iberian peninsula | https://en.wikipedia.org/wiki/Iberian_Peninsula | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14883-2.html.csv | comparative | there are more people living in madrid than there are living in porto . | {'row_1': '1', 'row_2': '4', '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', 'urban area', 'madrid'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose urban area record fuzzily matches to madrid .', 'tostr': 'filter_eq { all_rows ; urban area ; madrid }'}, 'population'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; urban area ; madrid } ; population }', 'tointer': 'select the rows whose urban area record fuzzily matches to madrid . take the population record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'urban area', 'porto'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose urban area record fuzzily matches to porto .', 'tostr': 'filter_eq { all_rows ; urban area ; porto }'}, 'population'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; urban area ; porto } ; population }', 'tointer': 'select the rows whose urban area record fuzzily matches to porto . take the population record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; urban area ; madrid } ; population } ; hop { filter_eq { all_rows ; urban area ; porto } ; population } } = true', 'tointer': 'select the rows whose urban area record fuzzily matches to madrid . take the population record of this row . select the rows whose urban area record fuzzily matches to porto . take the population record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; urban area ; madrid } ; population } ; hop { filter_eq { all_rows ; urban area ; porto } ; population } } = true | select the rows whose urban area record fuzzily matches to madrid . take the population record of this row . select the rows whose urban area record fuzzily matches to porto . take the population 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, 'urban area_7': 7, 'madrid_8': 8, 'population_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'urban area_11': 11, 'porto_12': 12, 'population_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', 'urban area_7': 'urban area', 'madrid_8': 'madrid', 'population_9': 'population', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'urban area_11': 'urban area', 'porto_12': 'porto', 'population_13': 'population'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'urban area_7': [0], 'madrid_8': [0], 'population_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'urban area_11': [1], 'porto_12': [1], 'population_13': [3]} | ['urban area', 'country', 'region', 'population', 'globalization index'] | [['madrid', 'spain', 'community of madrid', '6321398', 'alpha'], ['barcelona', 'spain', 'catalonia', '4604000', 'alpha -'], ['lisbon', 'portugal', 'lisbon region', '3035000', 'alpha -'], ['porto', 'portugal', 'norte region', '1676848', 'gamma -'], ['valencia', 'spain', 'community of valencia', '1564145', 'gamma']] |
2010 - 11 rugby - bundesliga | https://en.wikipedia.org/wiki/2010%E2%80%9311_Rugby-Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30153446-1.html.csv | unique | heidelberger rk was the only team to have won 15 games during the 2010-2011 season . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '15', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'won', '15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose won record is equal to 15 .', 'tostr': 'filter_eq { all_rows ; won ; 15 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; won ; 15 } }', 'tointer': 'select the rows whose won record is equal to 15 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'won', '15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose won record is equal to 15 .', 'tostr': 'filter_eq { all_rows ; won ; 15 }'}, 'club'], 'result': 'heidelberger rk', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; won ; 15 } ; club }'}, 'heidelberger rk'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; won ; 15 } ; club } ; heidelberger rk }', 'tointer': 'the club record of this unqiue row is heidelberger rk .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; won ; 15 } } ; eq { hop { filter_eq { all_rows ; won ; 15 } ; club } ; heidelberger rk } } = true', 'tointer': 'select the rows whose won record is equal to 15 . there is only one such row in the table . the club record of this unqiue row is heidelberger rk .'} | and { only { filter_eq { all_rows ; won ; 15 } } ; eq { hop { filter_eq { all_rows ; won ; 15 } ; club } ; heidelberger rk } } = true | select the rows whose won record is equal to 15 . there is only one such row in the table . the club record of this unqiue row is heidelberger rk . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'won_7': 7, '15_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'heidelberger rk_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'won_7': 'won', '15_8': '15', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'heidelberger rk_10': 'heidelberger rk'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'won_7': [0], '15_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'heidelberger rk_10': [3]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'difference', 'bonus points', 'points'] | [['1', 'heidelberger rk', '16', '15', '0', '1', '924', '120', '804', '15', '75'], ['2', 'sc 1880 frankfurt', '16', '14', '0', '2', '849', '237', '612', '12', '68'], ['3', 'tsv handschuhsheim', '16', '11', '0', '5', '468', '439', '29', '9', '53'], ['4', 'rg heidelberg', '16', '9', '0', '7', '512', '264', '248', '8', '44'], ['5', 'sc neuenheim', '16', '9', '0', '7', '380', '395', '- 15', '8', '44'], ['6', 'berliner rugby club', '16', '7', '0', '9', '281', '471', '- 190', '6', '34'], ['7', 'dsv 78 hannover', '16', '4', '0', '12', '265', '594', '- 329', '4', '20'], ['8', 'rk 03 berlin', '16', '2', '0', '14', '195', '688', '- 493', '2', '10']] |
1926 vfl season | https://en.wikipedia.org/wiki/1926_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-7.html.csv | ordinal | the third largest crowd for the vfl on 7 june 1926 numbered 20974 people . | {'row': '2', 'col': '6', 'order': '3', 'col_other': '7', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'crowd', '3'], 'result': '20974', 'ind': 0, 'tostr': 'nth_max { all_rows ; crowd ; 3 }', 'tointer': 'the 3rd maximum crowd record of all rows is 20974 .'}, '20974'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; crowd ; 3 } ; 20974 }', 'tointer': 'the 3rd maximum crowd record of all rows is 20974 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; crowd ; 3 }'}, 'date'], 'result': '7 june 1926', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 3 } ; date }'}, '7 june 1926'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; date } ; 7 june 1926 }', 'tointer': 'the date record of the row with 3rd maximum crowd record is 7 june 1926 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; crowd ; 3 } ; 20974 } ; eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; date } ; 7 june 1926 } } = true', 'tointer': 'the 3rd maximum crowd record of all rows is 20974 . the date record of the row with 3rd maximum crowd record is 7 june 1926 .'} | and { eq { nth_max { all_rows ; crowd ; 3 } ; 20974 } ; eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; date } ; 7 june 1926 } } = true | the 3rd maximum crowd record of all rows is 20974 . the date record of the row with 3rd maximum crowd record is 7 june 1926 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '3_9': 9, '20974_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'crowd_12': 12, '3_13': 13, 'date_14': 14, '7 june 1926_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '3_9': '3', '20974_10': '20974', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'crowd_12': 'crowd', '3_13': '3', 'date_14': 'date', '7 june 1926_15': '7 june 1926'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'crowd_8': [0], '3_9': [0], '20974_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'crowd_12': [2], '3_13': [2], 'date_14': [3], '7 june 1926_15': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '10.13 ( 73 )', 'richmond', '10.14 ( 74 )', 'arden street oval', '12000', '7 june 1926'], ['melbourne', '12.16 ( 88 )', 'south melbourne', '8.17 ( 65 )', 'mcg', '20974', '7 june 1926'], ['fitzroy', '11.15 ( 81 )', 'hawthorn', '14.12 ( 96 )', 'brunswick street oval', '8000', '7 june 1926'], ['geelong', '13.11 ( 89 )', 'essendon', '7.9 ( 51 )', 'corio oval', '25600', '7 june 1926'], ['st kilda', '9.12 ( 66 )', 'collingwood', '10.16 ( 76 )', 'junction oval', '24000', '7 june 1926'], ['footscray', '10.11 ( 71 )', 'carlton', '14.9 ( 93 )', 'western oval', '20000', '7 june 1926']] |
1970 vfl season | https://en.wikipedia.org/wiki/1970_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1164217-6.html.csv | unique | the only game in which the attendance was over 30000 was the melbourne game . | {'scope': 'all', 'row': '4', 'col': '6', 'col_other': '1', 'criterion': 'greater_than', 'value': '30000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '30000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is greater than 30000 .', 'tostr': 'filter_greater { all_rows ; crowd ; 30000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; crowd ; 30000 } }', 'tointer': 'select the rows whose crowd record is greater than 30000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '30000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is greater than 30000 .', 'tostr': 'filter_greater { all_rows ; crowd ; 30000 }'}, 'home team'], 'result': 'melbourne', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; crowd ; 30000 } ; home team }'}, 'melbourne'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; crowd ; 30000 } ; home team } ; melbourne }', 'tointer': 'the home team record of this unqiue row is melbourne .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; crowd ; 30000 } } ; eq { hop { filter_greater { all_rows ; crowd ; 30000 } ; home team } ; melbourne } } = true', 'tointer': 'select the rows whose crowd record is greater than 30000 . there is only one such row in the table . the home team record of this unqiue row is melbourne .'} | and { only { filter_greater { all_rows ; crowd ; 30000 } } ; eq { hop { filter_greater { all_rows ; crowd ; 30000 } ; home team } ; melbourne } } = true | select the rows whose crowd record is greater than 30000 . there is only one such row in the table . the home team record of this unqiue row is melbourne . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'crowd_7': 7, '30000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_9': 9, 'melbourne_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'crowd_7': 'crowd', '30000_8': '30000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_9': 'home team', 'melbourne_10': 'melbourne'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'crowd_7': [0], '30000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'home team_9': [2], 'melbourne_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['carlton', '23.9 ( 147 )', 'fitzroy', '15.20 ( 110 )', 'princes park', '20022', '9 may 1970'], ['south melbourne', '9.25 ( 79 )', 'st kilda', '9.8 ( 62 )', 'lake oval', '20312', '9 may 1970'], ['geelong', '18.15 ( 123 )', 'footscray', '11.11 ( 77 )', 'kardinia park', '21139', '9 may 1970'], ['melbourne', '10.12 ( 72 )', 'essendon', '7.15 ( 57 )', 'mcg', '34219', '9 may 1970'], ['north melbourne', '10.6 ( 66 )', 'collingwood', '17.30 ( 132 )', 'arden street oval', '20091', '9 may 1970'], ['hawthorn', '20.10 ( 130 )', 'richmond', '21.11 ( 137 )', 'vfl park', '26133', '9 may 1970']] |
sagarika ghatge | https://en.wikipedia.org/wiki/Sagarika_Ghatge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12807043-1.html.csv | unique | sagarika ghatge 's role of sonal was the only role that was in the marathi language . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'marathi', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'marathi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose language record fuzzily matches to marathi .', 'tostr': 'filter_eq { all_rows ; language ; marathi }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; language ; marathi } }', 'tointer': 'select the rows whose language record fuzzily matches to marathi . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'marathi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose language record fuzzily matches to marathi .', 'tostr': 'filter_eq { all_rows ; language ; marathi }'}, 'role'], 'result': 'sonal', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; language ; marathi } ; role }'}, 'sonal'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; language ; marathi } ; role } ; sonal }', 'tointer': 'the role record of this unqiue row is sonal .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; language ; marathi } } ; eq { hop { filter_eq { all_rows ; language ; marathi } ; role } ; sonal } } = true', 'tointer': 'select the rows whose language record fuzzily matches to marathi . there is only one such row in the table . the role record of this unqiue row is sonal .'} | and { only { filter_eq { all_rows ; language ; marathi } } ; eq { hop { filter_eq { all_rows ; language ; marathi } ; role } ; sonal } } = true | select the rows whose language record fuzzily matches to marathi . there is only one such row in the table . the role record of this unqiue row is sonal . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'language_7': 7, 'marathi_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'role_9': 9, 'sonal_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'language_7': 'language', 'marathi_8': 'marathi', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'role_9': 'role', 'sonal_10': 'sonal'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'language_7': [0], 'marathi_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'role_9': [2], 'sonal_10': [3]} | ['year', 'title', 'role', 'language', 'notes'] | [['2007', 'chak de ! india', 'preeti sabarwal', 'hindi', 'supporting role'], ['2009', 'fox', 'urvashi mathur', 'hindi', 'small role'], ['2011', 'miley naa miley hum', 'kamiah', 'hindi', 'supporting role'], ['2012', 'rush', 'ahana sharma', 'hindi', 'released on october 24 , 2012'], ['2013', 'premachi goshta', 'sonal', 'marathi', 'lead role , movie directed by satish rajwade']] |
1931 vfl season | https://en.wikipedia.org/wiki/1931_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10789881-3.html.csv | ordinal | princes park venue recorded the 2nd highest crowd participation during the 1931 vfl season . | {'row': '3', 'col': '6', 'order': '2', 'col_other': '5', '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', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'venue'], 'result': 'princes park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; venue }'}, 'princes park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; princes park } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is princes park .'} | eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; princes park } = true | select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is princes park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'venue_7': 7, 'princes park_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', '2_6': '2', 'venue_7': 'venue', 'princes park_8': 'princes park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'venue_7': [1], 'princes park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '7.10 ( 52 )', 'richmond', '13.16 ( 94 )', 'western oval', '30000', '16 may 1931'], ['collingwood', '13.16 ( 94 )', 'south melbourne', '10.13 ( 73 )', 'victoria park', '15000', '16 may 1931'], ['carlton', '18.18 ( 126 )', 'essendon', '5.14 ( 44 )', 'princes park', '20000', '16 may 1931'], ['st kilda', '10.12 ( 72 )', 'hawthorn', '10.8 ( 68 )', 'junction oval', '14000', '16 may 1931'], ['melbourne', '12.15 ( 87 )', 'geelong', '11.17 ( 83 )', 'mcg', '19767', '16 may 1931'], ['north melbourne', '6.12 ( 48 )', 'fitzroy', '12.16 ( 88 )', 'arden street oval', '7000', '16 may 1931']] |
nova scotia voyageurs | https://en.wikipedia.org/wiki/Nova_Scotia_Voyageurs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1166259-1.html.csv | count | between 1969 and 1983 the nova scotia voyageurs finished at least first in their division 4 times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '1st', 'result': '4', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'standing', '1st'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose standing record fuzzily matches to 1st .', 'tostr': 'filter_eq { all_rows ; standing ; 1st }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; standing ; 1st } }', 'tointer': 'select the rows whose standing record fuzzily matches to 1st . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; standing ; 1st } } ; 4 } = true', 'tointer': 'select the rows whose standing record fuzzily matches to 1st . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; standing ; 1st } } ; 4 } = true | select the rows whose standing record fuzzily matches to 1st . 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, 'standing_5': 5, '1st_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', 'standing_5': 'standing', '1st_6': '1st', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'standing_5': [0], '1st_6': [0], '4_7': [2]} | ['season', 'games', 'lost', 'tied', 'points', 'goals for', 'goals against', 'standing'] | [['1969 - 70', '72', '15', '14', '100', '327', '195', '1st , east'], ['1970 - 71', '72', '31', '14', '68', '215', '239', '2nd , east'], ['1971 - 72', '76', '21', '14', '96', '274', '202', '2nd , east'], ['1972 - 73', '76', '18', '15', '101', '316', '191', '1st , east'], ['1973 - 74', '76', '27', '12', '86', '263', '223', '3rd , north'], ['1974 - 75', '75', '26', '9', '89', '270', '227', '3rd , north'], ['1975 - 76', '76', '20', '8', '104', '326', '209', '1st , north'], ['1976 - 77', '80', '22', '6', '110', '308', '225', '1st , ahl'], ['1977 - 78', '81', '28', '16', '90', '304', '250', '2nd , north'], ['1978 - 79', '80', '37', '4', '82', '313', '302', '3rd , north'], ['1979 - 80', '79', '29', '7', '93', '331', '271', '2nd , north'], ['1980 - 81', '80', '37', '5', '81', '335', '298', '3rd , north'], ['1981 - 82', '80', '35', '10', '80', '330', '313', '3rd , north'], ['1982 - 83', '80', '34', '5', '87', '378', '333', '2nd , north'], ['1983 - 84', '80', '37', '11', '75', '277', '288', '4th , north']] |
2001 cfl draft | https://en.wikipedia.org/wiki/2001_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15817998-4.html.csv | unique | shawn gifford was the only played taken in the 2001 cfl draft from charleston southern college . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'charleston southern', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'charleston southern'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to charleston southern .', 'tostr': 'filter_eq { all_rows ; college ; charleston southern }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; charleston southern } }', 'tointer': 'select the rows whose college record fuzzily matches to charleston southern . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'charleston southern'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to charleston southern .', 'tostr': 'filter_eq { all_rows ; college ; charleston southern }'}, 'player'], 'result': 'shawn gifford', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; charleston southern } ; player }'}, 'shawn gifford'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; charleston southern } ; player } ; shawn gifford }', 'tointer': 'the player record of this unqiue row is shawn gifford .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; charleston southern } } ; eq { hop { filter_eq { all_rows ; college ; charleston southern } ; player } ; shawn gifford } } = true', 'tointer': 'select the rows whose college record fuzzily matches to charleston southern . there is only one such row in the table . the player record of this unqiue row is shawn gifford .'} | and { only { filter_eq { all_rows ; college ; charleston southern } } ; eq { hop { filter_eq { all_rows ; college ; charleston southern } ; player } ; shawn gifford } } = true | select the rows whose college record fuzzily matches to charleston southern . there is only one such row in the table . the player record of this unqiue row is shawn gifford . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'charleston southern_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'shawn gifford_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'charleston southern_8': 'charleston southern', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'shawn gifford_10': 'shawn gifford'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'charleston southern_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'shawn gifford_10': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['25', 'montreal alouettes', 'shawn gifford', 'ot', 'charleston southern'], ['26', 'toronto argonauts', 'kevin eiben', 's', 'bucknell'], ['27', 'winnipeg blue bombers', 'nick tsatsaronis', 'rb', 'memphis'], ['28', 'hamilton tiger - cats', 'ryan donnelly', 'ol', 'mcmaster'], ['29', 'montreal alouettes', 'peter moore', 'dl', 'syracuse'], ['30', 'calgary stampeders', 'andrew carter', 'ol', "bishop 's"], ['31', 'montreal alouettes', 'steven maheu', 'wr / qb', 'simon fraser'], ['32', 'bc lions', 'kelly bates', 'ol', 'saskatchewan']] |
bolt thrust | https://en.wikipedia.org/wiki/Bolt_thrust | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26967904-2.html.csv | superlative | the .50 bmg in the bolt thrust has the highest f bolt ( kgf ) . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '10', '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', 'f bolt ( kgf )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; f bolt ( kgf ) }'}, 'chambering'], 'result': '.50 bmg', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; f bolt ( kgf ) } ; chambering }'}, '.50 bmg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; f bolt ( kgf ) } ; chambering } ; .50 bmg } = true', 'tointer': 'select the row whose f bolt ( kgf ) record of all rows is maximum . the chambering record of this row is .50 bmg .'} | eq { hop { argmax { all_rows ; f bolt ( kgf ) } ; chambering } ; .50 bmg } = true | select the row whose f bolt ( kgf ) record of all rows is maximum . the chambering record of this row is .50 bmg . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'f bolt ( kgf )_5': 5, 'chambering_6': 6, '.50 bmg_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'f bolt ( kgf )_5': 'f bolt ( kgf )', 'chambering_6': 'chambering', '.50 bmg_7': '.50 bmg'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'f bolt ( kgf )_5': [0], 'chambering_6': [1], '.50 bmg_7': [2]} | ['chambering', 'p1 diameter ( mm )', 'a external ( cm 2 )', 'p max ( bar )', 'f bolt ( kgf )', 'f bolt'] | [['5.45 x39 mm', '10.00', '0.7854', '3800', '2985', 'n ( lbf )'], ['.223 remington', '9.58', '0.7208', '4300', '3099', 'n ( lbf )'], ['7.62 x39 mm', '11.35', '1.0118', '3550', '3592', 'n ( lbf )'], ['.308 winchester', '11.96', '1.1234', '4150', '4662', 'n ( lbf )'], ['.300 winchester magnum', '13.03', '1.3335', '4300', '5734', 'n ( lbf )'], ['.300 wsm', '14.12', '1.5659', '4450', '6968', 'n ( lbf )'], ['.300 remington ultra magnum', '13.97', '1.5328', '4480', '6876', 'n ( lbf )'], ['.338 lapua magnum', '14.91', '1.7460', '4200', '7333', 'n ( lbf )'], ['.300 lapua magnum', '14.91', '1.7460', '4700', '8339', 'n ( lbf )'], ['.50 bmg', '20.42', '3.2749', '3700', '12117', 'n ( lbf )']] |
