topic
stringlengths 3
96
| wiki
stringlengths 33
127
| url
stringlengths 101
106
| action
stringclasses 7
values | sent
stringlengths 34
223
| annotation
stringlengths 74
227
| logic
stringlengths 207
5.45k
| logic_str
stringlengths 37
493
| interpret
stringlengths 43
471
| num_func
stringclasses 15
values | nid
stringclasses 13
values | g_ids
stringlengths 70
455
| g_ids_features
stringlengths 98
670
| g_adj
stringlengths 79
515
| table_header
stringlengths 40
458
| table_cont
large_stringlengths 135
4.41k
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
united states senate election in arizona , 2004 | https://en.wikipedia.org/wiki/United_States_Senate_election_in_Arizona%2C_2004 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19681738-1.html.csv | comparative | hancock received more votes in coconino county than in graham during the 2004 united states senate election in arizona . | {'row_1': '3', 'row_2': '5', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'coconino'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to coconino .', 'tostr': 'filter_eq { all_rows ; county ; coconino }'}, 'hancock'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; county ; coconino } ; hancock }', 'tointer': 'select the rows whose county record fuzzily matches to coconino . take the hancock record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'graham'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose county record fuzzily matches to graham .', 'tostr': 'filter_eq { all_rows ; county ; graham }'}, 'hancock'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; county ; graham } ; hancock }', 'tointer': 'select the rows whose county record fuzzily matches to graham . take the hancock record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; county ; coconino } ; hancock } ; hop { filter_eq { all_rows ; county ; graham } ; hancock } }', 'tointer': 'select the rows whose county record fuzzily matches to coconino . take the hancock record of this row . select the rows whose county record fuzzily matches to graham . take the hancock record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'coconino'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to coconino .', 'tostr': 'filter_eq { all_rows ; county ; coconino }'}, 'hancock'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; county ; coconino } ; hancock }', 'tointer': 'select the rows whose county record fuzzily matches to coconino . take the hancock record of this row .'}, '1504'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; county ; coconino } ; hancock } ; 1504 }', 'tointer': 'the hancock record of the first row is 1504 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'graham'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose county record fuzzily matches to graham .', 'tostr': 'filter_eq { all_rows ; county ; graham }'}, 'hancock'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; county ; graham } ; hancock }', 'tointer': 'select the rows whose county record fuzzily matches to graham . take the hancock record of this row .'}, '322'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; county ; graham } ; hancock } ; 322 }', 'tointer': 'the hancock record of the second row is 322 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; county ; coconino } ; hancock } ; 1504 } ; eq { hop { filter_eq { all_rows ; county ; graham } ; hancock } ; 322 } }', 'tointer': 'the hancock record of the first row is 1504 . the hancock record of the second row is 322 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; county ; coconino } ; hancock } ; hop { filter_eq { all_rows ; county ; graham } ; hancock } } ; and { eq { hop { filter_eq { all_rows ; county ; coconino } ; hancock } ; 1504 } ; eq { hop { filter_eq { all_rows ; county ; graham } ; hancock } ; 322 } } } = true', 'tointer': 'select the rows whose county record fuzzily matches to coconino . take the hancock record of this row . select the rows whose county record fuzzily matches to graham . take the hancock record of this row . the first record is greater than the second record . the hancock record of the first row is 1504 . the hancock record of the second row is 322 .'} | and { greater { hop { filter_eq { all_rows ; county ; coconino } ; hancock } ; hop { filter_eq { all_rows ; county ; graham } ; hancock } } ; and { eq { hop { filter_eq { all_rows ; county ; coconino } ; hancock } ; 1504 } ; eq { hop { filter_eq { all_rows ; county ; graham } ; hancock } ; 322 } } } = true | select the rows whose county record fuzzily matches to coconino . take the hancock record of this row . select the rows whose county record fuzzily matches to graham . take the hancock record of this row . the first record is greater than the second record . the hancock record of the first row is 1504 . the hancock record of the second row is 322 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'county_11': 11, 'coconino_12': 12, 'hancock_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'county_15': 15, 'graham_16': 16, 'hancock_17': 17, 'and_7': 7, 'eq_5': 5, '1504_18': 18, 'eq_6': 6, '322_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'county_11': 'county', 'coconino_12': 'coconino', 'hancock_13': 'hancock', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'county_15': 'county', 'graham_16': 'graham', 'hancock_17': 'hancock', 'and_7': 'and', 'eq_5': 'eq', '1504_18': '1504', 'eq_6': 'eq', '322_19': '322'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'county_11': [0], 'coconino_12': [0], 'hancock_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'county_15': [1], 'graham_16': [1], 'hancock_17': [3], 'and_7': [8], 'eq_5': [7], '1504_18': [5], 'eq_6': [7], '322_19': [6]} | ['county', 'starky', 'starky %', 'hancock', 'hancock %', 'mccain', 'mccain %', 'total'] | [['apache', '9588', '40.95 %', '905', '3.86 %', '12923', '55.19 %', '23416'], ['cochise', '9555', '21.80 %', '1394', '3.18 %', '32879', '75.02 %', '43828'], ['coconino', '13520', '26.58 %', '1504', '2.96 %', '35849', '70.47 %', '50873'], ['gila', '4291', '20.96 %', '632', '3.09 %', '15551', '75.95 %', '20474'], ['graham', '2000', '19.06 %', '322', '3.07 %', '8171', '77.87 %', '10493'], ['greenlee', '746', '25.03 %', '68', '2.28 %', '2166', '72.68 %', '2980'], ['la paz', '965', '19.51 %', '156', '3.15 %', '3826', '77.34 %', '4947'], ['maricopa', '216124', '18.58 %', '29769', '2.56 %', '917527', '78.86 %', '1163420'], ['mohave', '10423', '18.44 %', '1686', '2.98 %', '44402', '78.57 %', '56511'], ['navajo', '7434', '23.42 %', '1222', '3.85 %', '23091', '72.73 %', '31747'], ['pima', '89483', '25.17 %', '7980', '2.24 %', '258010', '72.58 %', '355473'], ['pinal', '13595', '21.45 %', '1692', '2.67 %', '48094', '75.88 %', '63381'], ['santa cruz', '3583', '31.60 %', '252', '2.22 %', '7502', '66.17 %', '11337'], ['yavapai', '14852', '17.41 %', '3160', '3.70 %', '67312', '78.89 %', '85324'], ['yuma', '8348', '22.28 %', '1056', '2.82 %', '28069', '74.90 %', '37473']] |
list of doctor who audiobooks | https://en.wikipedia.org/wiki/List_of_Doctor_Who_audiobooks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20174050-23.html.csv | count | a total of nine doctor who audiobooks were original audiobooks that were not published in book form . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'not published in book form', 'result': '9', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'notes', 'not published in book form'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose notes record fuzzily matches to not published in book form .', 'tostr': 'filter_eq { all_rows ; notes ; not published in book form }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; notes ; not published in book form } }', 'tointer': 'select the rows whose notes record fuzzily matches to not published in book form . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; notes ; not published in book form } } ; 9 } = true', 'tointer': 'select the rows whose notes record fuzzily matches to not published in book form . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; notes ; not published in book form } } ; 9 } = true | select the rows whose notes record fuzzily matches to not published in book form . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'notes_5': 5, 'not published in book form_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'notes_5': 'notes', 'not published in book form_6': 'not published in book form', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'notes_5': [0], 'not published in book form_6': [0], '9_7': [2]} | ['title', 'author', 'reader', 'format', 'company', 'release date', 'notes'] | [['another life', 'anghelides , peter peter anghelides', 'barrowman , john john barrowman', '3 - cd', 'bbc audio', '2007 - 04 - 02 2 april 2007', 'abridged'], ['slow decay', 'lane , andy andy lane', 'gorman , burn burn gorman', '3 - cd', 'bbc audio', '2007 - 04 - 02 2 april 2007', 'abridged'], ['border princes', 'abnett , dan dan abnett', 'myles , eve eve myles', '3 - cd', 'bbc audio', '2007 - 04 - 02 2 april 2007', 'abridged'], ['hidden', 'saville , steven steven savile', 'mori , naoko naoko mori', '2 - cd', 'bbc audio', '2008 - 02 - 04 4 february 2008', 'an original audiobook , not published in book form'], ['everyone says hello', 'abnett , dan dan abnett', 'gorman , burn burn gorman', '2 - cd', 'bbc audio', '2008 - 02 - 04 4 february 2008', 'an original audiobook , not published in book form'], ['in the shadows', 'lidster , joseph joseph lidster', 'myles , eve eve myles', '2 - cd', 'bbc audio', '2009 - 05 - 07 7 may 2009', 'an original audiobook , not published in book form'], ['the sin eaters', 'minchin , brian brian minchin', 'david - lloyd , gareth gareth david - lloyd', '2 - cd', 'bbc audio', '2009 - 06 - 04 4 june 2009', 'an original audiobook , not published in book form'], ['department x', 'goss , james james goss', 'owen , kai kai owen', '2 - cd', 'bbc audio', '2011 - 04 - 03 3 march 2011', 'an original audiobook , not published in book form'], ['ghost train', 'goss , james james goss', 'owen , kai kai owen', '2 - cd', 'bbc audio', '2011 - 04 - 03 3 march 2011', 'an original audiobook , not published in book form'], ['long time dead', 'pinborough , sarah sarah pinborough', 'varma , idria indira varma', 'download', 'audiogo', '2011 - 10 - 01 october 2011', 'unabridged'], ['the men who sold the world', 'adams , guy guy adams', 'telfer , john john telfer', 'download', 'audiogo', '2011 - 10 - 01 october 2011', 'unabridged'], ['army of one', 'edginton , ian ian edginton', 'owen , kai kai owen', 'download / cd', 'audiogo', '2012 - 03 - 08 8 march 2012', 'an original audiobook , not published in book form'], ['fallout', 'llewellyn , david david llewellyn', 'price , tom tom price', 'download / cd', 'audiogo', '2012 - 04 - 05 5 april 2012', 'an original audiobook , not published in book form'], ['red skies', 'lidster , joseph joseph lidster', 'telfer , john john telfer', 'download / cd', 'audiogo', '2012 - 05 - 03 3 may 2012', 'an original audiobook , not published in book form']] |
grand tour ( cycling ) | https://en.wikipedia.org/wiki/Grand_Tour_%28cycling%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1286819-7.html.csv | ordinal | the 14th rider to compete had a final position of 66th in the vuelta . | {'row': '6', 'col': '2', 'order': '14', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '14'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 14 }'}, 'final position - vuelta'], 'result': '66', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 14 } ; final position - vuelta }'}, '66'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 14 } ; final position - vuelta } ; 66 } = true', 'tointer': 'select the row whose year record of all rows is 14th minimum . the final position - vuelta record of this row is 66 .'} | eq { hop { nth_argmin { all_rows ; year ; 14 } ; final position - vuelta } ; 66 } = true | select the row whose year record of all rows is 14th minimum . the final position - vuelta record of this row is 66 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '14_6': 6, 'final position - vuelta_7': 7, '66_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'year_5': 'year', '14_6': '14', 'final position - vuelta_7': 'final position - vuelta', '66_8': '66'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '14_6': [0], 'final position - vuelta_7': [1], '66_8': [2]} | ['rider', 'year', 'final position - giro', 'final position - tour', 'final position - vuelta'] | [['eduardo chozas', '1990', '11', '6', '33'], ['marino lejarreta ( 3 )', '1990', '7', '5', '55'], ['marino lejarreta ( 2 )', '1989', '10', '5', '20'], ['luis - javier lukin', '1988', '32', '82', '60'], ['marino lejarreta', '1987', '4', '10', '34'], ['philippe poissonier', '1985', '86', '90', '66'], ['jose luis uribezubia', '1971', '29', '50', '27'], ['jose manuel fuente', '1971', '39', '72', '54'], ['federico bahamontes', '1958', '17', '8', '6'], ['pierino baffi', '1958', '23', '63', '37'], ['mario baroni', '1957', '74', '53', '46'], ['gastone nencini', '1957', '1', '6', '9'], ['bernardo ruiz ( 3 )', '1957', '55', '24', '3'], ['arrigo padovan', '1956', '12', '26', '19'], ['bernardo ruiz ( 2 )', '1956', '38', '70', '31'], ['josã serra', '1956', '26', '81', '9'], ['raphael geminiani', '1955', '4', '6', '3'], ['bernardo ruiz', '1955', '28', '22', '14'], ['louis caput', '1955', '68', '54', '55']] |
kathy whitworth | https://en.wikipedia.org/wiki/Kathy_Whitworth | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1075064-4.html.csv | count | kathy whitworth won a total of two golf tournaments by a margin of 3 strokes . | {'scope': 'all', 'criterion': 'equal', 'value': '3 strokes', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'margin', '3 strokes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose margin record fuzzily matches to 3 strokes .', 'tostr': 'filter_eq { all_rows ; margin ; 3 strokes }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; margin ; 3 strokes } }', 'tointer': 'select the rows whose margin record fuzzily matches to 3 strokes . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; margin ; 3 strokes } } ; 2 } = true', 'tointer': 'select the rows whose margin record fuzzily matches to 3 strokes . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; margin ; 3 strokes } } ; 2 } = true | select the rows whose margin record fuzzily matches to 3 strokes . 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, 'margin_5': 5, '3 strokes_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', 'margin_5': 'margin', '3 strokes_6': '3 strokes', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'margin_5': [0], '3 strokes_6': [0], '2_7': [2]} | ['year', 'championship', 'winning score', 'margin', 'runner ( s ) - up'] | [['1965', 'titleholders championship', '- 1 ( 71 + 71 + 74 + 71 = 287 )', '10 strokes', 'peggy wilson'], ['1966', 'titleholders championship', '+ 3 ( 74 + 70 + 74 + 73 = 291 )', '2 strokes', 'judy kimball - simon , mary mills'], ['1967', 'lpga championship', '- 8 ( 69 + 74 + 72 + 69 = 284 )', '1 stroke', 'shirley englehorn'], ['1967', "women 's western open", '11 ( 71 + 74 + 73 + 71 = 289 )', '3 strokes', 'sandra haynie'], ['1971', 'eve - lpga championship', '- 4 ( 71 + 73 + 70 + 74 = 288 )', '3 strokes', 'kathy ahern'], ['1975', 'lpga championship', '- 4 ( 70 + 70 + 75 + 73 = 288 )', '1 stroke', 'sandra haynie']] |
1981 vfl season | https://en.wikipedia.org/wiki/1981_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-11.html.csv | superlative | richmond scored the highest of any team , home or away . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,4', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'home team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; home team score }'}, 'home team'], 'result': 'richmond', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; home team score } ; home team }'}, 'richmond'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; home team score } ; home team } ; richmond }', 'tointer': 'select the row whose home team score record of all rows is maximum . the home team record of this row is richmond .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'home team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; home team score }'}, 'away team score'], 'result': '14.10 ( 94 )', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; home team score } ; away team score }'}, '14.10 ( 94 )'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; home team score } ; away team score } ; 14.10 ( 94 ) }', 'tointer': 'the away team score record of this row is 14.10 ( 94 ) .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; home team score } ; home team } ; richmond } ; eq { hop { argmax { all_rows ; home team score } ; away team score } ; 14.10 ( 94 ) } } = true', 'tointer': 'select the row whose home team score record of all rows is maximum . the home team record of this row is richmond . the away team score record of this row is 14.10 ( 94 ) .'} | and { eq { hop { argmax { all_rows ; home team score } ; home team } ; richmond } ; eq { hop { argmax { all_rows ; home team score } ; away team score } ; 14.10 ( 94 ) } } = true | select the row whose home team score record of all rows is maximum . the home team record of this row is richmond . the away team score record of this row is 14.10 ( 94 ) . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'home team score_8': 8, 'home team_9': 9, 'richmond_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'away team score_11': 11, '14.10 (94)_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'home team score_8': 'home team score', 'home team_9': 'home team', 'richmond_10': 'richmond', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'away team score_11': 'away team score', '14.10 (94)_12': '14.10 ( 94 )'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'home team score_8': [0], 'home team_9': [1], 'richmond_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'away team score_11': [3], '14.10 (94)_12': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '20.16 ( 136 )', 'melbourne', '14.10 ( 94 )', 'mcg', '31025', '6 june 1981'], ['st kilda', '14.15 ( 99 )', 'fitzroy', '7.17 ( 59 )', 'moorabbin oval', '21672', '6 june 1981'], ['hawthorn', '18.19 ( 127 )', 'collingwood', '12.9 ( 81 )', 'vfl park', '92935', '6 june 1981'], ['footscray', '12.10 ( 82 )', 'geelong', '17.15 ( 117 )', 'western oval', '24974', '8 june 1981'], ['carlton', '17.13 ( 115 )', 'north melbourne', '11.18 ( 84 )', 'princes park', '31808', '8 june 1981'], ['south melbourne', '12.8 ( 80 )', 'essendon', '15.18 ( 108 )', 'lake oval', '28588', '8 june 1981']] |
wru division one west | https://en.wikipedia.org/wiki/WRU_Division_One_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12792876-2.html.csv | count | in wru division one west , 4 clubs had exactly one draw . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'drawn', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose drawn record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; drawn ; 1 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; drawn ; 1 } }', 'tointer': 'select the rows whose drawn record is equal to 1 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; drawn ; 1 } } ; 4 } = true', 'tointer': 'select the rows whose drawn record is equal to 1 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; drawn ; 1 } } ; 4 } = true | select the rows whose drawn record is equal to 1 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'drawn_5': 5, '1_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'drawn_5': 'drawn', '1_6': '1', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'drawn_5': [0], '1_6': [0], '4_7': [2]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['bridgend ravens', '22', '1', '1', '848', '337', '108', '30', '13', '1', '96'], ['narberth rfc', '22', '1', '8', '726', '443', '92', '53', '12', '5', '71'], ['bridgend athletic rfc', '22', '3', '5', '564', '486', '61', '55', '5', '1', '68'], ['bonymaen rfc', '22', '2', '6', '478', '464', '55', '55', '5', '3', '68'], ['corus ( port talbot ) rfc', '22', '1', '8', '576', '544', '73', '58', '10', '4', '68'], ['uwic rfc', '22', '1', '9', '624', '559', '80', '66', '10', '4', '64'], ['whitland rfc', '22', '2', '9', '550', '460', '69', '49', '6', '3', '57'], ['carmarthen athletic rfc', '22', '3', '10', '509', '554', '64', '69', '6', '2', '50'], ['llangennech rfc', '22', '0', '14', '402', '577', '46', '69', '4', '3', '39'], ['waunarlwydd rfc', '22', '0', '16', '505', '602', '48', '75', '3', '10', '37'], ['maesteg rfc', '22', '0', '19', '427', '714', '43', '91', '2', '5', '19'], ['felinfoel rfc', '22', '2', '19', '334', '803', '43', '112', '3', '5', '16']] |
midhordland | https://en.wikipedia.org/wiki/Midhordland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1452651-1.html.csv | ordinal | samnanger has the 2nd highest area among those whose language form is nynorsk in midhordland . | {'scope': 'subset', 'row': '8', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'nynorsk'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language form', 'nynorsk'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; language form ; nynorsk }', 'tointer': 'select the rows whose language form record fuzzily matches to nynorsk .'}, 'area', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; language form ; nynorsk } ; area ; 2 }'}, 'name'], 'result': 'samnanger', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; language form ; nynorsk } ; area ; 2 } ; name }'}, 'samnanger'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; language form ; nynorsk } ; area ; 2 } ; name } ; samnanger } = true', 'tointer': 'select the rows whose language form record fuzzily matches to nynorsk . select the row whose area record of these rows is 2nd maximum . the name record of this row is samnanger .'} | eq { hop { nth_argmax { filter_eq { all_rows ; language form ; nynorsk } ; area ; 2 } ; name } ; samnanger } = true | select the rows whose language form record fuzzily matches to nynorsk . select the row whose area record of these rows is 2nd maximum . the name record of this row is samnanger . | 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, 'language form_6': 6, 'nynorsk_7': 7, 'area_8': 8, '2_9': 9, 'name_10': 10, 'samnanger_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', 'language form_6': 'language form', 'nynorsk_7': 'nynorsk', 'area_8': 'area', '2_9': '2', 'name_10': 'name', 'samnanger_11': 'samnanger'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'language form_6': [0], 'nynorsk_7': [0], 'area_8': [1], '2_9': [1], 'name_10': [2], 'samnanger_11': [3]} | ['name', 'innhabitants', 'area', 'mayor', 'party', 'municipal code', 'language form'] | [['askøy', '24875', '100', 'knut hanselmann', 'frp', '1247', 'neutral'], ['fjell', '21744', '148', 'lars lie', 'høyre', '1246', 'nynorsk'], ['os', '16590', '140', 'terje søviknes', 'frp', '1243', 'nynorsk'], ['sund', '6069', '100', 'albrigt sangolt', 'høyre', '1245', 'nynorsk'], ['austevoll', '4503', '117', 'helge andre njåstad', 'frp', '1244', 'nynorsk'], ['øygarden', '4235', '66', 'olav martin vik', 'll', '1259', 'nynorsk'], ['fusa', '3822', '378', 'hans s vindenes', 'sp', '1241', 'nynorsk'], ['samnanger', '2362', '269', 'marit a aase', 'krf', '1242', 'nynorsk']] |
mountain peaks of the rocky mountains | https://en.wikipedia.org/wiki/Mountain_peaks_of_the_Rocky_Mountains | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12069382-4.html.csv | majority | the majority of these mountains are located in the state of colorado . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'colorado', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'region', 'colorado'], 'result': True, 'ind': 0, 'tointer': 'for the region records of all rows , all of them fuzzily match to colorado .', 'tostr': 'all_eq { all_rows ; region ; colorado } = true'} | all_eq { all_rows ; region ; colorado } = true | for the region records of all rows , all of them fuzzily match to colorado . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'region_3': 3, 'colorado_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'region_3': 'region', 'colorado_4': 'colorado'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'region_3': [0], 'colorado_4': [0]} | ['rank', 'mountain peak', 'region', 'mountain range', 'location'] | [['1', 'fishers peak', 'colorado', 'raton mesa', '37.0982 degreen 104.4628 degreew'], ['2', 'east spanish peak', 'colorado', 'spanish peaks', '37.3934 degreen 104.9201 degreew'], ['3', 'west spanish peak', 'colorado', 'spanish peaks', '37.3756 degreen 104.9934 degreew'], ['4', 'pikes peak', 'colorado', 'front range', '38.8405 degreen 105.0442 degreew'], ['5', 'blanca peak', 'colorado', 'sangre de cristo mountains', '37.5775 degreen 105.4856 degreew'], ['6', 'mount harvard', 'colorado', 'sawatch range', '38.9244 degreen 106.3207 degreew'], ['7', 'mount elbert', 'colorado', 'sawatch range', '39.1178 degreen 106.4454 degreew']] |
claudio cantelli | https://en.wikipedia.org/wiki/Claudio_Cantelli | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18446940-1.html.csv | aggregation | between 2006 and 2009 , claudio cantelli drove an average of 12 races per year . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '12', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'races'], 'result': '12', 'ind': 0, 'tostr': 'avg { all_rows ; races }'}, '12'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; races } ; 12 } = true', 'tointer': 'the average of the races record of all rows is 12 .'} | round_eq { avg { all_rows ; races } ; 12 } = true | the average of the races record of all rows is 12 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'races_4': 4, '12_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'races_4': 'races', '12_5': '12'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'races_4': [0], '12_5': [1]} | ['season', 'series', 'team', 'races', 'wins', 'podiums', 'points', 'position'] | [['2006', 'brazilian formula renault 2.0', 'dragão motorsport', '9', '0', '2', '185', '9th'], ['2006', 'brazilian formula renault 2.0', 'cesário frenault', '9', '0', '2', '185', '9th'], ['2006', 'eurocup formula renault 2.0', 'graff racing', '6', '0', '0', '1', '29th'], ['2006', 'british formula renault 2.0 - winter series', 'position 1 racing', '4', '0', '0', '38', '11th'], ['2007', 'international formula master', 'jd motorsport', '16', '0', '0', '1', '28th'], ['2008', 'formula renault 3.5 series', 'ultimate signature', '15', '0', '0', '3', '28th'], ['2008', 'formula renault 3.5 series', 'rc motorsport', '15', '0', '0', '3', '28th'], ['2009', 'south american formula 3 championship', 'bassan motorsport', '17', '3', '6', '97', '2nd']] |