2008 - 09 los angeles clippers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Los_Angeles_Clippers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17323529-7.html.csv | majority | eric fordon had the highest number of high points performances for the 2008 - 09 los angeles clippers . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'eric gordon', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'eric gordon'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to eric gordon .', 'tostr': 'most_eq { all_rows ; high points ; eric gordon } = true'} | most_eq { all_rows ; high points ; eric gordon } = true | for the high points records of all rows , most of them fuzzily match to eric gordon . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'eric gordon_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'eric gordon_4': 'eric gordon'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'eric gordon_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['32', 'january 2', 'phoenix', 'l 98 - 106 ( ot )', 'eric gordon ( 21 )', 'marcus camby ( 23 )', 'fred jones , marcus camby ( 4 )', 'us airways center 18422', '8 - 24'], ['33', 'january 4', 'detroit', 'l 87 - 88 ( ot )', 'eric gordon ( 31 )', 'marcus camby ( 20 )', 'mardy collins ( 12 )', 'staples center 17968', '8 - 25'], ['34', 'january 6', 'dallas', 'l 102 - 107 ( ot )', 'eric gordon ( 32 )', 'marcus camby ( 19 )', 'eric gordon ( 6 )', 'american airlines center 19794', '8 - 26'], ['35', 'january 8', 'san antonio', 'l 84 - 106 ( ot )', 'al thornton , eric gordon ( 21 )', 'marcus camby ( 9 )', 'jason hart ( 4 )', 'at & t center 17873', '8 - 27'], ['36', 'january 9', 'new orleans', 'l 80 - 107 ( ot )', 'eric gordon , mardy collins ( 15 )', 'marcus camby ( 17 )', 'mardy collins ( 6 )', 'new orleans arena 17815', '8 - 28'], ['37', 'january 11', 'phoenix', 'l 103 - 109 ( ot )', 'al thornton ( 23 )', 'marcus camby ( 18 )', 'fred jones ( 10 )', 'staples center 17307', '8 - 29'], ['38', 'january 14', 'atlanta', 'l 80 - 97 ( ot )', 'al thornton ( 25 )', 'marcus camby ( 18 )', 'mardy collins ( 8 )', 'staples center 15901', '8 - 30'], ['39', 'january 17', 'milwaukee', 'w 101 - 92 ( ot )', 'brian skinner , marcus camby ( 18 )', 'marcus camby ( 11 )', 'mardy collins ( 11 )', 'staples center 16448', '9 - 30'], ['40', 'january 19', 'minnesota', 'l 86 - 94 ( ot )', 'eric gordon ( 25 )', 'deandre jordan ( 10 )', 'mardy collins ( 8 )', 'staples center 14399', '9 - 31'], ['41', 'january 21', 'la lakers', 'l 97 - 108 ( ot )', 'deandre jordan ( 23 )', 'deandre jordan ( 12 )', 'eric gordon ( 6 )', 'staples center 19627', '9 - 32'], ['42', 'january 23', 'oklahoma city', 'w 107 - 104 ( ot )', 'eric gordon ( 41 )', 'cheikh samb ( 8 )', 'ricky davis ( 11 )', 'staples center 14913', '10 - 32'], ['43', 'january 25', 'golden state', 'l 92 - 107 ( ot )', 'eric gordon ( 21 )', 'deandre jordan ( 20 )', 'ricky davis ( 7 )', 'oracle arena 17746', '10 - 33'], ['44', 'january 26', 'portland', 'l 88 - 113 ( ot )', 'al thornton ( 23 )', 'brian skinner ( 10 )', 'fred jones , eric gordon ( 7 )', 'staples center 16570', '10 - 34'], ['45', 'january 28', 'chicago', 'l 75 - 95 ( ot )', 'eric gordon ( 19 )', 'al thornton , deandre jordan , marcus camby ( 6 )', 'eric gordon ( 7 )', 'staples center 15637', '10 - 35'], ['46', 'january 30', 'cleveland', 'l 95 - 112 ( ot )', 'eric gordon ( 27 )', 'eric gordon , baron davis ( 7 )', 'fred jones ( 9 )', 'quicken loans arena 20562', '10 - 36'], ['47', 'january 31', 'washington', 'l 94 - 106 ( ot )', 'eric gordon ( 25 )', 'brian skinner ( 10 )', 'baron davis , fred jones ( 6 )', 'verizon center 18227', '10 - 37']] |
mauricio cienfuegos | https://en.wikipedia.org/wiki/Mauricio_Cienfuegos | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1114137-1.html.csv | majority | mauricio cienfuegos scored the majority of his goals at the estadio cuscatlán , san salvador , el salvador venue . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'estadio cuscatlán , san salvador , el salvador', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'venue', 'estadio cuscatlán , san salvador , el salvador'], 'result': True, 'ind': 0, 'tointer': 'for the venue records of all rows , most of them fuzzily match to estadio cuscatlán , san salvador , el salvador .', 'tostr': 'most_eq { all_rows ; venue ; estadio cuscatlán , san salvador , el salvador } = true'} | most_eq { all_rows ; venue ; estadio cuscatlán , san salvador , el salvador } = true | for the venue records of all rows , most of them fuzzily match to estadio cuscatlán , san salvador , el salvador . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'venue_3': 3, 'estadio cuscatlán , san salvador , el salvador_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'venue_3': 'venue', 'estadio cuscatlán , san salvador , el salvador_4': 'estadio cuscatlán , san salvador , el salvador'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'venue_3': [0], 'estadio cuscatlán , san salvador , el salvador_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['23 july 1992', 'estadio cuscatlán , san salvador , el salvador', '2 - 0', '5 - 1', '1994 fifa world cup qualification'], ['1 november 1992', 'estadio cuscatlán , san salvador , el salvador', '3 - 0', '4 - 1', '1994 fifa world cup qualification'], ['23 march 1993', 'estadio cuscatlán , san salvador , el salvador', '2 - 2', '2 - 2', 'friendly match'], ['29 november 1995', 'estadio oscar quiteno , santa ana , el salvador', '1 - 0', '3 - 0', '1995 uncaf nations cup'], ['3 december 1995', 'estadio flor blanca , san salvador , el salvador', '2 - 1', '2 - 1', '1995 uncaf nations cup'], ['8 september 1996', 'estadio cuscatlán , san salvador , el salvador', '5 - 0', '5 - 0', '1998 fifa world cup qualification'], ['14 september 1997', 'estadio cuscatlán , san salvador , el salvador', '3 - 1', '4 - 1', '1998 fifa world cup qualification'], ['16 july 2000', 'estadio cuscatlán , san salvador , el salvador', '2 - 5', '2 - 5', '2002 fifa world cup qualification']] |
houston rockets all - time roster | https://en.wikipedia.org/wiki/Houston_Rockets_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11734041-6.html.csv | aggregation | the median height of players of the all-time roster of the houston rockets is 6 ' 3 " . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '6 \' 3 "', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height in ft'], 'result': '6 \' 3 "', 'ind': 0, 'tostr': 'avg { all_rows ; height in ft }'}, '6 \' 3 "'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height in ft } ; 6 \' 3 " } = true', 'tointer': 'the average of the height in ft record of all rows is 6 \' 3 " .'} | round_eq { avg { all_rows ; height in ft } ; 6 ' 3 " } = true | the average of the height in ft record of all rows is 6 ' 3 " . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height in ft_4': 4, '6\' 3"_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height in ft_4': 'height in ft', '6\' 3"_5': '6 \' 3 "'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height in ft_4': [0], '6\' 3"_5': [1]} | ['player', 'no ( s )', 'height in ft', 'position', 'years for rockets', 'school / club team / country'] | [['feitl , dave dave feitl', '5', '7 - 0', 'center', '1986 - 86 , 1990 - 91', 'texas - el paso'], ['finkel , hank hank finkel', '17', '7 - 0', 'center', '1967 - 69', 'dayton'], ['fitch , gerald gerald fitch', '0', '6 - 3', 'guard', '2006', 'kentucky'], ['floyd , sleepy sleepy floyd', '11 , 21', '6 - 3', 'guard', '1987 - 93', 'georgetown'], ['flynn , johnny johnny flynn', '3', '6 - 0', 'guard', '2012', 'syracuse'], ['ford , alton alton ford', '1', '6 - 9', 'forward', '2003 - 04', 'houston'], ['ford , phil phil ford', '1', '6 - 2', 'guard', '1983 - 85', 'north carolina'], ['frahm , rickie richie frahm', '14', '6 - 5', 'guard', '2005 - 06', 'gonzaga'], ['francis , steve steve francis', '3', '6 - 3', 'guard', '1999 - 2004 , 2007 - 08', 'maryland'], ['free , world b world b free', '21', '6 - 3', 'guard', '1987 - 88', 'guilford']] |
2007 bc lions season | https://en.wikipedia.org/wiki/2007_BC_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11994830-20.html.csv | aggregation | the average number of yards per player during the 2007 bc lions season was 888.8 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '888.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'yards'], 'result': '888.8', 'ind': 0, 'tostr': 'avg { all_rows ; yards }'}, '888.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; yards } ; 888.8 } = true', 'tointer': 'the average of the yards record of all rows is 888.8 .'} | round_eq { avg { all_rows ; yards } ; 888.8 } = true | the average of the yards record of all rows is 888.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'yards_4': 4, '888.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'yards_4': 'yards', '888.8_5': '888.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'yards_4': [0], '888.8_5': [1]} | ['player', 'att', 'comp', 'yards', 'rating'] | [['jarious jackson', '304', '167', '2553', '88.9'], ['buck pierce', '127', '81', '1013', '91.7'], ['dave dickenson', '87', '56', '740', '88.3'], ['gino guidugli', '11', '6', '138', '92.2'], ['ian smart', '1', '0', '0', '2.1']] |
2004 cleveland browns season | https://en.wikipedia.org/wiki/2004_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652530-2.html.csv | majority | the cleveland browns lost most of their games in the 2004 season . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'} | most_eq { all_rows ; result ; l } = true | for the result records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]} | ['week', 'date', 'opponent', 'result', 'stadium', 'record', 'attendance'] | [['1', 'september 12 , 2004', 'baltimore ravens', 'w 20 - 3', 'cleveland browns stadium', '1 - 0', '73068'], ['2', 'september 19 , 2004', 'dallas cowboys', 'l 12 - 19', 'texas stadium', '1 - 1', '63119'], ['3', 'september 26 , 2004', 'new york giants', 'l 10 - 27', 'giants stadium', '1 - 2', '78521'], ['4', 'october 3 , 2004', 'washington redskins', 'w 17 - 13', 'cleveland browns stadium', '2 - 2', '73348'], ['5', 'october 10 , 2004', 'pittsburgh steelers', 'l 23 - 34', 'heinz field', '2 - 3', '63609'], ['6', 'october 17 , 2004', 'cincinnati bengals', 'w 34 - 17', 'cleveland browns stadium', '3 - 3', '73263'], ['7', 'october 24 , 2004', 'philadelphia eagles', 'l 31 - 34', 'cleveland browns stadium', '3 - 4', '73394'], ['8', '-', '-', '-', '-', '-', ''], ['9', 'november 7 , 2004', 'baltimore ravens', 'l 13 - 27', 'm & t bank stadium', '3 - 5', '69781'], ['10', 'november 14 , 2004', 'pittsburgh steelers', 'l 10 - 24', 'cleveland browns stadium', '3 - 6', '73703'], ['11', 'november 21 , 2004', 'new york jets', 'l 7 - 10', 'cleveland browns stadium', '3 - 7', '72547'], ['12', 'november 28 , 2004', 'cincinnati bengals', 'l 48 - 58', 'paul brown stadium', '3 - 8', '65677'], ['13', 'december 5 , 2004', 'new england patriots', 'l 15 - 42', 'cleveland browns stadium', '3 - 9', '73028'], ['14', 'december 12 , 2004', 'buffalo bills', 'l 7 - 37', 'ralph wilson stadium', '3 - 10', '72330'], ['15', 'december 19 , 2004', 'san diego chargers', 'l 0 - 21', 'cleveland browns stadium', '3 - 11', '72489'], ['16', 'december 26 , 2004', 'miami dolphins', 'l 7 - 10', 'pro player stadium', '3 - 12', '73169'], ['17', 'january 2 , 2005', 'houston texans', 'w 22 - 14', 'reliant stadium', '4 - 12', '70724']] |
road network in tamil nadu | https://en.wikipedia.org/wiki/Road_network_in_Tamil_Nadu | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28723146-2.html.csv | superlative | national highways make up the largest amount of multi lane roads in tamil , nadu . | {'scope': 'all', 'col_superlative': '6', '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', 'multi lane'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; multi lane }'}, 'category wise'], 'result': 'national highways', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; multi lane } ; category wise }'}, 'national highways'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; multi lane } ; category wise } ; national highways } = true', 'tointer': 'select the row whose multi lane record of all rows is maximum . the category wise record of this row is national highways .'} | eq { hop { argmax { all_rows ; multi lane } ; category wise } ; national highways } = true | select the row whose multi lane record of all rows is maximum . the category wise record of this row is national highways . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'multi lane_5': 5, 'category wise_6': 6, 'national highways_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'multi lane_5': 'multi lane', 'category wise_6': 'category wise', 'national highways_7': 'national highways'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'multi lane_5': [0], 'category wise_6': [1], 'national highways_7': [2]} | ['sl no', 'category wise', 'single lane', 'intermediate lane', 'double lane', 'multi lane', 'total'] | [['1', 'national highways', '18', '42', '2685', '2128', '4873'], ['2', 'state highways', '32', '1414', '7261', '677', '9384'], ['3', 'major district roads', '4170', '3894', '3109', '115', '11288'], ['4', 'other district roads & sugarcane roads', '32825', '2292', '948', '31', '36096'], ['5', 'total ( approx )', '38071', '6998', '14535', '2037', '61641']] |
seattle supersonics all - time roster | https://en.wikipedia.org/wiki/Seattle_SuperSonics_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16772687-8.html.csv | majority | most of the all-time supersonics have a jersey number higher than 10 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'jersey number ( s )', '10'], 'result': True, 'ind': 0, 'tointer': 'for the jersey number ( s ) records of all rows , most of them are greater than 10 .', 'tostr': 'most_greater { all_rows ; jersey number ( s ) ; 10 } = true'} | most_greater { all_rows ; jersey number ( s ) ; 10 } = true | for the jersey number ( s ) records of all rows , most of them are greater than 10 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'jersey number (s)_3': 3, '10_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'jersey number (s)_3': 'jersey number ( s )', '10_4': '10'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'jersey number (s)_3': [0], '10_4': [0]} | ['player', 'nationality', 'jersey number ( s )', 'position', 'years', 'from'] | [['mickaël gelabale', 'france', '15', 'sf', '2006 - 2008', 'real madrid'], ['dick gibbs', 'united states', '21', 'sf / sg', '1973 - 1974', 'utep'], ['eddie gill', 'united states', '6', 'pg', '2008', 'weber state'], ['kendall gill', 'united states', '13', 'sg / sf', '1993 - 1995', 'illinois'], ['herm gilliam', 'united states', '3', 'g / sf', '1975 - 1976', 'purdue'], ['greg graham', 'united states', '21', 'sg', '1996 - 1997', 'indiana'], ['horace grant', 'united states', '54', 'pf / c', '1999 - 2000', 'clemson'], ['leonard gray', 'united states', '11', 'pf', '1974 - 1976', 'cal state - long beach'], ['jeff green', 'united states', '22', 'sf / pf', '2007 - 2008', 'georgetown'], ['mike green', 'united states', '23', 'c / pf', '1976 - 1977', 'louisiana tech'], ['john greig', 'united states', '22', 'f', '1982 - 1983', 'oregon'], ['adrian griffin', 'united states', '22', 'g / sf', '2008', 'seton hall']] |
flora , norway | https://en.wikipedia.org/wiki/Flora%2C_Norway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-178381-1.html.csv | ordinal | batalden bedehuskapell was the third most recent of these churches to be built . | {'row': '4', 'col': '4', 'order': '3', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'year built', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year built ; 3 }'}, 'church name'], 'result': 'batalden bedehuskapell', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year built ; 3 } ; church name }'}, 'batalden bedehuskapell'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; year built ; 3 } ; church name } ; batalden bedehuskapell } = true', 'tointer': 'select the row whose year built record of all rows is 3rd maximum . the church name record of this row is batalden bedehuskapell .'} | eq { hop { nth_argmax { all_rows ; year built ; 3 } ; church name } ; batalden bedehuskapell } = true | select the row whose year built record of all rows is 3rd maximum . the church name record of this row is batalden bedehuskapell . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year built_5': 5, '3_6': 6, 'church name_7': 7, 'batalden bedehuskapell_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'year built_5': 'year built', '3_6': '3', 'church name_7': 'church name', 'batalden bedehuskapell_8': 'batalden bedehuskapell'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year built_5': [0], '3_6': [0], 'church name_7': [1], 'batalden bedehuskapell_8': [2]} | ['parish ( prestegjeld )', 'sub - parish ( sokn )', 'church name', 'year built', 'location of the church'] | [['kinn parish', 'bru', 'askrova bedehuskapell', '1957', 'espeset'], ['kinn parish', 'bru', 'stavang kyrkje', '1957', 'stavang'], ['kinn parish', 'eikefjord', 'eikefjord kyrkje', '1812', 'eikefjord'], ['kinn parish', 'kinn', 'batalden bedehuskapell', '1907', 'fanøya'], ['kinn parish', 'kinn', 'florø kyrkje', '1882', 'florø'], ['kinn parish', 'kinn', 'kinnakyrkje', '12th century', 'kinn'], ['kinn parish', 'nordal', 'nordal kyrkje', '1898', 'nordalen']] |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17596418-5.html.csv | unique | owusu - abeyie is the only ghana player loaned by cardiff city in 2008 - 09 season . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'ghana', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'ghana'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to ghana .', 'tostr': 'filter_eq { all_rows ; country ; ghana }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; ghana } }', 'tointer': 'select the rows whose country record fuzzily matches to ghana . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'ghana'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to ghana .', 'tostr': 'filter_eq { all_rows ; country ; ghana }'}, 'name'], 'result': 'owusu - abeyie', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; ghana } ; name }'}, 'owusu - abeyie'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; ghana } ; name } ; owusu - abeyie }', 'tointer': 'the name record of this unqiue row is owusu - abeyie .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; ghana } } ; eq { hop { filter_eq { all_rows ; country ; ghana } ; name } ; owusu - abeyie } } = true', 'tointer': 'select the rows whose country record fuzzily matches to ghana . there is only one such row in the table . the name record of this unqiue row is owusu - abeyie .'} | and { only { filter_eq { all_rows ; country ; ghana } } ; eq { hop { filter_eq { all_rows ; country ; ghana } ; name } ; owusu - abeyie } } = true | select the rows whose country record fuzzily matches to ghana . there is only one such row in the table . the name record of this unqiue row is owusu - abeyie . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'ghana_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'owusu - abeyie_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'ghana_8': 'ghana', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'owusu - abeyie_10': 'owusu - abeyie'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'ghana_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'owusu - abeyie_10': [3]} | ['name', 'country', 'loan club', 'started', 'ended', 'start source', 'end source'] | [['heaton', 'eng', 'manchester united', '5 may', '30 june', 'bbc sport', 'south wales echo'], ['e johnson', 'usa', 'fulham', '22 august', '30 june', 'bbc sport', 'south wales echo'], ['chopra', 'eng', 'sunderland', '6 november', '30 december', 'bbc sport', 'bbc sport'], ['routledge', 'eng', 'aston villa', '20 november', '2 january', 'cardiff city', 'bbc sport'], ['owusu - abeyie', 'ghana', 'spartak moscow', '31 january', '30 june', 'bbc sport', 'south wales echo'], ['chopra', 'eng', 'sunderland', '2 february', '30 june', 'bbc sport', 'south wales echo'], ['konstantopoulos', 'gre', 'coventry city', '9 february', '30 june', 'bbc sport', 'south wales echo'], ['taylor', 'eng', 'aston villa', '13 march', '30 june', 'bbc sport', 'south wales echo']] |
united states house of representatives elections , 1924 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1924 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342393-23.html.csv | superlative | percy e quin had served the longest as a congressman when he ran for re-election in 1924 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'first elected'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; first elected }'}, 'incumbent'], 'result': 'percy e quin', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; first elected } ; incumbent }'}, 'percy e quin'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; first elected } ; incumbent } ; percy e quin } = true', 'tointer': 'select the row whose first elected record of all rows is minimum . the incumbent record of this row is percy e quin .'} | eq { hop { argmin { all_rows ; first elected } ; incumbent } ; percy e quin } = true | select the row whose first elected record of all rows is minimum . the incumbent record of this row is percy e quin . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, 'incumbent_6': 6, 'percy e quin_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', 'incumbent_6': 'incumbent', 'percy e quin_7': 'percy e quin'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], 'incumbent_6': [1], 'percy e quin_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['mississippi 1', 'john e rankin', 'democratic', '1920', 're - elected', 'john e rankin ( d ) unopposed'], ['mississippi 2', 'bill g lowrey', 'democratic', '1920', 're - elected', 'bill g lowrey ( d ) unopposed'], ['mississippi 3', 'william y humphreys', 'democratic', '1923', 'retired democratic hold', 'william madison whittington ( d ) unopposed'], ['mississippi 4', 'jeff busby', 'democratic', '1922', 're - elected', 'jeff busby ( d ) 95.7 % r h dekay ( r ) 4.3 %'], ['mississippi 5', 'ross a collins', 'democratic', '1920', 're - elected', 'ross a collins ( d ) unopposed'], ['mississippi 6', 't webber wilson', 'democratic', '1922', 're - elected', 't webber wilson ( d ) unopposed'], ['mississippi 7', 'percy e quin', 'democratic', '1912', 're - elected', 'percy e quin ( d ) unopposed']] |