1979 formula one season | https://en.wikipedia.org/wiki/1979_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140080-2.html.csv | unique | in the 1979 formula one season , the only race that patrick depailler won , was the spanish grand prix . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'patrick depailler', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'race winner', 'patrick depailler'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race winner record fuzzily matches to patrick depailler .', 'tostr': 'filter_eq { all_rows ; race winner ; patrick depailler }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; race winner ; patrick depailler } }', 'tointer': 'select the rows whose race winner record fuzzily matches to patrick depailler . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'race winner', 'patrick depailler'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race winner record fuzzily matches to patrick depailler .', 'tostr': 'filter_eq { all_rows ; race winner ; patrick depailler }'}, 'race'], 'result': 'spanish grand prix', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; race winner ; patrick depailler } ; race }'}, 'spanish grand prix'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; race winner ; patrick depailler } ; race } ; spanish grand prix }', 'tointer': 'the race record of this unqiue row is spanish grand prix .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; race winner ; patrick depailler } } ; eq { hop { filter_eq { all_rows ; race winner ; patrick depailler } ; race } ; spanish grand prix } } = true', 'tointer': 'select the rows whose race winner record fuzzily matches to patrick depailler . there is only one such row in the table . the race record of this unqiue row is spanish grand prix .'} | and { only { filter_eq { all_rows ; race winner ; patrick depailler } } ; eq { hop { filter_eq { all_rows ; race winner ; patrick depailler } ; race } ; spanish grand prix } } = true | select the rows whose race winner record fuzzily matches to patrick depailler . there is only one such row in the table . the race record of this unqiue row is spanish grand prix . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'race winner_7': 7, 'patrick depailler_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'race_9': 9, 'spanish grand prix_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'race winner_7': 'race winner', 'patrick depailler_8': 'patrick depailler', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'race_9': 'race', 'spanish grand prix_10': 'spanish grand prix'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'race winner_7': [0], 'patrick depailler_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'race_9': [2], 'spanish grand prix_10': [3]} | ['race', 'date', 'location', 'pole position', 'fastest lap', 'race winner', 'constructor', 'report'] | [['argentine grand prix', '21 january', 'buenos aires', 'jacques laffite', 'jacques laffite', 'jacques laffite', 'ligier - ford', 'report'], ['brazilian grand prix', '4 february', 'interlagos', 'jacques laffite', 'jacques laffite', 'jacques laffite', 'ligier - ford', 'report'], ['south african grand prix', '3 march', 'kyalami', 'jean - pierre jabouille', 'gilles villeneuve', 'gilles villeneuve', 'ferrari', 'report'], ['united states grand prix west', '8 april', 'long beach', 'gilles villeneuve', 'gilles villeneuve', 'gilles villeneuve', 'ferrari', 'report'], ['spanish grand prix', '29 april', 'jarama', 'jacques laffite', 'gilles villeneuve', 'patrick depailler', 'ligier - ford', 'report'], ['belgian grand prix', '13 may', 'zolder', 'jacques laffite', 'gilles villeneuve', 'jody scheckter', 'ferrari', 'report'], ['monaco grand prix', '27 may', 'monaco', 'jody scheckter', 'patrick depailler', 'jody scheckter', 'ferrari', 'report'], ['french grand prix', '1 july', 'dijon - prenois', 'jean - pierre jabouille', 'rené arnoux', 'jean - pierre jabouille', 'renault', 'report'], ['british grand prix', '14 july', 'silverstone', 'alan jones', 'clay regazzoni', 'clay regazzoni', 'williams - ford', 'report'], ['german grand prix', '29 july', 'hockenheimring', 'jean - pierre jabouille', 'gilles villeneuve', 'alan jones', 'williams - ford', 'report'], ['austrian grand prix', '12 august', 'österreichring', 'rené arnoux', 'rené arnoux', 'alan jones', 'williams - ford', 'report'], ['dutch grand prix', '26 august', 'zandvoort', 'rené arnoux', 'gilles villeneuve', 'alan jones', 'williams - ford', 'report'], ['italian grand prix', '9 september', 'monza', 'jean - pierre jabouille', 'clay regazzoni', 'jody scheckter', 'ferrari', 'report'], ['canadian grand prix', '30 september', 'île notre - dame', 'alan jones', 'alan jones', 'alan jones', 'williams - ford', 'report'], ['united states grand prix', '7 october', 'watkins glen', 'alan jones', 'nelson piquet', 'gilles villeneuve', 'ferrari', 'report']] |
sport in queensland | https://en.wikipedia.org/wiki/Sport_in_Queensland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10909383-1.html.csv | comparative | the brisbane broncos were established as a team before the brisbane bandits . | {'row_1': '2', 'row_2': '1', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club / team', 'brisbane broncos'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club / team record fuzzily matches to brisbane broncos .', 'tostr': 'filter_eq { all_rows ; club / team ; brisbane broncos }'}, 'established'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club / team ; brisbane broncos } ; established }', 'tointer': 'select the rows whose club / team record fuzzily matches to brisbane broncos . take the established record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club / team', 'brisbane bandits'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club / team record fuzzily matches to brisbane bandits .', 'tostr': 'filter_eq { all_rows ; club / team ; brisbane bandits }'}, 'established'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club / team ; brisbane bandits } ; established }', 'tointer': 'select the rows whose club / team record fuzzily matches to brisbane bandits . take the established record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; club / team ; brisbane broncos } ; established } ; hop { filter_eq { all_rows ; club / team ; brisbane bandits } ; established } } = true', 'tointer': 'select the rows whose club / team record fuzzily matches to brisbane broncos . take the established record of this row . select the rows whose club / team record fuzzily matches to brisbane bandits . take the established record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; club / team ; brisbane broncos } ; established } ; hop { filter_eq { all_rows ; club / team ; brisbane bandits } ; established } } = true | select the rows whose club / team record fuzzily matches to brisbane broncos . take the established record of this row . select the rows whose club / team record fuzzily matches to brisbane bandits . take the established 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, 'club / team_7': 7, 'brisbane broncos_8': 8, 'established_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club / team_11': 11, 'brisbane bandits_12': 12, 'established_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', 'club / team_7': 'club / team', 'brisbane broncos_8': 'brisbane broncos', 'established_9': 'established', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club / team_11': 'club / team', 'brisbane bandits_12': 'brisbane bandits', 'established_13': 'established'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club / team_7': [0], 'brisbane broncos_8': [0], 'established_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club / team_11': [1], 'brisbane bandits_12': [1], 'established_13': [3]} | ['club / team', 'league', 'venue', 'established', 'premierships'] | [['brisbane bandits', 'australian baseball league', 'brisbane exhibition ground', '1989', '1'], ['brisbane broncos', 'national rugby league', 'suncorp stadium', '1988', '6'], ['brisbane lions', 'australian football league', 'brisbane cricket ground', '1997', '3'], ['brisbane roar', 'a - league / w - league', 'suncorp stadium', '2004', '1 / 2'], ['queensland blades', 'australian hockey league', 'queensland state hockey centre', '1991', '5'], ['queensland bulls', 'pura cup / ford ranger cup', 'brisbane cricket ground', '1892', '13'], ['queensland firebirds', 'commonwealth bank trophy', 'chandler arena', '1997', 'nil'], ['queensland reds', 'super rugby', 'suncorp stadium', '1996', '1'], ['triple eight race engineering', 'international v8 supercars championship', 'queensland raceway', '2003', '4']] |
icl 20s world series 2007 - 08 | https://en.wikipedia.org/wiki/ICL_20s_World_Series_2007%E2%80%9308 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17103566-1.html.csv | ordinal | the match on april 10 between icl pakistan and icl world was the 2nd in the 2008 icl world series . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2,4,5', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'match number', '2'], 'result': '2', 'ind': 0, 'tostr': 'nth_min { all_rows ; match number ; 2 }', 'tointer': 'the 2nd minimum match number record of all rows is 2 .'}, '2'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; match number ; 2 } ; 2 }', 'tointer': 'the 2nd minimum match number record of all rows is 2 .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'match number', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; match number ; 2 }'}, 'date'], 'result': 'april 10', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; match number ; 2 } ; date }'}, 'april 10'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; match number ; 2 } ; date } ; april 10 }', 'tointer': 'the date record of the row with 2nd minimum match number record is april 10 .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'match number', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; match number ; 2 }'}, 'team 1'], 'result': 'icl pakistan', 'ind': 5, 'tostr': 'hop { nth_argmin { all_rows ; match number ; 2 } ; team 1 }'}, 'icl pakistan'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 1 } ; icl pakistan }', 'tointer': 'the team 1 record of the row with 2nd minimum match number record is icl pakistan .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'match number', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; match number ; 2 }'}, 'team 2'], 'result': 'icl world', 'ind': 7, 'tostr': 'hop { nth_argmin { all_rows ; match number ; 2 } ; team 2 }'}, 'icl world'], 'result': True, 'ind': 8, 'tostr': 'eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 2 } ; icl world }', 'tointer': 'the team 2 record of the row with 2nd minimum match number record is icl world .