great railway journeys | https://en.wikipedia.org/wiki/Great_Railway_Journeys | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15211468-3.html.csv | majority | all of the great railway journeys episodes had uk broadcast dates in the year 1996 . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '1996', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'uk broadcast date', '1996'], 'result': True, 'ind': 0, 'tointer': 'for the uk broadcast date records of all rows , all of them are equal to 1996 .', 'tostr': 'all_eq { all_rows ; uk broadcast date ; 1996 } = true'} | all_eq { all_rows ; uk broadcast date ; 1996 } = true | for the uk broadcast date records of all rows , all of them are equal to 1996 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'uk broadcast date_3': 3, '1996_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'uk broadcast date_3': 'uk broadcast date', '1996_4': '1996'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'uk broadcast date_3': [0], '1996_4': [0]} | ['episode no', 'episode title', 'uk broadcast date', 'presenter', 'countries visited'] | [['3.1', 'crewe to crewe', '1996 - 09 - 04', 'victoria wood', 'united kingdom'], ['3.2', 'aleppo to aqaba', '1996 - 09 - 11', 'alexei sayle', 'syria , jordan'], ['3.3', 'great zimbabwe to kilimatinde', '1996 - 09 - 18', 'henry louis gates jr', 'zimbabwe , zambia , tanzania'], ['3.4', 'the high andes to patagonia', '1996 - 09 - 25', 'buck henry', 'argentina'], ['3.5', 'mombasa to the mountains of the moon', '1996 - 10 - 02', 'benedict allen', 'kenya , uganda'], ['3.6', 'london to arcadia', '1996 - 10 - 09', 'ben okri', 'england , france , switzerland , italy , greece'], ['3.7', 'halifax to porteau cove', '1996 - 10 - 16', 'chris bonington', 'canada']] |
1967 south african grand prix | https://en.wikipedia.org/wiki/1967_South_African_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122362-1.html.csv | ordinal | at the 1967 south african grand prix , the 2nd fewest number of laps was competed by graham hill . | {'row': '17', 'col': '3', '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', 'laps', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; laps ; 2 }'}, 'driver'], 'result': 'graham hill', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; laps ; 2 } ; driver }'}, 'graham hill'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; laps ; 2 } ; driver } ; graham hill } = true', 'tointer': 'select the row whose laps record of all rows is 2nd minimum . the driver record of this row is graham hill .'} | eq { hop { nth_argmin { all_rows ; laps ; 2 } ; driver } ; graham hill } = true | select the row whose laps record of all rows is 2nd minimum . the driver record of this row is graham hill . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'laps_5': 5, '2_6': 6, 'driver_7': 7, 'graham hill_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', 'laps_5': 'laps', '2_6': '2', 'driver_7': 'driver', 'graham hill_8': 'graham hill'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'laps_5': [0], '2_6': [0], 'driver_7': [1], 'graham hill_8': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['pedro rodrã\xadguez', 'cooper - maserati', '80', '2:05:45.9', '4'], ['john love', 'cooper - climax', '80', '+ 26.4', '5'], ['john surtees', 'honda', '79', '+ 1 lap', '6'], ['denny hulme', 'brabham - repco', '78', '+ 2 laps', '2'], ['bob anderson', 'brabham - climax', '78', '+ 2 laps', '10'], ['jack brabham', 'brabham - repco', '76', '+ 4 laps', '1'], ['dave charlton', 'brabham - climax', '63', 'not classified', '8'], ['luki botha', 'brabham - climax', '60', 'not classified', '17'], ['sam tingle', 'lds - climax', '56', 'accident', '14'], ['piers courage', 'lotus - brm', '51', 'fuel system', '18'], ['dan gurney', 'eagle - climax', '44', 'suspension', '11'], ['jo siffert', 'cooper - maserati', '41', 'engine', '16'], ['jochen rindt', 'cooper - maserati', '38', 'engine', '7'], ['mike spence', 'brm', '31', 'oil leak', '13'], ['jo bonnier', 'cooper - maserati', '30', 'engine', '12'], ['jim clark', 'lotus - brm', '22', 'engine', '3'], ['graham hill', 'lotus - brm', '6', 'accident', '15'], ['jackie stewart', 'brm', '2', 'engine', '9']] |
great south athletic conference | https://en.wikipedia.org/wiki/Great_South_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1973842-2.html.csv | aggregation | the institutions in the great south athletic conference has a total enrollment of 8,600 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '8,600', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'enrollment'], 'result': '8,600', 'ind': 0, 'tostr': 'sum { all_rows ; enrollment }'}, '8,600'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; enrollment } ; 8,600 } = true', 'tointer': 'the sum of the enrollment record of all rows is 8,600 .'} | round_eq { sum { all_rows ; enrollment } ; 8,600 } = true | the sum of the enrollment record of all rows is 8,600 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '8,600_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '8,600_5': '8,600'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '8,600_5': [1]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined', 'left', 'current conference'] | [['fisk university', 'nashville , tennessee', 'bulldogs', '1866', 'private / united church of christ', '800', '1999', '2006', 'gulf coast ( gcac ) ( naia )'], ['covenant college', 'lookout mountain , georgia', "scots ( men 's ) lady scots ( women 's )", '1955', 'private / presbyterian', '1282', '2010', '2013', 'usa south'], ['huntingdon college', 'montgomery , alabama', 'hawks', '1854', 'private / methodist', '900', '2002', '2013', 'usa south'], ['lagrange college', 'lagrange , georgia', 'panthers', '1831', 'private / methodist', '942', '1999', '2012', 'usa south'], ['maryville college', 'maryville , tennessee', 'scots', '1819', 'private / presbyterian', '1176', '1999', '2012', 'usa south'], ['piedmont college', 'demorest , georgia', 'lions', '1897', 'private / united church of christ', '2000', '1999', '2012', 'usa south'], ['stillman college', 'tuscaloosa , alabama', 'tigers', '1876', 'private / presbyterian', '1500', '1999', '2002', 'siac ( ncaa division ii )']] |
wheelchair tennis at the 2008 summer paralympics | https://en.wikipedia.org/wiki/Wheelchair_tennis_at_the_2008_Summer_Paralympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18403681-1.html.csv | aggregation | the average number of gold medals in wheelchair tennis at the 2008 summer paralympics was .86 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '0.86', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '0.86', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '0.86'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; 0.86 } = true', 'tointer': 'the average of the gold record of all rows is 0.86 .'} | round_eq { avg { all_rows ; gold } ; 0.86 } = true | the average of the gold record of all rows is 0.86 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '0.86_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '0.86_5': '0.86'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '0.86_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'netherlands ( ned )', '2', '3', '1', '6'], ['2', 'france ( fra )', '1', '0', '2', '3'], ['3', 'great britain ( gbr )', '1', '0', '1', '2'], ['3', 'japan ( jpn )', '1', '0', '1', '2'], ['3', 'united states ( usa )', '1', '0', '1', '2'], ['6', 'sweden ( swe )', '0', '2', '0', '2'], ['7', 'israel ( isr )', '0', '1', '0', '1'], ['total', 'total', '6', '6', '6', '18']] |
1973 nhl amateur draft | https://en.wikipedia.org/wiki/1973_NHL_Amateur_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1965650-6.html.csv | majority | most of the players of the 1973 nhl amateur draft were from canada . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to canada .', 'tostr': 'most_eq { all_rows ; nationality ; canada } = true'} | most_eq { all_rows ; nationality ; canada } = true | for the nationality records of all rows , most of them fuzzily match to canada . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'canada_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'canada_4': 'canada'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'canada_4': [0]} | ['pick', 'player', 'position', 'nationality', 'nhl team', 'college / junior / club team'] | [['81', 'keith smith', 'defence', 'canada', 'new york islanders', 'brown university ( ecac )'], ['82', 'willie trognitz', 'left wing', 'canada', 'california golden seals', 'thunder bay vulcans ( tbjhl )'], ['83', 'jim cowell', 'centre', 'canada', 'vancouver canucks', "ottawa 67 's ( oha )"], ['84', 'doug marit', 'defence', 'canada', 'toronto maple leafs', 'regina pats ( wchl )'], ['85', 'ken houston', 'defence', 'canada', 'atlanta flames', 'chatham maroons sojhl'], ['86', 'blair macdonald', 'right wing', 'canada', 'los angeles kings', 'cornwall royals ( qmjhl )'], ['87', 'don seiling', 'left wing', 'canada', 'pittsburgh penguins', 'oshawa generals ( oha )'], ['88', 'randy smith', 'left wing', 'canada', 'st louis blues', 'edmonton oil kings ( wchl )'], ['89', 'david lee', 'left wing', 'united kingdom canada', 'minnesota north stars', "ottawa 67 's ( oha )"], ['90', 'doug ferguson', 'defence', 'canada', 'philadelphia flyers', 'hamilton red wings ( oha )'], ['91', 'glenn cickello', 'defence', 'canada', 'detroit red wings', 'hamilton red wings ( oha )'], ['92', 'neil korzack', 'left wing', 'canada', 'buffalo sabres', 'peterborough petes ( oha )'], ['93', 'garry doerksen', 'centre', 'canada', 'chicago black hawks', 'winnipeg jets ( wchl )'], ['94', 'dwayne pentland', 'defence', 'canada', 'new york rangers', 'brandon wheat kings ( wchl )'], ['95', 'jp burgoyne', 'defence', 'canada', 'boston bruins', 'shawinigan dynamos ( qmjhl )'], ['96', 'denis patry', 'right wing', 'canada', 'montreal canadiens', 'drummondville rangers ( qmjhl )']] |
list of maserati vehicles | https://en.wikipedia.org/wiki/List_of_Maserati_vehicles | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1810336-2.html.csv | comparative | when looking at the list of maserati vehicles , the model 450s had a larger displacement than model 4cl . | {'row_1': '10', 'row_2': '6', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', '450s'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to 450s .', 'tostr': 'filter_eq { all_rows ; model ; 450s }'}, 'displacement cc'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; model ; 450s } ; displacement cc }', 'tointer': 'select the rows whose model record fuzzily matches to 450s . take the displacement cc record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', '4cl'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose model record fuzzily matches to 4cl .', 'tostr': 'filter_eq { all_rows ; model ; 4cl }'}, 'displacement cc'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; model ; 4cl } ; displacement cc }', 'tointer': 'select the rows whose model record fuzzily matches to 4cl . take the displacement cc record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; model ; 450s } ; displacement cc } ; hop { filter_eq { all_rows ; model ; 4cl } ; displacement cc } } = true', 'tointer': 'select the rows whose model record fuzzily matches to 450s . take the displacement cc record of this row . select the rows whose model record fuzzily matches to 4cl . take the displacement cc record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; model ; 450s } ; displacement cc } ; hop { filter_eq { all_rows ; model ; 4cl } ; displacement cc } } = true | select the rows whose model record fuzzily matches to 450s . take the displacement cc record of this row . select the rows whose model record fuzzily matches to 4cl . take the displacement cc 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, 'model_7': 7, '450s_8': 8, 'displacement cc_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'model_11': 11, '4cl_12': 12, 'displacement cc_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', 'model_7': 'model', '450s_8': '450s', 'displacement cc_9': 'displacement cc', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'model_11': 'model', '4cl_12': '4cl', 'displacement cc_13': 'displacement cc'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'model_7': [0], '450s_8': [0], 'displacement cc_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'model_11': [1], '4cl_12': [1], 'displacement cc_13': [3]} | ['model', 'year', 'type', 'engine', 'displacement cc'] | [['type 26', '1926', 'grand prix', 'i8', '1500'], ['type 26b', '1928', 'grand prix', 'i8', '2000'], ['type v4 sedici cilindri', '1929', 'grand prix', 'v16', '4000'], ['8c', '1929', 'grand prix', 'i8', '1100 1500 2500'], ['6 cm', '1936', 'voiturette', 'i6', '1100 1500 2500'], ['4cl', '1939', 'voiturette', 'i4', '1491'], ['4clt', '1948', 'formula one', 'i4', '1491'], ['250f', '1953', 'formula one', 'i6', '2493'], ['350s', '1957', 'sports car', 'i6', '3500'], ['450s', '1957', 'sports car', 'v8', '4500'], ['type 61 birdcage', '1961', 'sports car', 'i4', '3000'], ['tipo 151', '19621963', 'sports car', 'v8', '4941'], ['tipo 154', '1965', 'sports car', 'v8', '5046.8']] |
david marrero | https://en.wikipedia.org/wiki/David_Marrero | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17666765-4.html.csv | count | fernando verdasco was david marrero 's partner for seven of the atp career finals he competed in . | {'scope': 'all', 'criterion': 'equal', 'value': 'fernando verdasco', 'result': '7', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'partner', 'fernando verdasco'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose partner record fuzzily matches to fernando verdasco .', 'tostr': 'filter_eq { all_rows ; partner ; fernando verdasco }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; partner ; fernando verdasco } }', 'tointer': 'select the rows whose partner record fuzzily matches to fernando verdasco . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; partner ; fernando verdasco } } ; 7 } = true', 'tointer': 'select the rows whose partner record fuzzily matches to fernando verdasco . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; partner ; fernando verdasco } } ; 7 } = true | select the rows whose partner record fuzzily matches to fernando verdasco . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'partner_5': 5, 'fernando verdasco_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'partner_5': 'partner', 'fernando verdasco_6': 'fernando verdasco', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'partner_5': [0], 'fernando verdasco_6': [0], '7_7': [2]} | ['date', 'tournament', 'surface', 'partner', 'opponents in the final'] | [['9 may 2010', 'estoril open , estoril , portugal', 'clay', 'marc lópez', 'pablo cuevas marcel granollers'], ['25 july 2010', 'international german open , hamburg , germany', 'clay', 'marc lópez', 'jérémy chardy paul - henri mathieu'], ['1 may 2011', 'estoril open , estoril , portugal', 'clay', 'marc lópez', 'eric butorac jean - julien rojer'], ['21 may 2011', 'open de nice côte dazur , nice , france', 'clay', 'santiago gonzalez', 'eric butorac jean - julien rojer'], ['24 september 2011', 'brd năstase țiriac trophy , bucharest , romania', 'clay', 'julian knowle', 'daniele bracciali potito starace'], ['23 october 2011', 'kremlin cup , moscow , russia', 'hard ( i )', 'carlos berlocq', 'františek čermák filip polášek'], ['25 february 2012', 'copa claro , buenos aires , argentina', 'clay', 'fernando verdasco', 'michal mertiňák andré sá'], ['4 march 2012', 'abierto mexicano telcel , acapulco , mexico', 'clay', 'fernando verdasco', 'marcel granollers marc lópez'], ['6 may 2012', 'estoril open , estoril , portugal', 'clay', 'julian knowle', 'aisam - ul - haq qureshi jean - julien rojer'], ['14 july 2012', 'atp vegeta croatia open umag , umag , croatia', 'clay', 'fernando verdasco', 'marcel granollers marc lópez'], ['22 july 2012', 'international german open , hamburg , germany', 'clay', 'fernando verdasco', 'rogério dutra da silva daniel muñoz de la nava'], ['28 october 2012', 'valencia open 500 , valencia , spain', 'hard ( i )', 'fernando verdasco', 'alexander peya bruno soares'], ['2 march 2013', 'abierto mexicano telcel , acapulco , mexico', 'clay', 'łukasz kubot', 'simone bolelli fabio fognini'], ['27 july 2013', 'atp vegeta croatia open umag , umag , croatia', 'clay', 'martin kližan', 'nicholas monroe simon stadler'], ['22 september 2013', 'st petersburg open , st petersburg , russia', 'hard ( i )', 'fernando verdasco', 'dominic inglot denis istomin'], ['13 october 2013', 'shanghai rolex masters , shanghai , china', 'hard', 'fernando verdasco', 'ivan dodig marcelo melo']] |
2007 - 08 scottish second division | https://en.wikipedia.org/wiki/2007%E2%80%9308_Scottish_Second_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11206787-5.html.csv | majority | the majority of stadiums in the 2007 - 08 scottish second division have less than 10000 seating capacity . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'capacity', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the capacity records of all rows , most of them are less than 10000 .', 'tostr': 'most_less { all_rows ; capacity ; 10000 } = true'} | most_less { all_rows ; capacity ; 10000 } = true | for the capacity records of all rows , most of them are less than 10000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'capacity_3': 3, '10000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'capacity_3': 'capacity', '10000_4': '10000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'capacity_3': [0], '10000_4': [0]} | ['team', 'stadium', 'capacity', 'highest', 'lowest', 'average'] | [['ross county', 'victoria park', '6700', '3716', '1511', '2247'], ['raith rovers', "stark 's park", '10104', '2357', '1349', '1759'], ['ayr united', 'somerset park', '11998', '1345', '971', '1137'], ['airdrie united', 'new broomfield', '10171', '1645', '611', '981'], ["queen 's park", 'hampden park', '52500', '1211', '431', '712'], ['peterhead', 'balmoor', '4000', '926', '462', '694'], ['alloa athletic', 'recreation park', '3100', '1053', '441', '602'], ['cowdenbeath', 'central park', '4370', '1953', '244', '519'], ['brechin city', 'glebe park', '3960', '669', '345', '489']] |
1985 in film | https://en.wikipedia.org/wiki/1985_in_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-171615-1.html.csv | ordinal | the fifth highest grossing movie in 1985 was " the color purple " , directed by spike lee . | {'scope': 'all', 'row': '5', 'col': '5', 'order': '5', 'col_other': '2,4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'gross', '5'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; gross ; 5 }'}, 'title'], 'result': 'the color purple', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; gross ; 5 } ; title }'}, 'the color purple'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; gross ; 5 } ; title } ; the color purple }', 'tointer': 'select the row whose gross record of all rows is 5th maximum . the title record of this row is the color purple .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'gross', '5'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; gross ; 5 }'}, 'director'], 'result': 'steven spielberg', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; gross ; 5 } ; director }'}, 'steven spielberg'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; gross ; 5 } ; director } ; steven spielberg }', 'tointer': 'the director record of this row is steven spielberg .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { nth_argmax { all_rows ; gross ; 5 } ; title } ; the color purple } ; eq { hop { nth_argmax { all_rows ; gross ; 5 } ; director } ; steven spielberg } } = true', 'tointer': 'select the row whose gross record of all rows is 5th maximum . the title record of this row is the color purple . the director record of this row is steven spielberg .'} | and { eq { hop { nth_argmax { all_rows ; gross ; 5 } ; title } ; the color purple } ; eq { hop { nth_argmax { all_rows ; gross ; 5 } ; director } ; steven spielberg } } = true | select the row whose gross record of all rows is 5th maximum . the title record of this row is the color purple . the director record of this row is steven spielberg . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_7': 7, 'gross_8': 8, '5_9': 9, 'title_10': 10, 'the color purple_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'director_12': 12, 'steven spielberg_13': 13} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_7': 'all_rows', 'gross_8': 'gross', '5_9': '5', 'title_10': 'title', 'the color purple_11': 'the color purple', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'director_12': 'director', 'steven spielberg_13': 'steven spielberg'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'nth_argmax_0': [1, 3], 'all_rows_7': [0], 'gross_8': [0], '5_9': [0], 'title_10': [1], 'the color purple_11': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'director_12': [3], 'steven spielberg_13': [4]} | ['rank', 'title', 'studio', 'director', 'gross'] | [['1', 'back to the future', 'universal', 'robert zemeckis', '215000000'], ['2', 'rocky iv', 'united artists', 'sylvester stallone', '127873716'], ['3', 'rambo : first blood part ii', 'tri - star / carolco', 'george pan cosmatos', '150415432'], ['4', 'out of africa', 'universal', 'sydney pollack', '128499205'], ['5', 'the color purple', 'warner bros', 'steven spielberg', '98467863'], ['6', 'the jewel of the nile', '20th century fox', 'lewis teague', '96773200'], ['7', 'cocoon', '20th century fox', 'ron howard', '85313124'], ['8', 'witness', 'paramount', 'peter weir', '68706993'], ['9', 'police academy 2 : their first assignment', 'warner bros / ladd', 'jerry paris', '61600000'], ['10', 'the goonies', 'warner bros', 'richard donner', '61389680'], ['11', 'spies like us', 'warner bros', 'john landis', '60088980'], ['12', 'a view to a kill', 'united artists', 'john glen', '50300000'], ['13', 'fletch', 'universal', 'michael ritchie', '50600000'], ['14', "national lampoon 's european vacation", 'warner bros', 'amy heckerling', '49364621'], ['15', 'mask', 'universal', 'peter bogdanovich', '48230162'], ['16', "brewster 's millions", 'universal', 'walter hill', '45833132'], ['17', 'the breakfast club', 'universal', 'john hughes', '45000000'], ['18', 'white nights', 'columbia', 'taylor hackford', '42160849'], ['19', 'pale rider', 'warner bros', 'clint eastwood', '41410568'], ['20', "pee - wee 's big adventure", 'warner bros', 'tim burton', '40940662']] |
2007 japanese television dramas | https://en.wikipedia.org/wiki/2007_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539861-3.html.csv | comparative | the 2007 japanese drama titled ' yama onna kabe onna ' had more episodes than the drama titled ' jotei ' . | {'row_1': '10', 'row_2': '15', 'col': '4', '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', 'romaji title', 'yama onna kabe onna'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose romaji title record fuzzily matches to yama onna kabe onna .', 'tostr': 'filter_eq { all_rows ; romaji title ; yama onna kabe onna }'}, 'episodes'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; romaji title ; yama onna kabe onna } ; episodes }', 'tointer': 'select the rows whose romaji title record fuzzily matches to yama onna kabe onna . take the episodes record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'romaji title', 'jotei'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose romaji title record fuzzily matches to jotei .', 'tostr': 'filter_eq { all_rows ; romaji title ; jotei }'}, 'episodes'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; romaji title ; jotei } ; episodes }', 'tointer': 'select the rows whose romaji title record fuzzily matches to jotei . take the episodes record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; romaji title ; yama onna kabe onna } ; episodes } ; hop { filter_eq { all_rows ; romaji title ; jotei } ; episodes } } = true', 'tointer': 'select the rows whose romaji title record fuzzily matches to yama onna kabe onna . take the episodes record of this row . select the rows whose romaji title record fuzzily matches to jotei . take the episodes record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; romaji title ; yama onna kabe onna } ; episodes } ; hop { filter_eq { all_rows ; romaji title ; jotei } ; episodes } } = true | select the rows whose romaji title record fuzzily matches to yama onna kabe onna . take the episodes record of this row . select the rows whose romaji title record fuzzily matches to jotei . take the episodes 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, 'romaji title_7': 7, 'yama onna kabe onna_8': 8, 'episodes_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'romaji title_11': 11, 'jotei_12': 12, 'episodes_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', 'romaji title_7': 'romaji title', 'yama onna kabe onna_8': 'yama onna kabe onna', 'episodes_9': 'episodes', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'romaji title_11': 'romaji title', 'jotei_12': 'jotei', 'episodes_13': 'episodes'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'romaji title_7': [0], 'yama onna kabe onna_8': [0], 'episodes_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'romaji title_11': [1], 'jotei_12': [1], 'episodes_13': [3]} | ['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings'] | [['スシ王子 ！', 'sushi ouji !', 'tv asahi', '8', '7.5 %'], ['菊次郎とさき 3', 'kikujirou to saki 3', 'tv asahi', '11', '9.3 %'], ['牛に願いを love & farm', 'ushi ni negai wo - love & farm', 'fuji tv', '11', '8.7 %'], ['ライフ', 'life', 'fuji tv', '11', '12.16 %'], ['受験の神様', 'juken no kamisama', 'ntv', '9', '9.5 %'], ['パパとムスメの7日間', 'papa to musume no nanokakan', 'tbs', '7', '13.9 %'], ['肩ごしの恋人', 'katagoshi no koibito', 'tbs', '9', '7.4 %'], ['花ざかりの君たちへ ～ イケメン ♂ パラダイス ～', 'hanazakari no kimitachi e ～ ikemen ♂ paradise ～', 'fuji tv', '12', '17.04 %'], ['ファースト ・ キス', 'first kiss', 'fuji tv', '11', '14.1 %'], ['山おんな壁おんな', 'yama onna kabe onna', 'fuji tv', '12', '12.1 %'], ['ホタルノヒカリ', 'hotaru no hikari', 'ntv', '10', '13.6 %'], ['山田太郎ものがたり', 'yamada taro monogatari', 'tbs', '10', '15.24 %'], ['探偵学園q', 'tantei gakuen q', 'ntv', '11', '11.1 %'], ['地獄の沙汰もヨメ次第', 'jigoku no sada mo yome shidai', 'tbs', '10', '10.3 %'], ['女帝', 'jotei', 'tv asahi', '10', '14.4 %']] |
fiba eurobasket 2007 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-14.html.csv | unique | erazem lorbek is the only player for the fiba eurobasket 2007 squads that currently plays for lottomatica roma . | {'scope': 'all', 'row': '12', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'lottomatica roma', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current club', 'lottomatica roma'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current club record fuzzily matches to lottomatica roma .', 'tostr': 'filter_eq { all_rows ; current club ; lottomatica roma }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; current club ; lottomatica roma } }', 'tointer': 'select the rows whose current club record fuzzily matches to lottomatica roma . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current club', 'lottomatica roma'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current club record fuzzily matches to lottomatica roma .', 'tostr': 'filter_eq { all_rows ; current club ; lottomatica roma }'}, 'player'], 'result': 'erazem lorbek', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; current club ; lottomatica roma } ; player }'}, 'erazem lorbek'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; current club ; lottomatica roma } ; player } ; erazem lorbek }', 'tointer': 'the player record of this unqiue row is erazem lorbek .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; current club ; lottomatica roma } } ; eq { hop { filter_eq { all_rows ; current club ; lottomatica roma } ; player } ; erazem lorbek } } = true', 'tointer': 'select the rows whose current club record fuzzily matches to lottomatica roma . there is only one such row in the table . the player record of this unqiue row is erazem lorbek .'} | and { only { filter_eq { all_rows ; current club ; lottomatica roma } } ; eq { hop { filter_eq { all_rows ; current club ; lottomatica roma } ; player } ; erazem lorbek } } = true | select the rows whose current club record fuzzily matches to lottomatica roma . there is only one such row in the table . the player record of this unqiue row is erazem lorbek . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'current club_7': 7, 'lottomatica roma_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'erazem lorbek_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'current club_7': 'current club', 'lottomatica roma_8': 'lottomatica roma', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'erazem lorbek_10': 'erazem lorbek'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'current club_7': [0], 'lottomatica roma_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'erazem lorbek_10': [3]} | ['player', 'height', 'position', 'year born', 'current club'] | [['sandi čebular', '1.94', 'guard', '1986', 'unattached'], ['jaka lakovič', '1.86', 'guard', '1978', 'axa fc barcelona'], ['aleksandar ćapin', '1.86', 'guard', '1982', 'whirlpool varese'], ['goran dragić', '1.88', 'guard', '1986', 'tau cerámica'], ['rasho nesterovič', '2.14', 'center', '1976', 'toronto raptors'], ['matjaž smodiš', '2.05', 'forward', '1979', 'cska moscow'], ['uroš slokar', '2.09', 'center', '1983', 'triumph lyubertsy'], ['jaka klobučar', '1.94', 'guard', '1987', 'geoplin slovan'], ['goran jagodnik', '2.02', 'forward', '1974', 'hemofarm'], ['domen lorbek', '1.96', 'guard', '1985', 'mmt estudiantes'], ['gašper vidmar', '2.08', 'center', '1987', 'fenerbahçe ülker'], ['erazem lorbek', '2.09', 'center', '1984', 'lottomatica roma']] |
2007 calgary stampeders season | https://en.wikipedia.org/wiki/2007_Calgary_Stampeders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12297537-1.html.csv | unique | henry bekkering was the only player that the calgary stampeders drafted from eastern washington college . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'eastern washington', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'eastern washington'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to eastern washington .', 'tostr': 'filter_eq { all_rows ; school / club team ; eastern washington }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; school / club team ; eastern washington } }', 'tointer': 'select the rows whose school / club team record fuzzily matches to eastern washington . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'eastern washington'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to eastern washington .', 'tostr': 'filter_eq { all_rows ; school / club team ; eastern washington }'}, 'player'], 'result': 'henry bekkering', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school / club team ; eastern washington } ; player }'}, 'henry bekkering'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; school / club team ; eastern washington } ; player } ; henry bekkering }', 'tointer': 'the player record of this unqiue row is henry bekkering .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; school / club team ; eastern washington } } ; eq { hop { filter_eq { all_rows ; school / club team ; eastern washington } ; player } ; henry bekkering } } = true', 'tointer': 'select the rows whose school / club team record fuzzily matches to eastern washington . there is only one such row in the table . the player record of this unqiue row is henry bekkering .'} | and { only { filter_eq { all_rows ; school / club team ; eastern washington } } ; eq { hop { filter_eq { all_rows ; school / club team ; eastern washington } ; player } ; henry bekkering } } = true | select the rows whose school / club team record fuzzily matches to eastern washington . there is only one such row in the table . the player record of this unqiue row is henry bekkering . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / club team_7': 7, 'eastern washington_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'henry bekkering_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / club team_7': 'school / club team', 'eastern washington_8': 'eastern washington', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'henry bekkering_10': 'henry bekkering'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / club team_7': [0], 'eastern washington_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'henry bekkering_10': [3]} | ['round', 'pick', 'player', 'position', 'school / club team'] | [['1', '3', 'mike gyetvai', 'ol', 'michigan state'], ['1', '5', 'justin phillips', 'lb', 'wilfrid laurier'], ['1', '6', 'jabari arthur', 'wr', 'akron'], ['2', '14', 'kevin challenger', 'wr', 'boston college'], ['3', '21', 'patrick macdonald', 'dl', 'alberta'], ['5', '35', 'henry bekkering', 'k', 'eastern washington'], ['5', '38', 'ian hazlett', 'lb', "queen 's"], ['6', '45', 'greg hetherington', 'sb', 'mcgill']] |
enernoc | https://en.wikipedia.org/wiki/EnerNOC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12752072-1.html.csv | unique | enernoc new zealand limited is the only enernoc company in new zealand . | {'scope': 'all', 'row': '15', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'new zealand', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'new zealand'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to new zealand .', 'tostr': 'filter_eq { all_rows ; country ; new zealand }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; new zealand } }', 'tointer': 'select the rows whose country record fuzzily matches to new zealand . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'new zealand'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to new zealand .', 'tostr': 'filter_eq { all_rows ; country ; new zealand }'}, 'company'], 'result': 'enernoc new zealand limited', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; new zealand } ; company }'}, 'enernoc new zealand limited'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; new zealand } ; company } ; enernoc new zealand limited }', 'tointer': 'the company record of this unqiue row is enernoc new zealand limited .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; new zealand } } ; eq { hop { filter_eq { all_rows ; country ; new zealand } ; company } ; enernoc new zealand limited } } = true', 'tointer': 'select the rows whose country record fuzzily matches to new zealand . there is only one such row in the table . the company record of this unqiue row is enernoc new zealand limited .'} | and { only { filter_eq { all_rows ; country ; new zealand } } ; eq { hop { filter_eq { all_rows ; country ; new zealand } ; company } ; enernoc new zealand limited } } = true | select the rows whose country record fuzzily matches to new zealand . there is only one such row in the table . the company record of this unqiue row is enernoc new zealand limited . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'new zealand_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'company_9': 9, 'enernoc new zealand limited_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'new zealand_8': 'new zealand', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'company_9': 'company', 'enernoc new zealand limited_10': 'enernoc new zealand limited'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'new zealand_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'company_9': [2], 'enernoc new zealand limited_10': [3]} | ['date', 'company', 'business', 'country', 'value ( usd )'] | [['unknown', 'celerity energy partners san diego llc', 'energy', 'united states', 'unknown'], ['2009', 'cogent energy , inc', 'green building', 'united states', 'unknown'], ['unknown', 'enoc securities corporation', 'securities', 'united states', 'unknown'], ['unknown', 'enernoc ltd', 'energy', 'canada', 'unknown'], ['unknown', 'enernoc uk limited', 'energy', 'united kingdom', 'unknown'], ['unknown', 'mdenergy , llc', 'energy', 'united states', 'unknown'], ['unknown', 'pinpoint power dr llc', 'energy', 'united states', 'unknown'], ['unknown', 'south river consulting , llc', 'energy', 'united states', 'unknown'], ['unknown', 'global energy partners , inc', 'energy', 'united states', 'unknown'], ['2011', 'm2 m communications corporation', 'energy', 'united states', 'unknown'], ['unknown', 'enernoc australia pty ltd', 'energy', 'australia', 'unknown'], ['unknown', 'dmt energy pty ltd', 'energy', 'australia', 'unknown'], ['unknown', 'energy response holdings pty ltd', 'energy', 'australia', 'unknown'], ['unknown', 'enernoc pty ltd', 'energy', 'australia', 'unknown'], ['unknown', 'enernoc new zealand limited', 'energy', 'new zealand', 'unknown'], ['unknown', 'high street corporation pty ltd', 'energy', 'australia', 'unknown']] |
demographics of imperial japan | https://en.wikipedia.org/wiki/Demographics_of_Imperial_Japan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1980653-5.html.csv | ordinal | fuzan had the third largest population in the 1910 census of imperial japan . | {'row': '2', 'col': '4', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', '1910 census', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; 1910 census ; 3 }'}, 'city'], 'result': 'fuzan', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; 1910 census ; 3 } ; city }'}, 'fuzan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; 1910 census ; 3 } ; city } ; fuzan } = true', 'tointer': 'select the row whose 1910 census record of all rows is 3rd maximum . the city record of this row is fuzan .'} | eq { hop { nth_argmax { all_rows ; 1910 census ; 3 } ; city } ; fuzan } = true | select the row whose 1910 census record of all rows is 3rd maximum . the city record of this row is fuzan . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, '1910 census_5': 5, '3_6': 6, 'city_7': 7, 'fuzan_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', '1910 census_5': '1910 census', '3_6': '3', 'city_7': 'city', 'fuzan_8': 'fuzan'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], '1910 census_5': [0], '3_6': [0], 'city_7': [1], 'fuzan_8': [2]} | ['rank', 'city', '1890 census', '1910 census', '1920 census', '1930 census', '1940 census'] | [['1', 'keijō', '1165000', '230000', '247000', '350000', '1100000'], ['2', 'fuzan', 'na', '81000', '74000', '130000', '400000'], ['3', 'heijō', 'na', '40000', '60000', '137000', '286000'], ['4', 'jinsen', 'na', '30000', '40000', '54000', '171000'], ['5', 'taihoku', '78000', '95000', '164000', '249000', '326000'], ['6', 'tainan', 'na', '44000', '112000', '166000', '296000']] |
octagonal | https://en.wikipedia.org/wiki/Octagonal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1284347-3.html.csv | superlative | manikato stakes was the first race that octagonal participated in . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'race'], 'result': 'manikato stakes', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; race }'}, 'manikato stakes'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; race } ; manikato stakes } = true', 'tointer': 'select the row whose date record of all rows is minimum . the race record of this row is manikato stakes .'} | eq { hop { argmin { all_rows ; date } ; race } ; manikato stakes } = true | select the row whose date record of all rows is minimum . the race record of this row is manikato stakes . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'race_6': 6, 'manikato stakes_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'race_6': 'race', 'manikato stakes_7': 'manikato stakes'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'race_6': [1], 'manikato stakes_7': [2]} | ['result', 'date', 'race', 'venue', 'group', 'distance', 'weight ( kg )', 'jockey', 'winner / 2nd'] | [['6th', '17 aug 1996', 'manikato stakes', 'moonee valley', 'g1', '1200 m', '57', 'd gauci', '1st - poetic king'], ['7th', '31 aug 1996', 'memsie stakes', 'caulfield', 'g2', '1400 m', '57', 'd gauci', '1st - sir boom'], ['5th', '14 sep 1996', 'feehan stakes', 'moonee valley', 'g2', '1600 m', '57', 'd gauci', '1st - toil'], ['won', '22 sep 1996', 'underwood stakes', 'caulfield', 'g1', '1800 m', '57', 'd beadman', '2nd - seascay'], ['4th', '12 oct 1996', 'caulfield stakes', 'caulfield', 'g1', '2000 m', '57', 'd beadman', '1st - juggler'], ['5th', '26 oct 1996', 'cox plate', 'moonee valley', 'g1', '2040 m', '57', 'd gauci', '1st - saintly'], ['9th', '2 nov 1996', 'mackinnon stakes', 'flemington', 'g1', '2000 m', '57', 'd beadman', '1st - all our mob'], ['2nd', '15 feb 1997', 'apollo stakes', 'warwick farm', 'g2', '1400 m', '57', 'd beadman', '1st - juggler'], ['won', '22 feb 1997', 'chipping norton stakes', 'warwick farm', 'g1', '1600 m', '57', 's dye', '2nd - juggler'], ['won', '10 mar 1997', 'australia cup', 'flemington', 'g1', '2000 m', '57', 's dye', '2nd - gold city'], ['won', '22 mar 1997', 'mercedes classic', 'rosehill', 'g1', '2400 m', '57', 's dye', '2nd - arkady'], ['2nd', '12 apr 1997', 'queen elizabeth stakes', 'randwick', 'g1', '2000 m', '57', 's dye', '1st - intergaze']] |
list of asian academy award winners and nominees | https://en.wikipedia.org/wiki/List_of_Asian_Academy_Award_winners_and_nominees | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11296015-5.html.csv | count | three of the films were released after the year 2000 . | {'scope': 'all', 'criterion': 'greater_than', 'value': '2000', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'year', '2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is greater than 2000 .', 'tostr': 'filter_greater { all_rows ; year ; 2000 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; year ; 2000 } }', 'tointer': 'select the rows whose year record is greater than 2000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; year ; 2000 } } ; 3 } = true', 'tointer': 'select the rows whose year record is greater than 2000 . the number of such rows is 3 .'} | eq { count { filter_greater { all_rows ; year ; 2000 } } ; 3 } = true | select the rows whose year record is greater than 2000 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'year_5': 5, '2000_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'year_5': 'year', '2000_6': '2000', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'year_5': [0], '2000_6': [0], '3_7': [2]} | ['year', 'name', 'film', 'role', 'status'] | [['year', 'name', 'film', 'role', 'status'], ['1957', 'miyoshi umeki', 'sayonara', 'katsumi kelly', 'won'], ['1985', 'meg tilly', 'agnes of god', 'sister agnes', 'nominated'], ['1994', 'jennifer tilly', 'bullets over broadway', 'olive neal', 'nominated'], ['2003', 'shohreh aghdashloo', 'house of sand and fog', 'nadereh behrani', 'nominated'], ['2006', 'rinko kikuchi', 'babel', 'chieko wataya', 'nominated'], ['2010', 'hailee steinfeld', 'true grit', 'mattie ross', 'nominated']] |
neden ( album ) | https://en.wikipedia.org/wiki/Neden_%28album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12355593-1.html.csv | majority | the majority of the songs on the album " neden " are less than 4 minutes long . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '4:00', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'time', '4:00'], 'result': True, 'ind': 0, 'tointer': 'for the time records of all rows , most of them are less than 4:00 .', 'tostr': 'most_less { all_rows ; time ; 4:00 } = true'} | most_less { all_rows ; time ; 4:00 } = true | for the time records of all rows , most of them are less than 4:00 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'time_3': 3, '4:00_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'time_3': 'time', '4:00_4': '4:00'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'time_3': [0], '4:00_4': [0]} | ['title', 'english translation', 'lyrics by', 'music by', 'time'] | [['hayırsız', 'scapegrace', 'candan erçetin', 'macedon anonymous', '4:31'], ['neden', 'why', 'candan erçetin', 'anonymous', '4:02'], ['gamsız hayat', 'carefree life', 'aylin atalay & candan erçetin', 'candan erçetin', '3:50'], ['parçalandım', 'i break into pieces', 'candan erçetin', 'alper erinç & candan erçetin', '3:57'], ['anlatma sakın', "do n't tell", 'sinan', 'candan erçetin', '3:36'], ['bensiz', 'without me', 'sinan', 'neslihan engin & candan erçetin', '3:17'], ['yapayalnız', 'very lonely', 'aylin atalay', 'candan erçetin', '4:13'], ['mühim değil', "it 's ok", 'sinan', 'neslihan engin & candan erçetin', '4:13'], ['ben böyleyim', 'this is the way i am', 'ümit aksu', 'armando manzanero', '3:44'], ['korkarım', "i 'm afraid", 'aylin atalay', 'candan erçetin & neslihan engin', '3:17'], ['dünya hali', 'nature of world', 'candan erçetin', 'candan erçetin', '3:37'], ['yüksek yüksek tepelere', 'to high hills', 'anonymous', 'anonymous', '4:08']] |