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 1 } ; icl pakistan } ; eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 2 } ; icl world } }', 'tointer': 'the team 1 record of the row with 2nd minimum match number record is icl pakistan . the team 2 record of the row with 2nd minimum match number record is icl world .'}], 'result': True, 'ind': 10, 'tostr': 'and { eq { hop { nth_argmin { all_rows ; match number ; 2 } ; date } ; april 10 } ; and { eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 1 } ; icl pakistan } ; eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 2 } ; icl world } } }', 'tointer': 'the date record of the row with 2nd minimum match number record is april 10 . the team 1 record of the row with 2nd minimum match number record is icl pakistan . the team 2 record of the row with 2nd minimum match number record is icl world .'}], 'result': True, 'ind': 11, 'tostr': 'and { eq { nth_min { all_rows ; match number ; 2 } ; 2 } ; and { eq { hop { nth_argmin { all_rows ; match number ; 2 } ; date } ; april 10 } ; and { eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 1 } ; icl pakistan } ; eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 2 } ; icl world } } } } = true', 'tointer': 'the 2nd minimum match number record of all rows is 2 . the date record of the row with 2nd minimum match number record is april 10 . the team 1 record of the row with 2nd minimum match number record is icl pakistan . the team 2 record of the row with 2nd minimum match number record is icl world .'} | and { eq { nth_min { all_rows ; match number ; 2 } ; 2 } ; and { eq { hop { nth_argmin { all_rows ; match number ; 2 } ; date } ; april 10 } ; and { eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 1 } ; icl pakistan } ; eq { hop { nth_argmin { all_rows ; match number ; 2 } ; team 2 } ; icl world } } } } = true | the 2nd minimum match number record of all rows is 2 . the date record of the row with 2nd minimum match number record is april 10 . the team 1 record of the row with 2nd minimum match number record is icl pakistan . the team 2 record of the row with 2nd minimum match number record is icl world . | 14 | 12 | {'and_11': 11, 'result_12': 12, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_13': 13, 'match number_14': 14, '2_15': 15, '2_16': 16, 'and_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_17': 17, 'match number_18': 18, '2_19': 19, 'date_20': 20, 'april 10_21': 21, 'and_9': 9, 'str_eq_6': 6, 'str_hop_5': 5, 'team 1_22': 22, 'icl pakistan_23': 23, 'str_eq_8': 8, 'str_hop_7': 7, 'team 2_24': 24, 'icl world_25': 25} | {'and_11': 'and', 'result_12': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_13': 'all_rows', 'match number_14': 'match number', '2_15': '2', '2_16': '2', 'and_10': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_17': 'all_rows', 'match number_18': 'match number', '2_19': '2', 'date_20': 'date', 'april 10_21': 'april 10', 'and_9': 'and', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'team 1_22': 'team 1', 'icl pakistan_23': 'icl pakistan', 'str_eq_8': 'str_eq', 'str_hop_7': 'str_hop', 'team 2_24': 'team 2', 'icl world_25': 'icl world'} | {'and_11': [12], 'result_12': [], 'eq_1': [11], 'nth_min_0': [1], 'all_rows_13': [0], 'match number_14': [0], '2_15': [0], '2_16': [1], 'and_10': [11], 'str_eq_4': [10], 'str_hop_3': [4], 'nth_argmin_2': [3, 5, 7], 'all_rows_17': [2], 'match number_18': [2], '2_19': [2], 'date_20': [3], 'april 10_21': [4], 'and_9': [10], 'str_eq_6': [9], 'str_hop_5': [6], 'team 1_22': [5], 'icl pakistan_23': [6], 'str_eq_8': [9], 'str_hop_7': [8], 'team 2_24': [7], 'icl world_25': [8]} | ['match number', 'date', 'venue', 'team 1', 'team 2', 'result', 'man of the match'] | [['1', 'april 9', 'hyderabad', 'icl world', 'icl india', 'icl world by 8 wickets', 'damien martyn ( icl world )'], ['2', 'april 10', 'hyderabad', 'icl pakistan', 'icl world', 'icl pakistan by 9 wickets', 'imran nazir ( icl pakistan )'], ['3', 'april 11', 'hyderabad', 'icl india', 'icl pakistan', 'icl india by 4 wickets', 'ibrahim khaleel ( icl india )'], ['4', 'april 12', 'hyderabad', 'icl india', 'icl world', 'icl india by 4 wickets', 'stuart binny ( icl india )'], ['5', 'april 13', 'hyderabad', 'icl india', 'icl pakistan', 'icl india by 4 wickets', 'tejinder pal singh ( icl india )']] |
allen county conference | https://en.wikipedia.org/wiki/Allen_County_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18765101-1.html.csv | comparative | in the allen county conference , leo joined 20 years before southern adams . | {'row_1': '5', 'row_2': '6', 'col': '7', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '20 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'leo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to leo .', 'tostr': 'filter_eq { all_rows ; school ; leo }'}, 'year joined'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; leo } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to leo . take the year joined record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'south adams'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose school record fuzzily matches to south adams .', 'tostr': 'filter_eq { all_rows ; school ; south adams }'}, 'year joined'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; school ; south adams } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to south adams . take the year joined record of this row .'}], 'result': '-20 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; school ; leo } ; year joined } ; hop { filter_eq { all_rows ; school ; south adams } ; year joined } }'}, '-20 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; school ; leo } ; year joined } ; hop { filter_eq { all_rows ; school ; south adams } ; year joined } } ; -20 years } = true', 'tointer': 'select the rows whose school record fuzzily matches to leo . take the year joined record of this row . select the rows whose school record fuzzily matches to south adams . take the year joined record of this row . the second record is 20 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; school ; leo } ; year joined } ; hop { filter_eq { all_rows ; school ; south adams } ; year joined } } ; -20 years } = true | select the rows whose school record fuzzily matches to leo . take the year joined record of this row . select the rows whose school record fuzzily matches to south adams . take the year joined record of this row . the second record is 20 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, 'leo_9': 9, 'year joined_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'school_12': 12, 'south adams_13': 13, 'year joined_14': 14, '-20 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', 'leo_9': 'leo', 'year joined_10': 'year joined', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'school_12': 'school', 'south adams_13': 'south adams', 'year joined_14': 'year joined', '-20 years_15': '-20 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], 'leo_9': [0], 'year joined_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'school_12': [1], 'south adams_13': [1], 'year joined_14': [3], '-20 years_15': [5]} | ['school', 'location', 'mascot', 'enrollment 08 - 09', 'ihsaa class / football class', 'county', 'year joined', 'previous conference'] | [['adams central', 'monroe', 'flying jets', '404', '2a / 1a', '01 adams', '1969', 'independent'], ['bluffton', 'bluffton', 'tigers', '467', '2a / 2a', '90 wells', '1989', 'northeastern indiana'], ['garrett', 'garrett', 'railroaders', '598', '3a / 3a', '17 dekalb', '2005', 'northeast corner'], ['heritage', 'monroeville', 'patriots', '734', '3a / 3a', '02 allen', '1969', 'independent'], ['leo', 'leo', 'lions', '980', '3a / 4a', '02 allen', '1969', 'independent'], ['south adams', 'berne', 'starfires', '398', '2a / 1a', '01 adams', '1989', 'northeastern indiana'], ['southern wells', 'poneto', 'raiders', '227', '1a / 1a', '90 wells', '1971', 'none ( new school )'], ['woodlan', 'woodburn', 'warriors', '591', '3a / 2a', '02 allen', '1969', 'independents']] |
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 | count | three of the electors had a cardinalatial order and title of bishop . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'bishop', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cardinalatial order and title', 'bishop'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cardinalatial order and title record fuzzily matches to bishop .', 'tostr': 'filter_eq { all_rows ; cardinalatial order and title ; bishop }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; cardinalatial order and title ; bishop } }', 'tointer': 'select the rows whose cardinalatial order and title record fuzzily matches to bishop . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; cardinalatial order and title ; bishop } } ; 3 } = true', 'tointer': 'select the rows whose cardinalatial order and title record fuzzily matches to bishop . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; cardinalatial order and title ; bishop } } ; 3 } = true | select the rows whose cardinalatial order and title record fuzzily matches to bishop . 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, 'cardinalatial order and title_5': 5, 'bishop_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', 'cardinalatial order and title_5': 'cardinalatial order and title', 'bishop_6': 'bishop', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'cardinalatial order and title_5': [0], 'bishop_6': [0], '3_7': [2]} | ['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']] |