list of ra - aus certified aircraft types | https://en.wikipedia.org/wiki/List_of_RA-Aus_certified_aircraft_types | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17699890-1.html.csv | count | there are 6 aus certified aircraft types manufactured by jabiru . | {'scope': 'all', 'criterion': 'equal', 'value': 'jabiru', 'result': '6', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'jabiru'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manufacturer record fuzzily matches to jabiru .', 'tostr': 'filter_eq { all_rows ; manufacturer ; jabiru }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; manufacturer ; jabiru } }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to jabiru . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; manufacturer ; jabiru } } ; 6 } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to jabiru . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; manufacturer ; jabiru } } ; 6 } = true | select the rows whose manufacturer record fuzzily matches to jabiru . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'manufacturer_5': 5, 'jabiru_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'manufacturer_5': 'manufacturer', 'jabiru_6': 'jabiru', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manufacturer_5': [0], 'jabiru_6': [0], '6_7': [2]} | ['manufacturer', 'model', 'kit / factory', 'wing', 'seats'] | [['aeroprakt', 'a - 22 foxbat', 'factory', 'high wing', '2'], ['allegro', 'allegro 2000 and allegro 2007', 'approved kit and factory built', 'high wing', '2'], ['evektor', 'sportstar', 'factory', 'low', '2'], ['jabiru', 'j120', 'factory', 'high', '2'], ['jabiru', 'j160', 'both', 'high', '2'], ['jabiru', 'j170', 'both', 'high', '2'], ['jabiru', 'j230', 'both', 'high', '2'], ['jabiru', 'j250', 'kit', 'high', '2'], ['jabiru', 'ul - d', 'kit', 'high', '2'], ['pipistrel', 'sinus', 'factory & kit built approved', 'high wing', '2'], ['pipistrel', 'virus - virus sw ( short wing )', 'factory & kit built approved', 'high wing', '2'], ['savage classic , savage cruiser , savage cub', 'cub', 'factory & kit built approved', 'high wing', '2'], ['tl 2000 sting carbon', 'sting', 'approved factory built', 'low wing', '2'], ['raj hamsa ultralights', 'x - air hanuman', 'approved kit or lsa', 'high wing', '2'], ['x - air standard', 'x - air standard', 'approved kit', 'high wing', '2']] |
ireland in the eurovision song contest 1990 | https://en.wikipedia.org/wiki/Ireland_in_the_Eurovision_Song_Contest_1990 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16729685-1.html.csv | aggregation | the average amount of points accumulated between all songs in the 1990 ireland in the eurovision song contest is 84 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '84', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '84', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '84'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 84 } = true', 'tointer': 'the average of the points record of all rows is 84 .'} | round_eq { avg { all_rows ; points } ; 84 } = true | the average of the points record of all rows is 84 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '84_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '84_5': '84'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '84_5': [1]} | ['draw', 'artist', 'song', 'points', 'place'] | [['1', 'the memories', 'if it means losing you', '57', '8th'], ['2', 'ann breen', 'oh , darling', '80', '4th'], ['3', 'fran meen', 'say that you love me', '66', '6th'], ['4', 'dreams', "sin sin ( that 's that )", '73', '5th'], ['5', 'connor stevens', 'count on me', '88', '3rd'], ['6', 'linda martin and friends', 'all the people in the world', '105', '2nd'], ['7', 'maggie toal', 'feed him with love', '61', '7th'], ['8', 'liam reilly', 'somewhere in europe', '130', '1st']] |
list of ottawa senators draft picks | https://en.wikipedia.org/wiki/List_of_Ottawa_Senators_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11803648-7.html.csv | unique | julien vauclair was the only player from switzerland that was drafted by the ottawa senators . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'switzerland', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'switzerland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to switzerland .', 'tostr': 'filter_eq { all_rows ; nationality ; switzerland }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; switzerland } }', 'tointer': 'select the rows whose nationality record fuzzily matches to switzerland . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'switzerland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to switzerland .', 'tostr': 'filter_eq { all_rows ; nationality ; switzerland }'}, 'player'], 'result': 'julien vauclair', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; switzerland } ; player }'}, 'julien vauclair'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; switzerland } ; player } ; julien vauclair }', 'tointer': 'the player record of this unqiue row is julien vauclair .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; switzerland } } ; eq { hop { filter_eq { all_rows ; nationality ; switzerland } ; player } ; julien vauclair } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to switzerland . there is only one such row in the table . the player record of this unqiue row is julien vauclair .'} | and { only { filter_eq { all_rows ; nationality ; switzerland } } ; eq { hop { filter_eq { all_rows ; nationality ; switzerland } ; player } ; julien vauclair } } = true | select the rows whose nationality record fuzzily matches to switzerland . there is only one such row in the table . the player record of this unqiue row is julien vauclair . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'switzerland_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'julien vauclair_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'switzerland_8': 'switzerland', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'julien vauclair_10': 'julien vauclair'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'switzerland_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'julien vauclair_10': [3]} | ['round', 'overall', 'player', 'nationality', 'club team'] | [['1', '15', 'mathieu chouinard', 'canada', 'shawinigan cataractes ( qmjhl )'], ['2', '44', 'mike fisher', 'canada', 'sudbury wolves ( ohl )'], ['2', '58', 'chris bala', 'united states', 'harvard university ( ncaa )'], ['3', '74', 'julien vauclair', 'switzerland', 'lugano ( switzerland )'], ['4', '101', 'petr schastlivy', 'russia', 'yaroslavl torpedo ( russia )'], ['5', '130', 'gavin mcleod', 'canada', 'kelowna rockets ( whl )'], ['6', '161', 'chris neil', 'canada', 'north bay centennials ( ohl )'], ['7', '188', 'michel periard', 'canada', 'shawinigan cataractes ( qmjhl )'], ['8', '223', 'sergei verenkin', 'russia', 'yaroslavl torpedo ( russia )'], ['9', '246', 'rastislav pavlikovsky', 'slovakia', 'utah grizzlies ( ihl )']] |
moses ndiema masai | https://en.wikipedia.org/wiki/Moses_Ndiema_Masai | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16682451-1.html.csv | count | moses ndiema masai competed in the 10000 m three times . | {'scope': 'all', 'criterion': 'equal', 'value': '10000 m', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', '10000 m'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to 10000 m .', 'tostr': 'filter_eq { all_rows ; event ; 10000 m }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; event ; 10000 m } }', 'tointer': 'select the rows whose event record fuzzily matches to 10000 m . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; event ; 10000 m } } ; 3 } = true', 'tointer': 'select the rows whose event record fuzzily matches to 10000 m . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; event ; 10000 m } } ; 3 } = true | select the rows whose event record fuzzily matches to 10000 m . 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, 'event_5': 5, '10000 m_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', 'event_5': 'event', '10000 m_6': '10000 m', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'event_5': [0], '10000 m_6': [0], '3_7': [2]} | ['year', 'competition', 'venue', 'position', 'event'] | [['2004', 'world junior championships', 'grosseto , italy', '10th', '10000 m'], ['2005', 'african junior championships', 'radès , tunisia', '1st', '5000 m'], ['2005', 'african junior championships', 'radès , tunisia', '1st', '10000 m'], ['2007', 'world athletics final', 'stuttgart , germany', '3rd', '5000 m'], ['2008', 'world cross country championships', 'edinburgh , scotland', '5th', 'senior race'], ['2008', 'world cross country championships', 'edinburgh , scotland', '1st', 'team competition'], ['2009', 'world championships', 'berlin , germany', '3rd', '10000 m'], ['2013', 'okpekpe international road race', 'okpekpe , nigeria', '1st', '10 kilometres']] |
sandro cortese | https://en.wikipedia.org/wiki/Sandro_Cortese | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16710541-2.html.csv | superlative | the highest number of points occurred in the year 2012 . | {'scope': 'all', 'col_superlative': '11', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'pts'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; pts }'}, 'season'], 'result': '2012', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; pts } ; season }'}, '2012'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; pts } ; season } ; 2012 } = true', 'tointer': 'select the row whose pts record of all rows is maximum . the season record of this row is 2012 .'} | eq { hop { argmax { all_rows ; pts } ; season } ; 2012 } = true | select the row whose pts record of all rows is maximum . the season record of this row is 2012 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'pts_5': 5, 'season_6': 6, '2012_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'pts_5': 'pts', 'season_6': 'season', '2012_7': '2012'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'pts_5': [0], 'season_6': [1], '2012_7': [2]} | ['season', 'class', 'team', 'motorcycle', 'type', 'races', 'wins', 'podiums', 'poles', 'fastest laps', 'pts', 'position'] | [['2005', '125cc', 'kiefer - bos - castrol honda', 'honda', 'honda rs125r', '16', '0', '0', '0', '0', '8', '26th'], ['2006', '125cc', 'elit - caffè latte', 'honda', 'honda rs125r', '16', '0', '0', '0', '0', '23', '17th'], ['2007', '125cc', 'emmi - caffè latte', 'aprilia', 'aprilia rs 125', '17', '0', '0', '0', '0', '66', '14th'], ['2008', '125cc', 'emmi - caffè latte', 'aprilia', 'aprilia rsa 125', '17', '0', '0', '0', '1', '141', '8th'], ['2009', '125cc', 'ajo interwetten', 'derbi', 'derbi rsa 125', '16', '0', '3', '1', '2', '130', '6th'], ['2010', '125cc', 'ajo motorsport', 'derbi', 'derbi rs 125 r', '17', '0', '2', '1', '2', '143', '7th'], ['2011', '125cc', 'intact - racing team germany', 'aprilia', 'aprilia rsa 125', '17', '2', '6', '1', '2', '225', '4th'], ['2012', 'moto3', 'red bull ktm ajo', 'ktm', 'ktm m32', '17', '5', '15', '7', '4', '325', '1st'], ['2013', 'moto2', 'dynavolt intact gp', 'kalex', 'kalex moto2', '16', '0', '0', '0', '0', '19', '20th']] |
2002 belarusian premier league | https://en.wikipedia.org/wiki/2002_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14747981-1.html.csv | superlative | minsk had the most teams of all the cities/locations in the 2002 league . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', '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', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; capacity }'}, 'location'], 'result': 'minsk', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; capacity } ; location }'}, 'minsk'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; capacity } ; location } ; minsk } = true', 'tointer': 'select the row whose capacity record of all rows is maximum . the location record of this row is minsk .'} | eq { hop { argmax { all_rows ; capacity } ; location } ; minsk } = true | select the row whose capacity record of all rows is maximum . the location record of this row is minsk . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'location_6': 6, 'minsk_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'location_6': 'location', 'minsk_7': 'minsk'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'location_6': [1], 'minsk_7': [2]} | ['team', 'location', 'venue', 'capacity', 'position in 2001'] | [['belshina', 'bobruisk', 'spartak , bobruisk', '3550', '1'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '2'], ['bate', 'borisov', 'city stadium , borisov', '5500', '3'], ['neman', 'grodno', 'neman', '6300', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['gomel', 'gomel', 'central , gomel', '11800', '6'], ['slavia', 'mozyr', 'yunost', '5500', '7'], ['torpedo - maz', 'minsk', 'torpedo , minsk', '5200', '8'], ['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '9'], ['molodechno - 2000', 'molodechno', 'city stadium , molodechno', '5500', '10'], ['dinamo brest', 'brest', 'osk brestskiy', '10080', '11'], ['lokomotiv - 96', 'vitebsk', 'central , vitebsk', '8300', '12'], ['torpedo', 'zhodino', 'torpedo , zhodino', '3020', 'first league , 1'], ['zvezda - va - bgu', 'minsk', 'traktor', '17600', 'first league , 2']] |
1938 vfl season | https://en.wikipedia.org/wiki/1938_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806592-9.html.csv | unique | the only venue with a crowd less than 10,000 was the corio oval . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '5', 'criterion': 'less_than', 'value': '10,000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10,000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is less than 10,000 .', 'tostr': 'filter_less { all_rows ; crowd ; 10,000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; crowd ; 10,000 } }', 'tointer': 'select the rows whose crowd record is less than 10,000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10,000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is less than 10,000 .', 'tostr': 'filter_less { all_rows ; crowd ; 10,000 }'}, 'venue'], 'result': 'corio oval', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; crowd ; 10,000 } ; venue }'}, 'corio oval'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; crowd ; 10,000 } ; venue } ; corio oval }', 'tointer': 'the venue record of this unqiue row is corio oval .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; crowd ; 10,000 } } ; eq { hop { filter_less { all_rows ; crowd ; 10,000 } ; venue } ; corio oval } } = true', 'tointer': 'select the rows whose crowd record is less than 10,000 . there is only one such row in the table . the venue record of this unqiue row is corio oval .'} | and { only { filter_less { all_rows ; crowd ; 10,000 } } ; eq { hop { filter_less { all_rows ; crowd ; 10,000 } ; venue } ; corio oval } } = true | select the rows whose crowd record is less than 10,000 . there is only one such row in the table . the venue record of this unqiue row is corio oval . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'crowd_7': 7, '10,000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'venue_9': 9, 'corio oval_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'crowd_7': 'crowd', '10,000_8': '10,000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'venue_9': 'venue', 'corio oval_10': 'corio oval'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'crowd_7': [0], '10,000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'venue_9': [2], 'corio oval_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '11.23 ( 89 )', 'hawthorn', '6.13 ( 49 )', 'corio oval', '7000', '18 june 1938'], ['fitzroy', '16.12 ( 108 )', 'south melbourne', '8.8 ( 56 )', 'brunswick street oval', '12000', '18 june 1938'], ['st kilda', '14.12 ( 96 )', 'melbourne', '16.16 ( 112 )', 'junction oval', '14000', '18 june 1938'], ['richmond', '15.14 ( 104 )', 'essendon', '15.9 ( 99 )', 'punt road oval', '20000', '18 june 1938'], ['footscray', '13.9 ( 87 )', 'collingwood', '10.5 ( 65 )', 'western oval', '18000', '18 june 1938'], ['north melbourne', '11.5 ( 71 )', 'carlton', '16.25 ( 121 )', 'arden street oval', '13000', '18 june 1938']] |
lexington legends | https://en.wikipedia.org/wiki/Lexington_Legends | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1031852-2.html.csv | aggregation | from the year 2001 to 2013 the lexington legends had an average winning percentage of .505 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '505', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'win %'], 'result': '505', 'ind': 0, 'tostr': 'avg { all_rows ; win % }'}, '505'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; win % } ; 505 } = true', 'tointer': 'the average of the win % record of all rows is 505 .'} | round_eq { avg { all_rows ; win % } ; 505 } = true | the average of the win % record of all rows is 505 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'win %_4': 4, '505_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'win %_4': 'win %', '505_5': '505'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'win %_4': [0], '505_5': [1]} | ['season', 'manager', 'record', 'win %', 'post - season record', 'post - season win %', 'mlb affiliate'] | [['2001', 'joe cannon', '92 - 48', '657', '4 - 0', '1.000', 'houston'], ['2002', 'joe cannon', '81 - 59', '579', '-', '-', 'houston'], ['2003 ♦', 'russ nixon', '75 - 63', '543', '0 - 2', '000', 'houston'], ['2004', 'iván dejesús', '68 - 72', '486', '-', '-', 'houston'], ['2005', 'tim bogar', '81 - 58', '583', '-', '-', 'houston'], ['2006 ♦', 'jack lind', '75 - 63', '543', '0 - 2', '000', 'houston'], ['2007', 'gregg langbehn', '59 - 81', '421', '-', '-', 'houston'], ['2008', 'gregg langbehn', '45 - 93', '326', '-', '-', 'houston'], ['2009', 'tom lawless', '68 - 72', '486', '-', '-', 'houston'], ['2010', 'rodney linares', '71 - 68', '511', '-', '-', 'houston'], ['2011', 'rodney linares', '59 - 79', '428', '-', '-', 'houston'], ['2012', 'iván dejesús', '69 - 69', '500', '-', '-', 'houston'], ['2013', 'brian buchanan', '44 - 42', '512', '-', '-', 'kansas city']] |
1992 pga championship | https://en.wikipedia.org/wiki/1992_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18121795-2.html.csv | superlative | hal sutton scored the highest total in the 1992 pga championship among all other players . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'player'], 'result': 'hal sutton', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; player }'}, 'hal sutton'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; player } ; hal sutton } = true', 'tointer': 'select the row whose total record of all rows is maximum . the player record of this row is hal sutton .'} | eq { hop { argmax { all_rows ; total } ; player } ; hal sutton } = true | select the row whose total record of all rows is maximum . the player record of this row is hal sutton . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'player_6': 6, 'hal sutton_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'player_6': 'player', 'hal sutton_7': 'hal sutton'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'player_6': [1], 'hal sutton_7': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par'] | [['jack nicklaus', 'united states', '1963 , 1971 , 1973 1975 , 1980', '150', '+ 8'], ['wayne grady', 'australia', '1990', '152', '+ 10'], ['john mahaffey', 'united states', '1978', '153', '+ 11'], ['hubert green', 'united states', '1985', '154', '+ 12'], ['hal sutton', 'united states', '1983', '155', '+ 13']] |
pasha kovalev | https://en.wikipedia.org/wiki/Pasha_Kovalev | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12051129-1.html.csv | majority | pasha kovalev had a safe result for his dance in the majority of weeks . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'safe', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'results', 'safe'], 'result': True, 'ind': 0, 'tointer': 'for the results records of all rows , most of them fuzzily match to safe .', 'tostr': 'most_eq { all_rows ; results ; safe } = true'} | most_eq { all_rows ; results ; safe } = true | for the results 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, 'results_3': 3, 'safe_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'results_3': 'results', 'safe_4': 'safe'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'results_3': [0], 'safe_4': [0]} | ['week', 'partner', 'style', 'choreographer ( s )', 'results'] | [['1', 'jessi peralta', 'smooth waltz', 'tony meredith', 'safe'], ['2', 'jessi peralta', 'jazz', 'tyce diorio', 'bottom three'], ['3', 'jessi peralta', 'cha cha', 'tony meredith melanie lapatin', 'safe'], ['4', 'sara von gillern', 'west coast swing', 'benji schwimmer heidi groskreutz', 'safe'], ['5', 'sara von gillern', 'jazz', 'mandy moore', 'safe'], ['6', 'lauren gottlieb', 'hip - hop', 'shane sparks', 'safe'], ['7', 'sabra johnson', 'broadway', 'tyce diorio', 'safe'], ['7', 'sabra johnson', 'quickstep', 'tony meredith melanie lapatin', 'safe'], ['8', 'lacey schwimmer', 'hip - hop', 'dave scott', 'top six'], ['8', 'lacey schwimmer', 'smooth waltz', 'hunter johnson', 'top six']] |
opec | https://en.wikipedia.org/wiki/OPEC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-166346-1.html.csv | superlative | in opec the most recent country to join the middle east was the united arab emirates in 1967 . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '9', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1,2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'middle east'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'middle east'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; region ; middle east }', 'tointer': 'select the rows whose region record fuzzily matches to middle east .'}, 'joined opec'], 'result': '1967', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; region ; middle east } ; joined opec }', 'tointer': 'select the rows whose region record fuzzily matches to middle east . the maximum joined opec record of these rows is 1967 .'}, '1967'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; region ; middle east } ; joined opec } ; 1967 }', 'tointer': 'select the rows whose region record fuzzily matches to middle east . the maximum joined opec record of these rows is 1967 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'middle east'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; region ; middle east }', 'tointer': 'select the rows whose region record fuzzily matches to middle east .'}, 'joined opec'], 'result': None, 'ind': 3, 'tostr': 'argmax { filter_eq { all_rows ; region ; middle east } ; joined opec }'}, 'country'], 'result': 'united arab emirates', 'ind': 4, 'tostr': 'hop { argmax { filter_eq { all_rows ; region ; middle east } ; joined opec } ; country }'}, 'united arab emirates'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; region ; middle east } ; joined opec } ; country } ; united arab emirates }', 'tointer': 'the country record of the row with superlative joined opec record is united arab emirates .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { max { filter_eq { all_rows ; region ; middle east } ; joined opec } ; 1967 } ; eq { hop { argmax { filter_eq { all_rows ; region ; middle east } ; joined opec } ; country } ; united arab emirates } } = true', 'tointer': 'select the rows whose region record fuzzily matches to middle east . the maximum joined opec record of these rows is 1967 . the country record of the row with superlative joined opec record is united arab emirates .'} | and { eq { max { filter_eq { all_rows ; region ; middle east } ; joined opec } ; 1967 } ; eq { hop { argmax { filter_eq { all_rows ; region ; middle east } ; joined opec } ; country } ; united arab emirates } } = true | select the rows whose region record fuzzily matches to middle east . the maximum joined opec record of these rows is 1967 . the country record of the row with superlative joined opec record is united arab emirates . | 8 | 7 | {'and_6': 6, 'result_7': 7, 'eq_2': 2, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_8': 8, 'region_9': 9, 'middle east_10': 10, 'joined opec_11': 11, '1967_12': 12, 'str_eq_5': 5, 'str_hop_4': 4, 'argmax_3': 3, 'joined opec_13': 13, 'country_14': 14, 'united arab emirates_15': 15} | {'and_6': 'and', 'result_7': 'true', 'eq_2': 'eq', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_8': 'all_rows', 'region_9': 'region', 'middle east_10': 'middle east', 'joined opec_11': 'joined opec', '1967_12': '1967', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'argmax_3': 'argmax', 'joined opec_13': 'joined opec', 'country_14': 'country', 'united arab emirates_15': 'united arab emirates'} | {'and_6': [7], 'result_7': [], 'eq_2': [6], 'max_1': [2], 'filter_str_eq_0': [1, 3], 'all_rows_8': [0], 'region_9': [0], 'middle east_10': [0], 'joined opec_11': [1], '1967_12': [2], 'str_eq_5': [6], 'str_hop_4': [5], 'argmax_3': [4], 'joined opec_13': [3], 'country_14': [4], 'united arab emirates_15': [5]} | ['country', 'region', 'joined opec', 'population ( july 2012 )', 'area ( km square )', 'production ( bbl / day )'] | [['algeria', 'africa', '1969', '37367226', '2381740', '2125000 ( 16th )'], ['angola', 'africa', '2007', '18056072', '1246700', '1948000 ( 17th )'], ['iraq', 'middle east', '1960', '31129225', '437072', '3200000 ( 12th )'], ['kuwait', 'middle east', '1960', '2646314', '17820', '2494000 ( 10th )'], ['libya', 'africa', '1962', '5613380', '1759540', '2210000 ( 15th )'], ['nigeria', 'africa', '1971', '170123740', '923768', '2211000 ( 14th )'], ['qatar', 'middle east', '1961', '1951591', '11437', '1213000 ( 21st )'], ['saudi arabia', 'middle east', '1960', '26534504', '2149690', '8800000 ( 1st )'], ['united arab emirates', 'middle east', '1967', '5314317', '83600', '2798000 ( 8th )'], ['venezuela', 'south america', '1960', '28047938', '912050', '2472000 ( 11th )']] |
2008 afl season | https://en.wikipedia.org/wiki/2008_AFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14312471-3.html.csv | ordinal | essendon had the second highest score amongst the home teams during the 2008 afl season . | {'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', 'home team score', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; home team score ; 2 }'}, 'home team'], 'result': 'essendon', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; home team score ; 2 } ; home team }'}, 'essendon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; home team score ; 2 } ; home team } ; essendon } = true', 'tointer': 'select the row whose home team score record of all rows is 2nd maximum . the home team record of this row is essendon .'} | eq { hop { nth_argmax { all_rows ; home team score ; 2 } ; home team } ; essendon } = true | select the row whose home team score record of all rows is 2nd maximum . the home team record of this row is essendon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'home team score_5': 5, '2_6': 6, 'home team_7': 7, 'essendon_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', 'home team score_5': 'home team score', '2_6': '2', 'home team_7': 'home team', 'essendon_8': 'essendon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'home team score_5': [0], '2_6': [0], 'home team_7': [1], 'essendon_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'report'] | [['collingwood', '8.14 ( 62 )', 'hawthorn', '17.14 ( 116 )', 'mcg', '58307', 'friday , 1 august', 'aflcomau'], ['essendon', '19.10 ( 124 )', 'melbourne', '17.6 ( 108 )', 'mcg', '46334', 'saturday , 2 august', 'aflcomau'], ['adelaide', '13.16 ( 94 )', 'carlton', '12.14 ( 86 )', 'aami stadium', '40730', 'saturday , 2 august', 'aflcomau'], ['geelong', '20.14 ( 134 )', 'richmond', '10.11 ( 71 )', 'telstra dome', '42238', 'saturday , 2 august', 'aflcomau'], ['north melbourne', '13.14 ( 92 )', 'brisbane lions', '11.18 ( 84 )', 'gold coast stadium', '10037', 'saturday , 2 august', 'aflcomau'], ['western bulldogs', '17.11 ( 113 )', 'sydney', '14.13 ( 97 )', 'manuka oval', '13550', 'sunday , 3 august', 'aflcomau'], ['st kilda', '14.17 ( 101 )', 'port adelaide', '14.9 ( 93 )', 'telstra dome', '22878', 'sunday , 3 august', 'aflcomau']] |
list of awards and nominations received by er | https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_ER | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18540176-11.html.csv | comparative | john wells was nominated for an award before carol flint was nominated for one . | {'row_1': '1', 'row_2': '2', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nominee ( s )', 'john wells'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nominee ( s ) record fuzzily matches to john wells .', 'tostr': 'filter_eq { all_rows ; nominee ( s ) ; john wells }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nominee ( s ) ; john wells } ; year }', 'tointer': 'select the rows whose nominee ( s ) record fuzzily matches to john wells . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nominee ( s )', 'carol flint'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nominee ( s ) record fuzzily matches to carol flint .', 'tostr': 'filter_eq { all_rows ; nominee ( s ) ; carol flint }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nominee ( s ) ; carol flint } ; year }', 'tointer': 'select the rows whose nominee ( s ) record fuzzily matches to carol flint . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; nominee ( s ) ; john wells } ; year } ; hop { filter_eq { all_rows ; nominee ( s ) ; carol flint } ; year } } = true', 'tointer': 'select the rows whose nominee ( s ) record fuzzily matches to john wells . take the year record of this row . select the rows whose nominee ( s ) record fuzzily matches to carol flint . take the year record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; nominee ( s ) ; john wells } ; year } ; hop { filter_eq { all_rows ; nominee ( s ) ; carol flint } ; year } } = true | select the rows whose nominee ( s ) record fuzzily matches to john wells . take the year record of this row . select the rows whose nominee ( s ) record fuzzily matches to carol flint . take the year record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nominee (s)_7': 7, 'john wells_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nominee (s)_11': 11, 'carol flint_12': 12, 'year_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nominee (s)_7': 'nominee ( s )', 'john wells_8': 'john wells', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nominee (s)_11': 'nominee ( s )', 'carol flint_12': 'carol flint', 'year_13': 'year'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nominee (s)_7': [0], 'john wells_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nominee (s)_11': [1], 'carol flint_12': [1], 'year_13': [3]} | ['year', 'category', 'nominee ( s )', 'episode', 'result'] | [['1996', '60 minute category', 'john wells', 'the healers', 'nominated'], ['1998', '60 minute category', 'carol flint', 'family practice', 'nominated'], ['2001', '60 minute category', 'john wells', 'a walk in the woods', 'nominated'], ['2003', '60 minute category', 'john wells', 'on the beach', 'nominated'], ['2004', '60 minute category', 'john wells', 'makemba', 'nominated'], ['2005', '60 minute category', 'dee johnson', 'alone in a crowd', 'nominated'], ['2006', '60 minute category', 'janine sherman', 'darfur', 'nominated'], ['2007', '60 minute category', 'r scott gemmill , david zabel', 'there are no angels here', 'won']] |
papal election , 1280 - 81 | https://en.wikipedia.org/wiki/Papal_election%2C_1280%E2%80%9381 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18924985-1.html.csv | unique | only one of the electors came from alatri . | {'scope': 'all', 'row': '10', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'alatri', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'alatri'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to alatri .', 'tostr': 'filter_eq { all_rows ; nationality ; alatri }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; alatri } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to alatri . there is only one such row in the table .'} | only { filter_eq { all_rows ; nationality ; alatri } } = true | select the rows whose nationality record fuzzily matches to alatri . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'nationality_4': 4, 'alatri_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'nationality_4': 'nationality', 'alatri_5': 'alatri'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'nationality_4': [0], 'alatri_5': [0]} | ['elector', 'nationality', 'cardinalatial order and title', 'elevated', 'elevator'] | [['ordonho alvares', 'portuguese', 'cardinal - bishop of frascati', '1278 , march 12', 'nicholas iii'], ['latino malabranca orsini , op', 'rome', 'cardinal - bishop of ostia e velletri', '1278 , march 12', 'nicholas iii'], ['bentivenga da bentivengi , ofm', 'acquasparta', 'cardinal - bishop of albano', '1278 , march 12', 'nicholas iii'], ['anchero pantalãone', 'french', 'cardinal - priest of s prassede', '1262 , may 22', 'urban iv'], ['simon de brion', 'french', 'cardinal - priest of s cecilia', '1261 , december 17', 'urban iv'], ['guillaume de bray', 'french', 'cardinal - priest of s marco', '1262 , may 22', 'urban iv'], ['gerardo bianchi', 'parma', 'cardinal - priest of ss xii apostoli', '1278 , march 12', 'nicholas iii'], ['girolamo masci , ofm', 'lisciano', 'cardinal - priest of s pudenziana', '1278 , march 12', 'nicholas iii'], ['giacomo savelli', 'rome', 'cardinal - deacon of s maria in cosmedin', '1261 , december 17', 'urban iv'], ['goffredo da alatri', 'alatri', 'cardinal - deacon of s giorgio in velabro', '1261 , december 17', 'urban iv'], ['matteo orsini', 'rome', 'cardinal - deacon of s maria in portico', '1262 , may 22', 'urban iv'], ['giordano orsini', 'rome', 'cardinal - deacon of s eustachio', '1278 , march 12', 'nicholas iii'], ['giacomo colonna', 'rome', 'cardinal - deacon of s maria in via lata', '1278 , march 12', 'nicholas iii']] |
1959 vfl season | https://en.wikipedia.org/wiki/1959_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775038-17.html.csv | aggregation | the average of the home team scores for the 1959 vfl season was 12.07 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '12.07', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'home team score'], 'result': '12.07', 'ind': 0, 'tostr': 'avg { all_rows ; home team score }'}, '12.07'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; home team score } ; 12.07 } = true', 'tointer': 'the average of the home team score record of all rows is 12.07 .'} | round_eq { avg { all_rows ; home team score } ; 12.07 } = true | the average of the home team score record of all rows is 12.07 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'home team score_4': 4, '12.07_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'home team score_4': 'home team score', '12.07_5': '12.07'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'home team score_4': [0], '12.07_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '6.6 ( 42 )', 'south melbourne', '19.20 ( 134 )', 'arden street oval', '12500', '22 august 1959'], ['essendon', '11.8 ( 74 )', 'fitzroy', '7.12 ( 54 )', 'windy hill', '30000', '22 august 1959'], ['carlton', '13.20 ( 98 )', 'hawthorn', '14.12 ( 96 )', 'princes park', '18720', '22 august 1959'], ['st kilda', '18.15 ( 123 )', 'richmond', '13.19 ( 97 )', 'junction oval', '14500', '22 august 1959'], ['melbourne', '17.18 ( 120 )', 'geelong', '9.12 ( 66 )', 'mcg', '21646', '22 august 1959'], ['footscray', '5.5 ( 35 )', 'collingwood', '8.17 ( 65 )', 'western oval', '33960', '22 august 1959']] |
art competitions at the 1928 summer olympics | https://en.wikipedia.org/wiki/Art_competitions_at_the_1928_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16574447-6.html.csv | superlative | in art competitions at the 1928 summer olympics , the highest number of gold medals was won by the netherlands . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'gold'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gold }'}, 'nation'], 'result': 'netherlands ( ned )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gold } ; nation }'}, 'netherlands ( ned )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gold } ; nation } ; netherlands ( ned ) } = true', 'tointer': 'select the row whose gold record of all rows is maximum . the nation record of this row is netherlands ( ned ) .'} | eq { hop { argmax { all_rows ; gold } ; nation } ; netherlands ( ned ) } = true | select the row whose gold record of all rows is maximum . the nation record of this row is netherlands ( ned ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'nation_6': 6, 'netherlands (ned)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'nation_6': 'nation', 'netherlands (ned)_7': 'netherlands ( ned )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'nation_6': [1], 'netherlands (ned)_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'netherlands ( ned )', '2', '1', '1', '4'], ['2', 'germany ( ger )', '1', '2', '5', '8'], ['3', 'france ( fra )', '1', '2', '1', '4'], ['4', 'great britain ( gbr )', '1', '1', '0', '2'], ['5', 'poland ( pol )', '1', '0', '1', '2'], ['6', 'austria ( aut )', '1', '0', '0', '1'], ['6', 'hungary ( hun )', '1', '0', '0', '1'], ['6', 'luxembourg ( lux )', '1', '0', '0', '1'], ['9', 'switzerland ( sui )', '0', '2', '0', '2'], ['10', 'denmark ( den )', '0', '1', '2', '3'], ['11', 'italy ( ita )', '0', '1', '0', '1']] |
2010 - 11 uae pro - league | https://en.wikipedia.org/wiki/2010%E2%80%9311_UAE_Pro-League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27631756-2.html.csv | majority | most of the teams in the 2010 - 11 uae pro - league had a kitmaker . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': 'n / a', 'subset': None} | {'func': 'most_str_not_eq', 'args': ['all_rows', 'kitmaker', 'n / a'], 'result': True, 'ind': 0, 'tointer': 'for the kitmaker records of all rows , most of them do not match to n / a .', 'tostr': 'most_not_eq { all_rows ; kitmaker ; n / a } = true'} | most_not_eq { all_rows ; kitmaker ; n / a } = true | for the kitmaker records of all rows , most of them do not match to n / a . | 1 | 1 | {'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'kitmaker_3': 3, 'n / a_4': 4} | {'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'kitmaker_3': 'kitmaker', 'n / a_4': 'n / a'} | {'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'kitmaker_3': [0], 'n / a_4': [0]} | ['team', 'chairman', 'head coach', 'captain', 'kitmaker', 'shirt sponsor'] | [['al ahli', 'abdullah saeed al naboodah', 'abdul hamid al mistaki', 'fabio cannavaro', 'adidas', 'toshiba'], ['al jazira', 'mansour bin zayed al nahyan', 'abel braga', 'ibrahim diaky', 'adidas', 'ipic'], ['al wahda', 'sheikh saeed bin zayed al nahyan', 'josef hickersberger', 'bashir saeed', 'nike', 'emal'], ['al ain', 'hazza bin zayed al nahyan', 'alexandre gallo', 'ali al wehaibi', 'macron', 'first gulf bank'], ['al sharjah', 'abdullah bin mohammed al thani', 'abdul majid', 'abdullah suhail', 'n / a', 'saif - zone'], ['al nasr', 'maktoum bin hasher bin maktoum al maktoum', 'walter zenga', 'abdallah mousa', 'erreà', 'emirates nbd'], ['ittihad kalba', 'saeed bin saqr al qasimi', 'jorvan vieira', 'gregory dufrennes', 'adidas', 'gillett group'], ['dubai', 'sheikh ahmed bin rashed al maktoum', 'junior dos santos', 'ali hassan', 'umbro', 'n / a'], ['bani yas', 'saif bin zayed al nahyan', 'mahdi ali', 'fawzi bashir', 'erreà', 'secure project management'], ['al wasl', 'sheikh ahmed bin rashed al maktoum', 'khalifa mobarak', 'khalid darwish', 'nike', 'saif belhasa group of companies'], ['al shabab', 'hh sh saeed bin maktoum al maktoum', 'paulo bonamigo', 'adeel abdullah', 'erreà', 'emaratech']] |
fittipaldi automotive | https://en.wikipedia.org/wiki/Fittipaldi_Automotive | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1262596-2.html.csv | superlative | emerson fittipaldi was the driver that had the highest position result for fittipaldi automotive . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'result'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; result }'}, 'driver'], 'result': 'emerson fittipaldi', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; result } ; driver }'}, 'emerson fittipaldi'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; result } ; driver } ; emerson fittipaldi } = true', 'tointer': 'select the row whose result record of all rows is minimum . the driver record of this row is emerson fittipaldi .'} | eq { hop { argmin { all_rows ; result } ; driver } ; emerson fittipaldi } = true | select the row whose result record of all rows is minimum . the driver record of this row is emerson fittipaldi . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'result_5': 5, 'driver_6': 6, 'emerson fittipaldi_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'result_5': 'result', 'driver_6': 'driver', 'emerson fittipaldi_7': 'emerson fittipaldi'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'result_5': [0], 'driver_6': [1], 'emerson fittipaldi_7': [2]} | ['year', 'event', 'venue', 'driver', 'result'] | [['1975', 'brdc international trophy', 'silverstone', 'wilson fittipaldi', 'ret'], ['1978', 'brdc international trophy', 'silverstone', 'emerson fittipaldi', '2'], ['1979', 'gran premio dino ferrari', 'imola', 'alex ribeiro', 'ret'], ['1980', 'spanish grand prix', 'jarama', 'emerson fittipaldi', '5'], ['1980', 'spanish grand prix', 'jarama', 'keke rosberg', 'ret'], ['1981', 'south african grand prix', 'kyalami', 'keke rosberg', '4'], ['1981', 'south african grand prix', 'kyalami', 'chico serra', '9']] |
2010 - 11 fc basel season | https://en.wikipedia.org/wiki/2010%E2%80%9311_FC_Basel_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28068645-8.html.csv | ordinal | in the 2010-11 fc basel season , when the position is f2 , the 2nd highest number is for fwayo tembo . | {'scope': 'subset', 'row': '7', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'fw'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'fw'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; fw }', 'tointer': 'select the rows whose position record fuzzily matches to fw .'}, 'number', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; position ; fw } ; number ; 2 }'}, 'player'], 'result': 'fwayo tembo', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; position ; fw } ; number ; 2 } ; player }'}, 'fwayo tembo'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; position ; fw } ; number ; 2 } ; player } ; fwayo tembo } = true', 'tointer': 'select the rows whose position record fuzzily matches to fw . select the row whose number record of these rows is 2nd maximum . the player record of this row is fwayo tembo .'} | eq { hop { nth_argmax { filter_eq { all_rows ; position ; fw } ; number ; 2 } ; player } ; fwayo tembo } = true | select the rows whose position record fuzzily matches to fw . select the row whose number record of these rows is 2nd maximum . the player record of this row is fwayo tembo . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'position_6': 6, 'fw_7': 7, 'number_8': 8, '2_9': 9, 'player_10': 10, 'fwayo tembo_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'position_6': 'position', 'fw_7': 'fw', 'number_8': 'number', '2_9': '2', 'player_10': 'player', 'fwayo tembo_11': 'fwayo tembo'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'position_6': [0], 'fw_7': [0], 'number_8': [1], '2_9': [1], 'player_10': [2], 'fwayo tembo_11': [3]} | ['position', 'number', 'player', 'super league', 'champions league', 'swiss cup', 'total'] | [['mf', '14', 'valentin stocker', '3', '0', '0', '3'], ['fw', '13', 'alexander frei', '2', '1', '0', '3'], ['df', '22', 'samuel inkoom', '2', '0', '0', '2'], ['df', '20', 'behrang safari', '1', '1', '0', '2'], ['mf', '8', 'benjamin huggel', '0', '2', '0', '2'], ['mf', '17', 'xherdan shaqiri', '0', '2', '0', '2'], ['fw', '30', 'fwayo tembo', '1', '0', '0', '1'], ['fw', '31', 'jacques zoua', '0', '1', '0', '1']] |
supernatural ( season 4 ) | https://en.wikipedia.org/wiki/Supernatural_%28season_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19396259-1.html.csv | majority | most of the episodes in the fourth season of supernatural originally aired in 2009 . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '2009', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'original air date', '2009'], 'result': True, 'ind': 0, 'tointer': 'for the original air date records of all rows , most of them fuzzily match to 2009 .', 'tostr': 'most_eq { all_rows ; original air date ; 2009 } = true'} | most_eq { all_rows ; original air date ; 2009 } = true | for the original air date records of all rows , most of them fuzzily match to 2009 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'original air date_3': 3, '2009_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'original air date_3': 'original air date', '2009_4': '2009'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'original air date_3': [0], '2009_4': [0]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['61', '1', 'lazarus rising', 'kim manners', 'eric kripke', 'september 18 , 2008', '3t7501', '3.96'], ['63', '3', 'in the beginning', 'steve boyum', 'jeremy carver', 'october 2 , 2008', '3t7504', '3.51'], ['64', '4', 'metamorphosis', 'kim manners', 'cathryn humphris', 'october 9 , 2008', '3t7505', '3.15'], ['65', '5', 'monster movie', 'robert singer', 'ben edlund', 'october 16 , 2008', '3t7503', '3.06'], ['66', '6', 'yellow fever', 'phil sgriccia', 'andrew dabb & daniel loflin', 'october 23 , 2008', '3t7506', '3.25'], ['67', '7', "it 's the great pumpkin , sam winchester", 'charles beeson', 'julie siege', 'october 30 , 2008', '3t7507', '3.55'], ['69', '9', 'i know what you did last summer', 'charles beeson', 'sera gamble', 'november 13 , 2008', '3t7509', '2.94'], ['70', '10', 'heaven and hell', 'j miller tobin', 'story by : trevor sands teleplay by : eric kripke', 'november 20 , 2008', '3t7510', '3.34'], ['71', '11', 'family remains', 'phil sgriccia', 'jeremy carver', 'january 15 , 2009', '3t7511', '2.98'], ['72', '12', 'criss angel is a douchebag', 'robert singer', 'julie siege', 'january 22 , 2009', '3t7512', '3.06'], ['73', '13', 'after school special', 'adam kane', 'andrew dabb & daniel loflin', 'january 29 , 2009', '3t7513', '3.56'], ['74', '14', 'sex and violence', 'charles beeson', 'cathryn humphris', 'february 5 , 2009', '3t7514', '3.37'], ['75', '15', 'death takes a holiday', 'steve boyum', 'jeremy carver', 'march 12 , 2009', '3t7515', '2.84'], ['76', '16', 'on the head of a pin', 'mike rohl', 'ben edlund', 'march 19 , 2009', '3t7516', '3.37'], ['77', '17', "it 's a terrible life", 'james l conway', 'sera gamble', 'march 26 , 2009', '3t7517', '3.13'], ['79', '19', 'jump the shark', 'phil sgriccia', 'andrew dabb & daniel loflin', 'april 23 , 2009', '3t7519', '2.70'], ['80', '20', 'the rapture', 'charles beeson', 'jeremy carver', 'april 30 , 2009', '3t7520', '2.95'], ['81', '21', 'when the levee breaks', 'robert singer', 'sera gamble', 'may 7 , 2009', '3t7521', '2.79']] |