2008 issf world cup final ( rifle and pistol ) | https://en.wikipedia.org/wiki/2008_ISSF_World_Cup_Final_%28rifle_and_pistol%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18191407-15.html.csv | count | only two of the shooters were from usa . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'usa', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shooter', 'usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shooter record fuzzily matches to usa .', 'tostr': 'filter_eq { all_rows ; shooter ; usa }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; shooter ; usa } }', 'tointer': 'select the rows whose shooter record fuzzily matches to usa . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; shooter ; usa } } ; 2 } = true', 'tointer': 'select the rows whose shooter record fuzzily matches to usa . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; shooter ; usa } } ; 2 } = true | select the rows whose shooter record fuzzily matches to usa . 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, 'shooter_5': 5, 'usa_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', 'shooter_5': 'shooter', 'usa_6': 'usa', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'shooter_5': [0], 'usa_6': [0], '2_7': [2]} | ['shooter', 'prone', 'stand', 'kneel', 'qual'] | [['sonja pfeilschifter ( ger )', '199', '195', '196', '590'], ['olga dovgun ( kaz )', '200', '196', '193', '589'], ['lioubov galkina ( rus )', '199', '193', '194', '586'], ['yin wen ( chn )', '197', '195', '194', '586'], ['jamie beyerle ( usa )', '198', '188', '194', '580'], ['snježana pejčić ( cro )', '197', '193', '190', '580'], ['eglis yaima cruz ( cub )', '199', '186', '193', '578'], ['morgan hicks ( usa )', '196', '190', '192', '578'], ['du li ( chn )', '199', '189', '190', '578'], ['thanyalak chotphibunsin ( tha )', '197', '185', '194', '576'], ['kristina vestveit ( nor )', '195', '189', '191', '575'], ['adela sykorova ( cze )', '195', '187', '188', '570']] |
the sunday night project | https://en.wikipedia.org/wiki/The_Sunday_Night_Project | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1590967-3.html.csv | ordinal | in the sunday night project , the episode with the 2nd most recent air date was the episode with ross kemp as the host . | {'row': '10', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'air date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; air date ; 2 }'}, 'guest host'], 'result': 'ross kemp', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; air date ; 2 } ; guest host }'}, 'ross kemp'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; air date ; 2 } ; guest host } ; ross kemp } = true', 'tointer': 'select the row whose air date record of all rows is 2nd maximum . the guest host record of this row is ross kemp .'} | eq { hop { nth_argmax { all_rows ; air date ; 2 } ; guest host } ; ross kemp } = true | select the row whose air date record of all rows is 2nd maximum . the guest host record of this row is ross kemp . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'air date_5': 5, '2_6': 6, 'guest host_7': 7, 'ross kemp_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', 'air date_5': 'air date', '2_6': '2', 'guest host_7': 'guest host', 'ross kemp_8': 'ross kemp'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'air date_5': [0], '2_6': [0], 'guest host_7': [1], 'ross kemp_8': [2]} | ['episode number', 'air date', 'guest host', 'musical guest ( song performed )', 'who knows the most about the guest host panelists'] | [['1', '16 june 2006', 'jerry springer', 'orson ( bright idea )', 'zãe lucker and sam brodie'], ['2', '23 june 2006', 'patsy kensit', 'placebo ( infra - red )', 'jeremy edwards and grace adams - short'], ['3', '30 june 2006', 'rob lowe', 'the zutons ( valerie )', 'jennifer ellison and kirsty gallacher'], ['4', '7 july 2006', 'mischa barton', 'dirty pretty things ( deadwood )', 'camille coduri and harry judd'], ['5', '14 july 2006', 'ian wright', 'feeder ( just a day )', 'sally lindsay and lea walker'], ['6', '21 july 2006', 'jade goody', 'razorlight ( in the morning )', 'dominic wood and nikki grahame'], ['7', '28 july 2006', 'justin hawkins', 'kasabian ( empire )', 'holly willoughby and jayne kitt'], ['8', '4 august 2006', 'rupert everett', 'primal scream ( dolls ( sweet rock and roll ) )', 'jennie mcalpine and sarah beeny'], ['9', '11 august 2006', 'carol vorderman', 'the automatic ( recover )', 'gary lucy and susie verrico'], ['10', '18 august 2006', 'ross kemp', 'the feeling ( never be lonely )', 'matt willis and chantelle houghton'], ['11', '25 august 2006', 'cheryl cole , kimberley walsh and sarah harding', 'the fratellis ( chelsea dagger )', 'aisleyne horgan - wallace and glyn wise']] |
fugitive pieces ( film ) | https://en.wikipedia.org/wiki/Fugitive_Pieces_%28film%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17480544-1.html.csv | ordinal | second time the fugitive pieces ( film ) won an award was in 2008 . | {'scope': 'subset', 'row': '3', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'won'}} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nominated / won', 'won'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nominated / won ; won }', 'tointer': 'select the rows whose nominated / won record fuzzily matches to won .'}, 'year', '2'], 'result': '2008', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; nominated / won ; won } ; year ; 2 }', 'tointer': 'select the rows whose nominated / won record fuzzily matches to won . the 2nd minimum year record of these rows is 2008 .'}, '2008'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; nominated / won ; won } ; year ; 2 } ; 2008 } = true', 'tointer': 'select the rows whose nominated / won record fuzzily matches to won . the 2nd minimum year record of these rows is 2008 .'} | eq { nth_min { filter_eq { all_rows ; nominated / won ; won } ; year ; 2 } ; 2008 } = true | select the rows whose nominated / won record fuzzily matches to won . the 2nd minimum year record of these rows is 2008 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'nominated / won_5': 5, 'won_6': 6, 'year_7': 7, '2_8': 8, '2008_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'nominated / won_5': 'nominated / won', 'won_6': 'won', 'year_7': 'year', '2_8': '2', '2008_9': '2008'} | {'eq_2': [3], 'result_3': [], 'nth_min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nominated / won_5': [0], 'won_6': [0], 'year_7': [1], '2_8': [1], '2008_9': [2]} | ['year', 'nominated / won', 'award / category', 'festival / organization', 'role'] | [['2007', 'won', 'best actor', 'rome film festival', 'rade šerbedžija as athos'], ['2008', 'nominated', 'best supporting actor in a motion picture', 'satellite award', 'rade šerbedžija as athos'], ['2008', 'won', 'best film', 'sydney film festival', '-'], ['2008', 'won', 'audience award ( narrative feature )', 'sarasota film festival', '-'], ['2008', 'won', 'jury award', 'newport beach film festival', '-']] |
roman catholic archdiocese of santa fe | https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Santa_Fe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1656555-1.html.csv | comparative | in the roman catholic archdiocese of santa fe , jean baptiste lamy was born 11 years before jean baptiste salpointe . | {'row_1': '1', 'row_2': '2', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'archbishop', 'jean baptiste lamy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste lamy .', 'tostr': 'filter_eq { all_rows ; archbishop ; jean baptiste lamy }'}, 'born'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born }', 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste lamy . take the born record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'archbishop', 'jean baptiste salpointe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste salpointe .', 'tostr': 'filter_eq { all_rows ; archbishop ; jean baptiste salpointe }'}, 'born'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born }', 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste salpointe . take the born record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born } ; hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born } }', 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste lamy . take the born record of this row . select the rows whose archbishop record fuzzily matches to jean baptiste salpointe . take the born record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'archbishop', 'jean baptiste lamy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste lamy .', 'tostr': 'filter_eq { all_rows ; archbishop ; jean baptiste lamy }'}, 'born'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born }', 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste lamy . take the born record of this row .'