1950 masters tournament | https://en.wikipedia.org/wiki/1950_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13059194-1.html.csv | superlative | in 1950 masters tournament the player with the most money was jimmy demaret with 2400 in money . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'money'], 'result': '2400', 'ind': 0, 'tostr': 'max { all_rows ; money }', 'tointer': 'the maximum money record of all rows is 2400 .'}, '2400'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; money } ; 2400 }', 'tointer': 'the maximum money record of all rows is 2400 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'money'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; money }'}, 'player'], 'result': 'jimmy demaret', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; money } ; player }'}, 'jimmy demaret'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; money } ; player } ; jimmy demaret }', 'tointer': 'the player record of the row with superlative money record is jimmy demaret .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; money } ; 2400 } ; eq { hop { argmax { all_rows ; money } ; player } ; jimmy demaret } } = true', 'tointer': 'the maximum money record of all rows is 2400 . the player record of the row with superlative money record is jimmy demaret .'} | and { eq { max { all_rows ; money } ; 2400 } ; eq { hop { argmax { all_rows ; money } ; player } ; jimmy demaret } } = true | the maximum money record of all rows is 2400 . the player record of the row with superlative money record is jimmy demaret . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'money_8': 8, '2400_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'money_11': 11, 'player_12': 12, 'jimmy demaret_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'money_8': 'money', '2400_9': '2400', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'money_11': 'money', 'player_12': 'player', 'jimmy demaret_13': 'jimmy demaret'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'money_8': [0], '2400_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'money_11': [2], 'player_12': [3], 'jimmy demaret_13': [4]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'jimmy demaret', 'united states', '70 + 72 + 72 + 69 = 283', '- 5', '2400'], ['2', 'jim ferrier', 'australia', '70 + 67 + 73 + 75 = 285', '- 3', '1500'], ['3', 'sam snead', 'united states', '71 + 74 + 70 + 72 = 287', '- 1', '1020'], ['t4', 'ben hogan', 'united states', '73 + 68 + 71 + 76 = 288', 'e', '725'], ['t4', 'byron nelson', 'united states', '75 + 70 + 69 + 74 = 288', 'e', '725'], ['6', 'lloyd mangrum', 'united states', '76 + 74 + 73 + 68 = 291', '+ 3', '480'], ['t7', 'clayton heafner', 'united states', '74 + 77 + 69 + 72 = 292', '+ 4', '405'], ['t7', 'cary middlecoff', 'united states', '75 + 76 + 68 + 73 = 292', '+ 4', '405'], ['9', 'lawson little', 'united states', '70 + 73 + 75 + 75 = 293', '+ 5', '360'], ['t10', 'fred haas', 'united states', '74 + 76 + 73 + 71 = 294', '+ 6', '333'], ['t10', 'gene sarazen', 'united states', '80 + 70 + 72 + 72 = 294', '+ 6', '333']] |
1964 vfl season | https://en.wikipedia.org/wiki/1964_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10784349-18.html.csv | superlative | the largest crowd size was for the game at the junction oval . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'junction oval', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'junction oval'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; junction oval } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is junction oval .'} | eq { hop { argmax { all_rows ; crowd } ; venue } ; junction oval } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is junction oval . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'junction oval_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'junction oval_7': 'junction oval'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'junction oval_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '12.6 ( 78 )', 'melbourne', '4.14 ( 38 )', 'western oval', '20555', '22 august 1964'], ['essendon', '28.16 ( 184 )', 'south melbourne', '2.7 ( 19 )', 'windy hill', '16800', '22 august 1964'], ['richmond', '9.18 ( 72 )', 'hawthorn', '16.19 ( 115 )', 'punt road oval', '15500', '22 august 1964'], ['st kilda', '12.18 ( 90 )', 'geelong', '11.12 ( 78 )', 'junction oval', '27100', '22 august 1964'], ['north melbourne', '8.13 ( 61 )', 'collingwood', '14.8 ( 92 )', 'arden street oval', '21895', '22 august 1964'], ['fitzroy', '7.12 ( 54 )', 'carlton', '19.20 ( 134 )', 'brunswick street oval', '14151', '22 august 1964']] |
athletics at the 1978 commonwealth games | https://en.wikipedia.org/wiki/Athletics_at_the_1978_Commonwealth_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10215649-3.html.csv | count | at the 1978 commonwealth games , among the athletes that did n't win any gold medals , 2 of them won 2 silver medals each . | {'scope': 'subset', 'criterion': 'equal', 'value': '2', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': '0'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; gold ; 0 }', 'tointer': 'select the rows whose gold record is equal to 0 .'}, 'silver', '2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 2 .', 'tostr': 'filter_eq { filter_eq { all_rows ; gold ; 0 } ; silver ; 2 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; gold ; 0 } ; silver ; 2 } }', 'tointer': 'select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 2 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; gold ; 0 } ; silver ; 2 } } ; 2 } = true', 'tointer': 'select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 2 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; gold ; 0 } ; silver ; 2 } } ; 2 } = true | select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 2 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'gold_6': 6, '0_7': 7, 'silver_8': 8, '2_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'gold_6': 'gold', '0_7': '0', 'silver_8': 'silver', '2_9': '2', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'gold_6': [0], '0_7': [0], 'silver_8': [1], '2_9': [1], '2_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'england', '16', '5', '12', '33'], ['2', 'australia', '7', '10', '7', '25'], ['3', 'canada', '6', '8', '10', '24'], ['4', 'kenya', '5', '4', '2', '11'], ['5', 'scotland', '2', '1', '3', '6'], ['6', 'jamaica', '1', '2', '2', '5'], ['7', 'tanzania', '1', '1', '0', '2'], ['8', 'wales', '1', '0', '0', '1'], ['9', 'trinidad and tobago', '0', '2', '1', '3'], ['10', 'new zealand', '0', '2', '0', '2'], ['11', 'guyana', '0', '1', '1', '2'], ['12', 'bahamas', '0', '1', '0', '1'], ['13', 'india', '0', '0', '1', '1'], ['total', 'total', '38', '38', '39', '115']] |
1984 seattle seahawks season | https://en.wikipedia.org/wiki/1984_Seattle_Seahawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13258851-2.html.csv | superlative | the game played on week 6 of the 1984 seattle seahawks season drew the highest attendance . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'week'], 'result': '6', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; week }'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; week } ; 6 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the week record of this row is 6 .'} | eq { hop { argmax { all_rows ; attendance } ; week } ; 6 } = true | select the row whose attendance record of all rows is maximum . the week record of this row is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'week_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'week_6': 'week', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'week_6': [1], '6_7': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 3 , 1984', 'cleveland browns', 'w 33 - 0', 'kingdome', '1 - 0', '59540'], ['2', 'september 9 , 1984', 'san diego chargers', 'w 31 - 17', 'kingdome', '2 - 0', '61314'], ['3', 'september 16 , 1984', 'new england patriots', 'l 23 - 38', 'sullivan stadium', '2 - 1', '43140'], ['4', 'september 23 , 1984', 'chicago bears', 'w 38 - 9', 'kingdome', '3 - 1', '61520'], ['5', 'september 30 , 1984', 'minnesota vikings', 'w 20 - 12', 'hubert h humphrey metrodome', '4 - 1', '57171'], ['6', 'october 7 , 1984', 'los angeles raiders', 'l 14 - 28', 'los angeles memorial coliseum', '4 - 2', '77904'], ['7', 'october 14 , 1984', 'buffalo bills', 'w 31 - 28', 'kingdome', '5 - 2', '59034'], ['8', 'october 21 , 1984', 'green bay packers', 'w 30 - 24', 'lambeau field', '6 - 2', '52286'], ['9', 'october 29 , 1984', 'san diego chargers', 'w 24 - 0', 'jack murphy stadium', '7 - 2', '53974'], ['10', 'november 4 , 1984', 'kansas city chiefs', 'w 45 - 0', 'kingdome', '8 - 2', '61396'], ['11', 'november 12 , 1984', 'los angeles raiders', 'w 17 - 14', 'kingdome', '9 - 2', '64001'], ['12', 'november 18 , 1984', 'cincinnati bengals', 'w 26 - 6', 'riverfront stadium', '10 - 2', '50280'], ['13', 'november 25 , 1984', 'denver broncos', 'w 27 - 24', 'mile high stadium', '11 - 2', '74922'], ['14', 'december 2 , 1984', 'detroit lions', 'w 38 - 17', 'kingdome', '12 - 2', '62441'], ['15', 'december 9 , 1984', 'kansas city chiefs', 'l 7 - 34', 'arrowhead stadium', '12 - 3', '34855']] |
yugoslavia national football team results | https://en.wikipedia.org/wiki/Yugoslavia_national_football_team_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14305653-58.html.csv | comparative | the yugoslavia national football team scored more points against poland than against italy . | {'row_1': '3', 'row_2': '7', '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', 'opponent', 'poland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to poland .', 'tostr': 'filter_eq { all_rows ; opponent ; poland }'}, 'results'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; poland } ; results }', 'tointer': 'select the rows whose opponent record fuzzily matches to poland . take the results record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'italy'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; opponent ; italy }'}, 'results'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; italy } ; results }', 'tointer': 'select the rows whose opponent record fuzzily matches to italy . take the results record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; poland } ; results } ; hop { filter_eq { all_rows ; opponent ; italy } ; results } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to poland . take the results record of this row . select the rows whose opponent record fuzzily matches to italy . take the results record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; poland } ; results } ; hop { filter_eq { all_rows ; opponent ; italy } ; results } } = true | select the rows whose opponent record fuzzily matches to poland . take the results record of this row . select the rows whose opponent record fuzzily matches to italy . take the results 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, 'opponent_7': 7, 'poland_8': 8, 'results_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'italy_12': 12, 'results_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', 'opponent_7': 'opponent', 'poland_8': 'poland', 'results_9': 'results', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'italy_12': 'italy', 'results_13': 'results'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'poland_8': [0], 'results_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'italy_12': [1], 'results_13': [3]} | ['date', 'city', 'opponent', 'results', 'type of game'] | [['march 22', 'sarajevo', 'uruguay', '2:1', 'friendly'], ['march 30', 'belgrade', 'romania', '2:0', 'balkan cup'], ['april 26', 'borovo', 'poland', '2:1', 'friendly'], ['august 27', 'bucharest , romania', 'romania', '1:4', 'balkan cup'], ['september 10', 'luxembourg', 'luxembourg', '5:0', '1982 wcq'], ['september 27', 'ljubljana', 'denmark', '2:1', '1982 wcq'], ['november 15', 'torino , italy', 'italy', '0:2', '1982 wcq']] |
2005 texas rangers season | https://en.wikipedia.org/wiki/2005_Texas_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12125069-2.html.csv | majority | most of the games were played in the location of arlington . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'arlington', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'arlington'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to arlington .', 'tostr': 'most_eq { all_rows ; location ; arlington } = true'} | most_eq { all_rows ; location ; arlington } = true | for the location records of all rows , most of them fuzzily match to arlington . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'arlington_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'arlington_4': 'arlington'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'arlington_4': [0]} | ['date', 'winning team', 'score', 'winning pitcher', 'losing pitcher', 'attendance', 'location'] | [['may 20', 'texas', '7 - 3', 'kenny rogers', 'brandon backe', '38109', 'arlington'], ['may 21', 'texas', '18 - 3', 'chris young', 'ezequiel astacio', '35781', 'arlington'], ['may 22', 'texas', '2 - 0', 'chan ho park', 'roy oswalt', '40583', 'arlington'], ['june 24', 'houston', '5 - 2', 'roy oswalt', 'ricardo rodríguez', '36199', 'houston'], ['june 25', 'texas', '6 - 5', 'chris young', 'brandon backe', '41868', 'houston']] |
1996 in film | https://en.wikipedia.org/wiki/1996_in_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-169568-1.html.csv | unique | of the top 20 films released in 1996 , tristar pictures released only one . | {'scope': 'all', 'row': '9', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'tristar pictures', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'studio', 'tristar pictures'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose studio record fuzzily matches to tristar pictures .', 'tostr': 'filter_eq { all_rows ; studio ; tristar pictures }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; studio ; tristar pictures } } = true', 'tointer': 'select the rows whose studio record fuzzily matches to tristar pictures . there is only one such row in the table .'} | only { filter_eq { all_rows ; studio ; tristar pictures } } = true | select the rows whose studio record fuzzily matches to tristar pictures . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'studio_4': 4, 'tristar pictures_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'studio_4': 'studio', 'tristar pictures_5': 'tristar pictures'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'studio_4': [0], 'tristar pictures_5': [0]} | ['rank', 'title', 'studio', 'director', 'worldwide gross'] | [['1', 'independence day', '20th century fox', 'roland emmerich', '817400891'], ['2', 'twister', 'warner bros / universal studios', 'jan de bont', '494471524'], ['3', 'mission : impossible', 'paramount pictures', 'brian de palma', '457696359'], ['4', 'the rock', 'hollywood pictures', 'michael bay', '335062621'], ['5', 'the hunchback of notre dame', 'walt disney pictures', 'kirk wise , gary trousdale', '325338851'], ['6', '101 dalmatians', 'walt disney pictures / great oaks', 'stephen herek', '320689294'], ['7', 'ransom', 'touchstone pictures / image entertainment', 'ron howard', '309492681'], ['8', 'the nutty professor', 'universal pictures', 'tom shadyac', '273961019'], ['9', 'jerry maguire', 'tristar pictures', 'cameron crowe', '273552592'], ['10', 'eraser', 'warner bros', 'chuck russell', '242295562'], ['11', 'the english patient', 'miramax films', 'anthony minghella', '231976425'], ['12', 'space jam', 'warner bros', 'joe pytka', '230418342'], ['13', 'the birdcage', 'united artists', 'mike nichols', '185260553'], ['14', 'the first wives club', 'paramount pictures', 'hugh wilson', '181490000'], ['15', 'scream', 'dimension films', 'wes craven', '173046663'], ['16', 'sleepers', 'warner bros', 'barry levinson', '165615285'], ['17', 'daylight', 'universal pictures', 'rob cohen', '159212469'], ['18', 'a time to kill', 'warner bros', 'joel schumacher', '152266007'], ['19', 'phenomenon', 'buena vista', 'jon turteltaub', '152036382'], ['20', 'broken arrow', '20th century fox', 'john woo', '150270147']] |
california 's great america | https://en.wikipedia.org/wiki/California%27s_Great_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1680162-1.html.csv | aggregation | the average rating that was achieved by all the rides was 4 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'rating'], 'result': '4', 'ind': 0, 'tostr': 'avg { all_rows ; rating }'}, '4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; rating } ; 4 } = true', 'tointer': 'the average of the rating record of all rows is 4 .'} | round_eq { avg { all_rows ; rating } ; 4 } = true | the average of the rating record of all rows is 4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'rating_4': 4, '4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'rating_4': 'rating', '4_5': '4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'rating_4': [0], '4_5': [1]} | ['ride', 'year opened', 'ride manufacturer and type', 'minimum height', 'rating'] | [['the demon', '1980', 'arrow dynamics', '48', '5'], ['flight deck', '1993', 'bolliger & mabillard inverted roller coaster', '54', '5'], ['gold striker', '2013', 'great coasters international wooden roller coaster', '48', '4'], ['grizzly', '1986', 'wooden roller coaster', '48', '4'], ['psycho mouse', '2001', 'arrow dynamics wild mouse roller coaster', '44', '4'], ['taxi jam', '1999', 'e & f miller industries kiddie coaster', '36', '2'], ['vortex', '1991', 'bolliger & mabillard stand - up roller coaster', '54', '5'], ['woodstock express', '1987', 'intamin family roller coaster', '40', '3']] |
united states house of representatives elections , 1990 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1990 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341568-44.html.csv | majority | the democrats won the majority of the elections listed . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic .', 'tostr': 'most_eq { all_rows ; party ; democratic } = true'} | most_eq { all_rows ; party ; democratic } = true | for the party records of all rows , most of them fuzzily match to democratic . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'elected', 'status', 'opponent'] | [['texas1', 'jim chapman', 'democratic', '1985', 're - elected', 'jim chapman ( d ) 61.0 % hamp hodges ( r ) 39.0 %'], ['texas2', 'charlie wilson', 'democratic', '1972', 're - elected', 'charlie wilson ( d ) 55.6 % donna peterson ( r ) 44.4 %'], ['texas3', 'steve bartlett', 'republican', '1982', 're - elected', 'steve bartlett ( r ) 99.6 % noel kopala ( i - wi ) 0.4 %'], ['texas4', 'ralph hall', 'democratic', '1980', 're - elected', 'ralph hall ( d ) 99.6 % tim j mccord ( i - wi ) 0.4 %'], ['texas7', 'bill archer', 'republican', '1970', 're - elected', 'bill archer ( r ) unopposed'], ['texas8', 'jack fields', 'republican', '1980', 're - elected', 'jack fields ( r ) unopposed'], ['texas9', 'jack brooks', 'democratic', '1952', 're - elected', 'jack brooks ( d ) 57.7 % maury meyers ( r ) 42.3 %'], ['texas11', 'marvin leath', 'democratic', '1978', 'retired democratic hold', 'chet edwards ( d ) 53.5 % hugh shine ( r ) 46.5 %'], ['texas12', 'pete geren', 'democratic', '1989', 're - elected', 'pete geren ( d ) 71.3 % mike mcginn ( r ) 28.7 %'], ['texas14', 'greg laughlin', 'democratic', '1988', 're - elected', 'greg laughlin ( d ) 54.3 % joe dial ( r ) 45.7 %'], ['texas15', 'kika de la garza', 'democratic', '1964', 're - elected', 'kika de la garza ( d ) unopposed'], ['texas17', 'charles stenholm', 'democratic', '1978', 're - elected', 'charles stenholm ( d ) unopposed'], ['texas18', 'craig anthony washington', 'democratic', '1989', 're - elected', 'craig anthony washington ( d ) 99.6 %'], ['texas19', 'larry combest', 'republican', '1984', 're - elected', 'larry combest ( r ) unopposed'], ['texas20', 'henry b gonzalez', 'democratic', '1960', 're - elected', 'henry b gonzalez ( d ) unopposed'], ['texas22', 'tom delay', 'republican', '1984', 're - elected', 'tom delay ( r ) 71.2 % bruce director ( d ) 28.8 %'], ['texas24', 'martin frost', 'democratic', '1978', 're - elected', 'martin frost ( d ) unopposed'], ['texas25', 'michael a andrews', 'democratic', '1982', 're - elected', 'michael a andrews ( d ) unopposed'], ['texas26', 'dick armey', 'republican', '1984', 're - elected', 'dick armey ( r ) 70.4 % john wayne caton ( d ) 29.6 %']] |
peaches & herb | https://en.wikipedia.org/wiki/Peaches_%26_Herb | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1862179-1.html.csv | count | a total of two releases by the duo peaches & herb were in the year 1979 . | {'scope': 'all', 'criterion': 'equal', 'value': '1979', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year of release', '1979'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year of release record is equal to 1979 .', 'tostr': 'filter_eq { all_rows ; year of release ; 1979 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year of release ; 1979 } }', 'tointer': 'select the rows whose year of release record is equal to 1979 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year of release ; 1979 } } ; 2 } = true', 'tointer': 'select the rows whose year of release record is equal to 1979 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; year of release ; 1979 } } ; 2 } = true | select the rows whose year of release record is equal to 1979 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year of release_5': 5, '1979_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year of release_5': 'year of release', '1979_6': '1979', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year of release_5': [0], '1979_6': [0], '2_7': [2]} | ['title', 'label', 'year of release', 'country of release', 'peaches :'] | [['for your love', 'date', '1967', 'usa', 'francine barker'], ["let 's fall in love", 'date', '1967', 'usa', 'francine barker'], ['peaches & herb', 'mca', '1977', 'usa', 'linda greene'], ['2 hot', 'mvp / polydor', '1978', 'usa', 'linda greene'], ['twice the fire', 'mvp / polydor', '1979', 'usa', 'linda greene'], ['demasiado candente', 'mvp / polydor', '1979', 'argentina', 'linda greene'], ['worth the wait', 'mvp / polydor', '1980', 'usa', 'linda greene'], ["sayin ' something", 'mvp / polydor', '1981', 'usa', 'linda greene'], ['remember', 'the entertainment co / columbia', '1983', 'usa', 'linda greene'], ['colors of love', 'imagen', '2009', 'usa', 'meritxell negre']] |
list of state leaders in the 20th century bc | https://en.wikipedia.org/wiki/List_of_state_leaders_in_the_20th_century_BC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17606888-1.html.csv | count | 3 of the state leaders in the 20th century bc were in the 12th dynasty . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'twelfth', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'royal house', 'twelfth'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose royal house record fuzzily matches to twelfth .', 'tostr': 'filter_eq { all_rows ; royal house ; twelfth }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; royal house ; twelfth } }', 'tointer': 'select the rows whose royal house record fuzzily matches to twelfth . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; royal house ; twelfth } } ; 3 } = true', 'tointer': 'select the rows whose royal house record fuzzily matches to twelfth . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; royal house ; twelfth } } ; 3 } = true | select the rows whose royal house record fuzzily matches to twelfth . 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, 'royal house_5': 5, 'twelfth_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', 'royal house_5': 'royal house', 'twelfth_6': 'twelfth', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'royal house_5': [0], 'twelfth_6': [0], '3_7': [2]} | ['type', 'name', 'title', 'royal house', 'from'] | [['sovereign', 'mentuhotep ii', 'pharaoh', 'eleventh dynasty', '2010 bc'], ['sovereign', 'mentuhotep iv', 'pharaoh', 'eleventh dynasty', '1998 bc or 1997 bc'], ['sovereign', 'amenemhat i', 'pharaoh', 'twelfth dynasty', '1991 bc'], ['sovereign', 'senusret i', 'pharaoh', 'twelfth dynasty', '1971 bc'], ['sovereign', 'amenemhat ii', 'pharaoh', 'twelfth dynasty', '1929 bc']] |
anthony kim | https://en.wikipedia.org/wiki/Anthony_Kim | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11106562-3.html.csv | aggregation | the average number of times anthony kim was in the top-5 was .5 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'top - 5'], 'result': '.5', 'ind': 0, 'tostr': 'avg { all_rows ; top - 5 }'}, '.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; top - 5 } ; .5 } = true', 'tointer': 'the average of the top - 5 record of all rows is .5 .'} | round_eq { avg { all_rows ; top - 5 } ; .5 } = true | the average of the top - 5 record of all rows is .5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'top - 5_4': 4, '.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'top - 5_4': 'top - 5', '.5_5': '.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'top - 5_4': [0], '.5_5': [1]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '1', '2', '3', '2'], ['us open', '0', '0', '0', '2', '4', '4'], ['the open championship', '0', '1', '2', '2', '3', '2'], ['pga championship', '0', '0', '0', '0', '5', '3'], ['totals', '0', '2', '3', '6', '15', '11']] |
high - speed rail in europe | https://en.wikipedia.org/wiki/High-speed_rail_in_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14227171-10.html.csv | majority | most of the lines of the european speed lines are shorter than 100 km long . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '100 km', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'length', '100 km'], 'result': True, 'ind': 0, 'tointer': 'for the length records of all rows , most of them are less than 100 km .', 'tostr': 'most_less { all_rows ; length ; 100 km } = true'} | most_less { all_rows ; length ; 100 km } = true | for the length records of all rows , most of them are less than 100 km . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'length_3': 3, '100 km_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'length_3': 'length', '100 km_4': '100 km'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'length_3': [0], '100 km_4': [0]} | ['line', 'speed', 'length', 'construction begun', 'expected start of revenue services'] | [['svilengrad - turkish border', '200 km / h', '19 km', '2010', '2012'], ['dimitrovgrad - svilengrad', '200 km / h', '70 km', '2012', '2013'], ['plovdiv - burgas', '200 km / h', '291 km', '2010', '2013'], ['sofia - plovdiv', '200 km / h', '156 km', '2010', '2015'], ['sofia - radomir', '200 km / h', '53 km', '2014', '2017'], ['sofia - dragoman', '200 km / h', '44 km', '2014', '2017'], ['vidin - sofia', '200 km / h', '222 km', 'unknown', '2020']] |
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 | majority | most of the people representing the 5th district in texas have been democrats . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democrat', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democrat'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democrat .', 'tostr': 'most_eq { all_rows ; party ; democrat } = true'} | most_eq { all_rows ; party ; democrat } = true | for the party records of all rows , most of them fuzzily match to democrat . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democrat_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democrat_4': 'democrat'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democrat_4': [0]} | ['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']] |
werner pfirter | https://en.wikipedia.org/wiki/Werner_Pfirter | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16431762-2.html.csv | aggregation | the average number of points for werner pfirter is 15.5 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '15.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '15.5', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '15.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 15.5 } = true', 'tointer': 'the average of the points record of all rows is 15.5 .'} | round_eq { avg { all_rows ; points } ; 15.5 } = true | the average of the points record of all rows is 15.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '15.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '15.5_5': '15.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '15.5_5': [1]} | ['year', 'class', 'team', 'points', 'wins'] | [['1970', '250cc', 'yamaha', '0', '0'], ['1970', '350cc', 'yamaha', '0', '0'], ['1971', '250cc', 'yamaha', '9', '0'], ['1971', '350cc', 'yamaha', '33', '0'], ['1972', '250cc', 'yamaha', '28', '0'], ['1972', '350cc', 'yamaha', '17', '0'], ['1973', '250cc', 'yamaha', '20', '0'], ['1973', '350cc', 'yamaha', '17', '0']] |
chennai super kings | https://en.wikipedia.org/wiki/Chennai_Super_Kings | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15829930-5.html.csv | superlative | for the chennai super kings , the highest number of wins when there were a total of 16 matches was in 2011 . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2,1', 'subset': {'col': '2', 'criterion': 'equal', 'value': '16'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'matches', '16'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; matches ; 16 }', 'tointer': 'select the rows whose matches record is equal to 16 .'}, 'wins'], 'result': '11', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; matches ; 16 } ; wins }', 'tointer': 'select the rows whose matches record is equal to 16 . the maximum wins record of these rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; matches ; 16 } ; wins } ; 11 }', 'tointer': 'select the rows whose matches record is equal to 16 . the maximum wins record of these rows is 11 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'matches', '16'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; matches ; 16 }', 'tointer': 'select the rows whose matches record is equal to 16 .'}, 'wins'], 'result': None, 'ind': 3, 'tostr': 'argmax { filter_eq { all_rows ; matches ; 16 } ; wins }'}, 'year'], 'result': '2011', 'ind': 4, 'tostr': 'hop { argmax { filter_eq { all_rows ; matches ; 16 } ; wins } ; year }'}, '2011'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; matches ; 16 } ; wins } ; year } ; 2011 }', 'tointer': 'the year record of the row with superlative wins record is 2011 .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { max { filter_eq { all_rows ; matches ; 16 } ; wins } ; 11 } ; eq { hop { argmax { filter_eq { all_rows ; matches ; 16 } ; wins } ; year } ; 2011 } } = true', 'tointer': 'select the rows whose matches record is equal to 16 . the maximum wins record of these rows is 11 . the year record of the row with superlative wins record is 2011 .'} | and { eq { max { filter_eq { all_rows ; matches ; 16 } ; wins } ; 11 } ; eq { hop { argmax { filter_eq { all_rows ; matches ; 16 } ; wins } ; year } ; 2011 } } = true | select the rows whose matches record is equal to 16 . the maximum wins record of these rows is 11 . the year record of the row with superlative wins record is 2011 . | 8 | 7 | {'and_6': 6, 'result_7': 7, 'eq_2': 2, 'max_1': 1, 'filter_eq_0': 0, 'all_rows_8': 8, 'matches_9': 9, '16_10': 10, 'wins_11': 11, '11_12': 12, 'eq_5': 5, 'num_hop_4': 4, 'argmax_3': 3, 'wins_13': 13, 'year_14': 14, '2011_15': 15} | {'and_6': 'and', 'result_7': 'true', 'eq_2': 'eq', 'max_1': 'max', 'filter_eq_0': 'filter_eq', 'all_rows_8': 'all_rows', 'matches_9': 'matches', '16_10': '16', 'wins_11': 'wins', '11_12': '11', 'eq_5': 'eq', 'num_hop_4': 'num_hop', 'argmax_3': 'argmax', 'wins_13': 'wins', 'year_14': 'year', '2011_15': '2011'} | {'and_6': [7], 'result_7': [], 'eq_2': [6], 'max_1': [2], 'filter_eq_0': [1, 3], 'all_rows_8': [0], 'matches_9': [0], '16_10': [0], 'wins_11': [1], '11_12': [2], 'eq_5': [6], 'num_hop_4': [5], 'argmax_3': [4], 'wins_13': [3], 'year_14': [4], '2011_15': [5]} | ['year', 'matches', 'wins', 'losses', 'no result', 'tied', 'success rate', 'position', 'summary'] | [['2008', '16', '9', '7', '0', '0', '56.25 %', '2nd', 'runners - up'], ['2009', '15', '8', '6', '1', '0', '53.33 %', '4th', 'semi - finalists'], ['2010', '16', '9', '7', '0', '0', '56.25 %', '1st', 'champions'], ['2011', '16', '11', '5', '0', '0', '68.75 %', '1st', 'champions'], ['2012', '19', '19', '11', '8', '0', '52.63 %', '2nd', 'runners - up'], ['2013', '18', '12', '6', '0', '0', '66.67 %', '2nd', 'runners - up']] |
2008 masters tournament | https://en.wikipedia.org/wiki/2008_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12531523-5.html.csv | superlative | in the 2008 master tournament the player with the highest rank was trevor immelman in place 1 . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'place'], 'result': '1', 'ind': 0, 'tostr': 'min { all_rows ; place }', 'tointer': 'the minimum place record of all rows is 1 .'}, '1'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; place } ; 1 }', 'tointer': 'the minimum place record of all rows is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'place'], 'result': None, 'ind': 2, 'tostr': 'argmin { all_rows ; place }'}, 'player'], 'result': 'trevor immelman', 'ind': 3, 'tostr': 'hop { argmin { all_rows ; place } ; player }'}, 'trevor immelman'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmin { all_rows ; place } ; player } ; trevor immelman }', 'tointer': 'the player record of the row with superlative place record is trevor immelman .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { min { all_rows ; place } ; 1 } ; eq { hop { argmin { all_rows ; place } ; player } ; trevor immelman } } = true', 'tointer': 'the minimum place record of all rows is 1 . the player record of the row with superlative place record is trevor immelman .'} | and { eq { min { all_rows ; place } ; 1 } ; eq { hop { argmin { all_rows ; place } ; player } ; trevor immelman } } = true | the minimum place record of all rows is 1 . the player record of the row with superlative place record is trevor immelman . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'min_0': 0, 'all_rows_7': 7, 'place_8': 8, '1_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmin_2': 2, 'all_rows_10': 10, 'place_11': 11, 'player_12': 12, 'trevor immelman_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'min_0': 'min', 'all_rows_7': 'all_rows', 'place_8': 'place', '1_9': '1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmin_2': 'argmin', 'all_rows_10': 'all_rows', 'place_11': 'place', 'player_12': 'player', 'trevor immelman_13': 'trevor immelman'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'min_0': [1], 'all_rows_7': [0], 'place_8': [0], '1_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmin_2': [3], 'all_rows_10': [2], 'place_11': [2], 'player_12': [3], 'trevor immelman_13': [4]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'trevor immelman', 'south africa', '68 + 68 + 69 = 205', '- 11'], ['2', 'brandt snedeker', 'united states', '69 + 68 + 70 = 207', '- 9'], ['3', 'steve flesch', 'united states', '72 + 67 + 69 = 208', '- 8'], ['4', 'paul casey', 'england', '71 + 69 + 69 = 209', '- 7'], ['5', 'tiger woods', 'united states', '72 + 71 + 68 = 211', '- 5'], ['6', 'stewart cink', 'united states', '72 + 69 + 71 = 212', '- 4'], ['t7', 'retief goosen', 'south africa', '71 + 71 + 72 = 214', '- 2'], ['t7', 'pádraig harrington', 'ireland', '74 + 71 + 69 = 214', '- 2'], ['t7', 'zach johnson', 'united states', '70 + 76 + 68 = 214', '- 2'], ['t7', 'robert karlsson', 'sweden', '70 + 73 + 71 = 214', '- 2'], ['t7', 'phil mickelson', 'united states', '71 + 68 + 75 = 214', '- 2'], ['t7', "sean o'hair", 'united states', '72 + 71 + 71 = 214', '- 2'], ['t7', 'ian poulter', 'england', '70 + 69 + 75 = 214', '- 2'], ['t7', 'andrés romero', 'argentina', '72 + 72 + 70 = 214', '- 2'], ['t7', 'boo weekley', 'united states', '72 + 74 + 68 = 214', '- 2']] |
2006 hamburg sea devils season | https://en.wikipedia.org/wiki/2006_Hamburg_Sea_Devils_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24989925-2.html.csv | superlative | the game that took place at commerzbank - arena had the highest attendance . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '7', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'game site'], 'result': 'commerzbank - arena', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; game site }'}, 'commerzbank - arena'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; game site } ; commerzbank - arena } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the game site record of this row is commerzbank - arena .'} | eq { hop { argmax { all_rows ; attendance } ; game site } ; commerzbank - arena } = true | select the row whose attendance record of all rows is maximum . the game site record of this row is commerzbank - arena . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'game site_6': 6, 'commerzbank - arena_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'game site_6': 'game site', 'commerzbank - arena_7': 'commerzbank - arena'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'game site_6': [1], 'commerzbank - arena_7': [2]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , march 18', '6:00 pm', 'cologne centurions', 'l 10 - 14', '0 - 1 - 0', 'aol arena', '15243'], ['2', 'saturday , march 25', '7:00 pm', 'frankfurt galaxy', 'l 14 - 31', '0 - 2 - 0', 'commerzbank - arena', '26713'], ['3', 'saturday , april 1', '6:00 pm', 'berlin thunder', 't 17 - 17 ot', '0 - 2 - 1', 'aol arena', '15837'], ['4', 'saturday , april 8', '7:00 pm', 'rhein fire', 'l 21 - 31', '0 - 3 - 1', 'ltu arena', '18224'], ['5', 'saturday , april 15', '6:00 pm', 'frankfurt galaxy', 'l 13 - 17', '0 - 4 - 1', 'aol arena', '12281'], ['6', 'sunday , april 23', '4:00 pm', 'cologne centurions', 'l 17 - 20', '0 - 5 - 1', 'rheinenergiestadion', '9238'], ['7', 'saturday , april 29', '6:00 pm', 'amsterdam admirals', 'l 17 - 18', '0 - 6 - 1', 'aol arena', '15224'], ['8', 'sunday , may 7', '4:00 pm', 'berlin thunder', 'w 38 - 14', '1 - 6 - 1', 'olympic stadium', '16762'], ['9', 'sunday , may 14', '4:00 pm', 'rhein fire', 'w 13 - 10', '2 - 6 - 1', 'aol arena', '16823']] |
1983 - 84 north west counties football league | https://en.wikipedia.org/wiki/1983%E2%80%9384_North_West_Counties_Football_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17718005-2.html.csv | ordinal | eastwood hanley has the second highest points in the1983 – 84 north west counties football league . | {'row': '2', 'col': '9', '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 1', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points 1 ; 2 }'}, 'team'], 'result': 'eastwood hanley', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points 1 ; 2 } ; team }'}, 'eastwood hanley'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points 1 ; 2 } ; team } ; eastwood hanley } = true', 'tointer': 'select the row whose points 1 record of all rows is 2nd maximum . the team record of this row is eastwood hanley .'} | eq { hop { nth_argmax { all_rows ; points 1 ; 2 } ; team } ; eastwood hanley } = true | select the row whose points 1 record of all rows is 2nd maximum . the team record of this row is eastwood hanley . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points 1_5': 5, '2_6': 6, 'team_7': 7, 'eastwood hanley_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 1_5': 'points 1', '2_6': '2', 'team_7': 'team', 'eastwood hanley_8': 'eastwood hanley'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points 1_5': [0], '2_6': [0], 'team_7': [1], 'eastwood hanley_8': [2]} | ['position', 'team', 'played', 'drawn', 'lost', 'goals for', 'goals against', 'goal difference', 'points 1'] | [['1', 'fleetwood town', '34', '8', '2', '73', '24', '+ 49', '56'], ['2', 'eastwood hanley', '34', '6', '7', '69', '35', '+ 34', '48'], ['3', 'irlam town', '34', '8', '7', '67', '41', '+ 26', '46'], ['4', 'warrington town', '34', '7', '9', '65', '45', '+ 20', '43'], ['5', 'droylsden', '34', '5', '10', '59', '42', '+ 17', '43'], ['6', 'colne dynamoes', '34', '9', '9', '55', '37', '+ 18', '41'], ['7', 'ellesmere port & neston', '34', '10', '12', '49', '38', '+ 11', '34'], ['8', 'chadderton', '34', '6', '14', '56', '46', '+ 10', '34'], ['9', 'atherton laburnum rovers', '34', '11', '12', '37', '41', '4', '33'], ['10', 'wren rovers', '34', '10', '13', '45', '47', '2', '33'], ['11', 'skelmersdale united', '34', '6', '15', '60', '63', '3', '32'], ['12', 'ford motors', '34', '9', '16', '38', '53', '15', '27'], ['13', 'prescot bi', '34', '9', '16', '50', '66', '16', '27'], ['14', 'lytham', '34', '3', '18', '56', '81', '25', '27 2'], ['15', 'rossendale united', '34', '6', '18', '53', '84', '31', '26'], ['16', 'great harwood town', '34', '12', '17', '36', '60', '24', '22'], ['17', 'salford', '34', '11', '18', '24', '60', '36', '21'], ['18', 'nantwich town', '34', '2', '24', '44', '73', '29', '18']] |
portugal in the eurovision song contest 2008 | https://en.wikipedia.org/wiki/Portugal_in_the_Eurovision_Song_Contest_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15739554-1.html.csv | ordinal | according to the portugal in the eurovision song contest 2008 , artist vnia fernandes took 1st place . | {'scope': 'all', 'row': '5', 'col': '6', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'place', '1'], 'result': '1', 'ind': 0, 'tostr': 'nth_min { all_rows ; place ; 1 }', 'tointer': 'the 1st minimum place record of all rows is 1 .'}, '1'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; place ; 1 } ; 1 }', 'tointer': 'the 1st minimum place record of all rows is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'place', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; place ; 1 }'}, 'artist'], 'result': 'vnia fernandes', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; place ; 1 } ; artist }'}, 'vnia fernandes'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; place ; 1 } ; artist } ; vnia fernandes }', 'tointer': 'the artist record of the row with 1st minimum place record is vnia fernandes .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; place ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; place ; 1 } ; artist } ; vnia fernandes } } = true', 'tointer': 'the 1st minimum place record of all rows is 1 . the artist record of the row with 1st minimum place record is vnia fernandes .'} | and { eq { nth_min { all_rows ; place ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; place ; 1 } ; artist } ; vnia fernandes } } = true | the 1st minimum place record of all rows is 1 . the artist record of the row with 1st minimum place record is vnia fernandes . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'place_8': 8, '1_9': 9, '1_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'place_12': 12, '1_13': 13, 'artist_14': 14, 'vnia fernandes_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'place_8': 'place', '1_9': '1', '1_10': '1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'place_12': 'place', '1_13': '1', 'artist_14': 'artist', 'vnia fernandes_15': 'vnia fernandes'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'place_8': [0], '1_9': [0], '1_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'place_12': [2], '1_13': [2], 'artist_14': [3], 'vnia fernandes_15': [4]} | ['draw', 'artist', 'song', 'producer', 'votes', 'place'] | [['1', 'marco rodridgues', 'em água e sal', 'elvis veiguinha', '5944', '3'], ['2', 'carluz belo', 'cavaleiro da manhã', 'carluz belo', '2049', '8'], ['3', 'big hit', 'por ti , portugal', 'fernando martins', '2934', '6'], ['4', 'lisboa não sejas francesa', 'porto de encontro', 'miguel majer , ricardo santos', '1974', '9'], ['5', 'vnia fernandes', 'senhora do mar', 'carlos coelho', '17650', '1'], ['6', 'vanessa', 'do outro lado da vida', 'nuno feist', '2622', '7'], ['7', 'ricardo soler', 'canção pop', 'renato júnior', '4736', '4'], ['8', 'alex smith', 'obrigatório ter', 'jan van dijck', '6928', '2'], ['9', 'tucha', 'o poder da mensagem', 'ménito ramos', '626', '10'], ['10', 'blá blà blá', 'magicantasticamente', 'gimba', '4616', '5']] |
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