}, 'october 11 , 1814'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born } ; october 11 , 1814 }', 'tointer': 'the born record of the first row is october 11 , 1814 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'archbishop', 'jean baptiste salpointe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste salpointe .', 'tostr': 'filter_eq { all_rows ; archbishop ; jean baptiste salpointe }'}, 'born'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born }', 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste salpointe . take the born record of this row .'}, 'february 22 , 1825'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born } ; february 22 , 1825 }', 'tointer': 'the born record of the second row is february 22 , 1825 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born } ; october 11 , 1814 } ; eq { hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born } ; february 22 , 1825 } }', 'tointer': 'the born record of the first row is october 11 , 1814 . the born record of the second row is february 22 , 1825 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born } ; hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born } } ; and { eq { hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born } ; october 11 , 1814 } ; eq { hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born } ; february 22 , 1825 } } } = true', 'tointer': 'select the rows whose archbishop record fuzzily matches to jean baptiste lamy . take the born record of this row . select the rows whose archbishop record fuzzily matches to jean baptiste salpointe . take the born record of this row . the first record is less than the second record . the born record of the first row is october 11 , 1814 . the born record of the second row is february 22 , 1825 .'} | and { less { hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born } ; hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born } } ; and { eq { hop { filter_eq { all_rows ; archbishop ; jean baptiste lamy } ; born } ; october 11 , 1814 } ; eq { hop { filter_eq { all_rows ; archbishop ; jean baptiste salpointe } ; born } ; february 22 , 1825 } } } = true | select the rows whose archbishop record fuzzily matches to jean baptiste lamy . take the born record of this row . select the rows whose archbishop record fuzzily matches to jean baptiste salpointe . take the born record of this row . the first record is less than the second record . the born record of the first row is october 11 , 1814 . the born record of the second row is february 22 , 1825 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'archbishop_11': 11, 'jean baptiste lamy_12': 12, 'born_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'archbishop_15': 15, 'jean baptiste salpointe_16': 16, 'born_17': 17, 'and_7': 7, 'str_eq_5': 5, 'october 11 , 1814_18': 18, 'str_eq_6': 6, 'february 22 , 1825_19': 19} | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'archbishop_11': 'archbishop', 'jean baptiste lamy_12': 'jean baptiste lamy', 'born_13': 'born', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'archbishop_15': 'archbishop', 'jean baptiste salpointe_16': 'jean baptiste salpointe', 'born_17': 'born', 'and_7': 'and', 'str_eq_5': 'str_eq', 'october 11 , 1814_18': 'october 11 , 1814', 'str_eq_6': 'str_eq', 'february 22 , 1825_19': 'february 22 , 1825'} | {'and_8': [9], 'result_9': [], 'less_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'archbishop_11': [0], 'jean baptiste lamy_12': [0], 'born_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'archbishop_15': [1], 'jean baptiste salpointe_16': [1], 'born_17': [3], 'and_7': [8], 'str_eq_5': [7], 'october 11 , 1814_18': [5], 'str_eq_6': [7], 'february 22 , 1825_19': [6]} | ['archbishop', 'born', 'ordained priest', 'ordained bishop', 'appointed archbishop', 'vacated throne', 'died'] | [['jean baptiste lamy', 'october 11 , 1814', 'december 1838', 'november 24 , 1850', 'february 12 , 1875', 'august 18 , 1885', 'february 13 , 1888'], ['jean baptiste salpointe', 'february 22 , 1825', 'december 20 , 1851', 'june 20 , 1869', 'august 18 , 1885', 'january 7 , 1894', 'july 15 , 1898'], ['placide louis chapelle', 'august 28 , 1843', 'june 28 , 1866', 'november 1 , 1891', 'january 7 , 1895', 'december 7 , 1898', 'august 8 , 1906'], ['peter bourgade', 'october 17 , 1846', 'november 30 , 1869', 'may 1 , 1886', 'january 7 , 1899', 'may 17 , 1907', 'may 17 , 1907'], ['john baptist pitaval', 'february 10 , 1858', 'december 24 , 1881', 'july 25 , 1902', 'january 3 , 1909', 'july 29 , 1918', 'may 23 , 1928'], ['albert daeger', 'march 5 , 1872', 'july 25 , 1896', 'may 7 , 1919', 'march 10 , 1919', 'december 2 , 1932', 'december 2 , 1932'], ['rudolph gerken', 'march 7 , 1887', 'july 10 , 1917', 'april 26 , 1927', 'june 2 , 1933', 'march 2 , 1943', 'march 2 , 1943'], ['edwin byrne', 'august 9 , 1891', 'may 22 , 1915', 'november 30 , 1925', 'june 12 , 1943', 'july 26 , 1963', 'july 26 , 1963'], ['james peter davis', 'june 9 , 1904', 'may 19 , 1929', 'october 6 , 1943', 'january 3 , 1964', 'june 1 , 1974', 'march 4 , 1988'], ['robert fortune sanchez', 'march 20 , 1934', 'december 20 , 1959', 'july 25 , 1974', 'june 1 , 1974', 'april 6 , 1993', 'january 20 , 2012'], ['michael jarboe sheehan', 'july 9 , 1939', 'july 12 , 1964', 'june 17 , 1983', 'august 16 , 1993', 'still serving', 'still living']] |
jovan kirovski | https://en.wikipedia.org/wiki/Jovan_Kirovski | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1115680-1.html.csv | unique | the goal scored on february 12 , 2000 was jovan kirovski 's only goal in the 2000 concacaf gold cup . | {'scope': 'all', 'row': '7', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': '2000 concacaf gold cup', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2000 concacaf gold cup'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2000 concacaf gold cup .', 'tostr': 'filter_eq { all_rows ; competition ; 2000 concacaf gold cup }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; competition ; 2000 concacaf gold cup } }', 'tointer': 'select the rows whose competition record fuzzily matches to 2000 concacaf gold cup . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2000 concacaf gold cup'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2000 concacaf gold cup .', 'tostr': 'filter_eq { all_rows ; competition ; 2000 concacaf gold cup }'}, 'date'], 'result': 'february 12 , 2000', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; 2000 concacaf gold cup } ; date }'}, 'february 12 , 2000'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; competition ; 2000 concacaf gold cup } ; date } ; february 12 , 2000 }', 'tointer': 'the date record of this unqiue row is february 12 , 2000 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; competition ; 2000 concacaf gold cup } } ; eq { hop { filter_eq { all_rows ; competition ; 2000 concacaf gold cup } ; date } ; february 12 , 2000 } } = true', 'tointer': 'select the rows whose competition record fuzzily matches to 2000 concacaf gold cup . there is only one such row in the table . the date record of this unqiue row is february 12 , 2000 .'} | and { only { filter_eq { all_rows ; competition ; 2000 concacaf gold cup } } ; eq { hop { filter_eq { all_rows ; competition ; 2000 concacaf gold cup } ; date } ; february 12 , 2000 } } = true | select the rows whose competition record fuzzily matches to 2000 concacaf gold cup . there is only one such row in the table . the date record of this unqiue row is february 12 , 2000 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, '2000 concacaf gold cup_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'february 12 , 2000_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'competition_7': 'competition', '2000 concacaf gold cup_8': '2000 concacaf gold cup', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'february 12 , 2000_10': 'february 12 , 2000'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'competition_7': [0], '2000 concacaf gold cup_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'february 12 , 2000_10': [3]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', 'november 22 , 1994', '1 - 0', '3 - 0', 'friendly'], ['2', 'december 11 , 1994', '1 - 1', '1 - 1', 'friendly'], ['3', 'january 21 , 1996', '3 - 0', '3 - 0', '1996 concacaf gold cup'], ['4', 'june 17 , 1997', '2 - 0', '2 - 1', 'friendly'], ['5', 'february 6 , 1999', '1 - 0', '3 - 0', 'friendly'], ['6', 'july 24 , 1999', '2 - 0', '2 - 1', 'friendly'], ['7', 'february 12 , 2000', '1 - 0', '3 - 0', '2000 concacaf gold cup'], ['8', 'march 29 , 2003', '1 - 0', '2 - 0', 'friendly'], ['9', 'june 8 , 2003', '2 - 1', '2 - 1', 'friendly']] |
1999 in film | https://en.wikipedia.org/wiki/1999_in_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-169577-1.html.csv | majority | every one of 1999 's top 10 biggest box office films grossed over $ 300,000,000 worldwide . | {'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '300,000,000', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '10'}} | {'func': 'all_greater', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'rank', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; rank ; 10 }', 'tointer': 'select the rows whose rank record is less than or equal to 10 .'}, 'worldwide gross', '300,000,000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose rank record is less than or equal to 10 . for the worldwide gross records of these rows , all of them are greater than 300,000,000 .', 'tostr': 'all_greater { filter_less_eq { all_rows ; rank ; 10 } ; worldwide gross ; 300,000,000 } = true'} | all_greater { filter_less_eq { all_rows ; rank ; 10 } ; worldwide gross ; 300,000,000 } = true | select the rows whose rank record is less than or equal to 10 . for the worldwide gross records of these rows , all of them are greater than 300,000,000 . | 2 | 2 | {'all_greater_1': 1, 'result_2': 2, 'filter_less_eq_0': 0, 'all_rows_3': 3, 'rank_4': 4, '10_5': 5, 'worldwide gross_6': 6, '300,000,000_7': 7} | {'all_greater_1': 'all_greater', 'result_2': 'true', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_3': 'all_rows', 'rank_4': 'rank', '10_5': '10', 'worldwide gross_6': 'worldwide gross', '300,000,000_7': '300,000,000'} | {'all_greater_1': [2], 'result_2': [], 'filter_less_eq_0': [1], 'all_rows_3': [0], 'rank_4': [0], '10_5': [0], 'worldwide gross_6': [1], '300,000,000_7': [1]} | ['rank', 'title', 'studio', 'director ( s )', 'worldwide gross'] | [['1', 'star wars episode i : the phantom menace', '20th century fox / lucasfilm', 'george lucas', '924317558'], ['2', 'the sixth sense', 'hollywood pictures / blinding edge', 'm night shyamalan', '672806292'], ['3', 'toy story 2', 'disney / pixar', 'john lasseter and lee unkrich', '485015179'], ['4', 'the matrix', 'warner bros', 'andy & larry wachowski', '460379930'], ['5', 'tarzan', 'walt disney pictures', 'kevin lima and chris buck', '448191819'], ['6', 'the mummy', 'universal studios / amblin entertainment', 'stephen sommers', '415933406'], ['7', 'notting hill', 'universal studios', 'roger michell', '363889678'], ['8', 'the world is not enough', 'mgm', 'michael apted', '361832400'], ['9', 'american beauty', 'dreamworks', 'sam mendes', '356296601'], ['10', 'austin powers : the spy who shagged me', 'new line cinema', 'jay roach', '312016858'], ['11', 'runaway bride', 'paramount / touchstone', 'garry marshall', '309457509'], ['12', 'stuart little', 'columbia pictures', 'rob minkoff', '300135367'], ['13', 'the green mile', 'warner bros', 'frank darabont', '290701374'], ['14', 'the blair witch project', 'haxan films', 'eduardo sã ¡ nchez and daniel myrick', '248639099'], ['15', 'american pie', 'universal studios', 'paul weitz', '235483004'], ['16', 'big daddy', 'columbia pictures', 'dennis dugan', '234801895'], ['17', 'wild wild west', 'warner bros', 'barry sonnenfeld', '222105681'], ['18', 'entrapment', '20th century fox', 'jon amiel', '212404396'], ['19', 'end of days', 'universal studios', 'peter hyams', '211989043'], ['20', 'sleepy hollow', 'paramount pictures', 'tim burton', '206071502']] |
westmorland county , new brunswick | https://en.wikipedia.org/wiki/Westmorland_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-176529-2.html.csv | aggregation | the total population of all the parishes in westmorland county , new brunswick is 20423 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '20423', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'population'], 'result': '20423', 'ind': 0, 'tostr': 'sum { all_rows ; population }'}, '20423'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; population } ; 20423 } = true', 'tointer': 'the sum of the population record of all rows is 20423 .'} | round_eq { sum { all_rows ; population } ; 20423 } = true | the sum of the population record of all rows is 20423 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'population_4': 4, '20423_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'population_4': 'population', '20423_5': '20423'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'population_4': [0], '20423_5': [1]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['moncton', 'parish', '582.20', '8861', '427 of 5008'], ['shediac', 'parish', '238.47', '4801', '709 of 5008'], ['salisbury', 'parish', '873.55', '3425', '909 of 5008'], ['botsford', 'parish', '303.75', '1203', '1827 of 5008'], ['sackville', 'parish', '578.28', '1174', '1857 of 5008'], ['westmorland', 'parish', '173.48', '959', '2105 of 5008']] |
1993 washington redskins season | https://en.wikipedia.org/wiki/1993_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14610099-1.html.csv | aggregation | the average crowd attendance in the was 1993 washington redskins season 56169 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '56169', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '56169', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '56169'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 56169 } = true', 'tointer': 'the average of the attendance record of all rows is 56169 .'} | round_eq { avg { all_rows ; attendance } ; 56169 } = true | the average of the attendance record of all rows is 56169 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '56169_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '56169_5': '56169'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '56169_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 6 , 1993', 'dallas cowboys', 'w 35 - 16', '56345'], ['2', 'september 12 , 1993', 'phoenix cardinals', 'l 17 - 10', '53525'], ['3', 'september 19 , 1993', 'philadelphia eagles', 'l 34 - 31', '65435'], ['5', 'october 4 , 1993', 'miami dolphins', 'l 17 - 10', '68568'], ['6', 'october 10 , 1993', 'new york giants', 'l 41 - 7', '53715'], ['7', 'october 17 , 1993', 'phoenix cardinals', 'l 36 - 6', '48143'], ['9', 'november 1 , 1993', 'buffalo bills', 'l 24 - 10', '79106'], ['10', 'november 7 , 1993', 'indianapolis colts', 'w 30 - 24', '50523'], ['11', 'november 14 , 1993', 'new york giants', 'l 20 - 6', '76606'], ['12', 'november 21 , 1993', 'los angeles rams', 'l 10 - 6', '45546'], ['13', 'november 28 , 1993', 'philadelphia eagles', 'l 17 - 14', '46663'], ['14', 'december 5 , 1993', 'tampa bay buccaneers', 'w 23 - 17', '49035'], ['15', 'december 11 , 1993', 'new york jets', 'l 3 - 0', '47970'], ['16', 'december 19 , 1993', 'atlanta falcons', 'w 30 - 17', '50192'], ['17', 'december 26 , 1993', 'dallas cowboys', 'l 38 - 3', '64497'], ['18', 'december 31 , 1993', 'minnesota vikings', 'l 14 - 9', '42836']] |
list of intel atom microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Atom_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16729930-18.html.csv | majority | in the list of intel atom microprocessors all who has gpu frequency 320 mhz have a release price of more than 60 usd . | {'scope': 'subset', 'col': '13', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '60', 'subset': {'col': '4', 'criterion': 'equal', 'value': '320 mhz'}} | {'func': 'all_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gpu frequency', '320 mhz'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; gpu frequency ; 320 mhz }', 'tointer': 'select the rows whose gpu frequency record fuzzily matches to 320 mhz .'}, 'release price ( usd )', '60'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose gpu frequency record fuzzily matches to 320 mhz . for the release price ( usd ) records of these rows , all of them are greater than 60 .', 'tostr': 'all_greater { filter_eq { all_rows ; gpu frequency ; 320 mhz } ; release price ( usd ) ; 60 } = true'} | all_greater { filter_eq { all_rows ; gpu frequency ; 320 mhz } ; release price ( usd ) ; 60 } = true | select the rows whose gpu frequency record fuzzily matches to 320 mhz . for the release price ( usd ) records of these rows , all of them are greater than 60 . | 2 | 2 | {'all_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'gpu frequency_4': 4, '320 mhz_5': 5, 'release price ( usd )_6': 6, '60_7': 7} | {'all_greater_1': 'all_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'gpu frequency_4': 'gpu frequency', '320 mhz_5': '320 mhz', 'release price ( usd )_6': 'release price ( usd )', '60_7': '60'} | {'all_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'gpu frequency_4': [0], '320 mhz_5': [0], 'release price ( usd )_6': [1], '60_7': [1]} | ['model number', 'sspec number', 'frequency', 'gpu frequency', 'l2 cache', 'i / o bus', 'memory', 'voltage', 'tdp', 'socket', 'release date', 'part number ( s )', 'release price ( usd )'] | [['atom e625c', 'slh9z ( b0 )', '600 mhz', '320 mhz', '512 kb', 'pcie', '1 ddr2 - 800', '0.8 - 1.175 v', '2.7 w', 'fc - bga 1466', 'november 22 , 2010', 'cy80632007227ab', '61'], ['atome625ct', 'slh9k ( b0 )', '600 mhz', '320 mhz', '512 kb', 'pcie', '1 ddr2 - 800', '0.8 - 1.175 v', '2.7 w', 'fc - bga 1466', 'november 22 , 2010', 'cy80632007227aa', '65'], ['atom e645c', 'slh9y ( b0 )', '1 ghz', '320 mhz', '512 kb', 'pcie', '1 ddr2 - 800', '0.8 - 1.175 v', '3.6 w', 'fc - bga 1466', 'november 22 , 2010', 'cy80632007221ab', '72'], ['atome645ct', 'slh9j ( b0 )', '1 ghz', '320 mhz', '512 kb', 'pcie', '1 ddr2 - 800', '0.8 - 1.175 v', '3.6 w', 'fc - bga 1466', 'november 22 , 2010', 'cy80632007221aa', '79'], ['atom e665c', 'slh9x ( b0 )', '1.3 ghz', '400 mhz', '512 kb', 'pcie', '1 ddr2 - 800', '0.8 - 1.175 v', '3.6 w', 'fc - bga 1466', 'november 22 , 2010', 'cy80632007224ab', '97']] |
thomas wheatley ( locomotive engineer ) | https://en.wikipedia.org/wiki/Thomas_Wheatley_%28locomotive_engineer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10668727-1.html.csv | comparative | more 251 nbr class locomotives designed by thomas wheatley were made than 229 nbr class locomotives . | {'row_1': '7', 'row_2': '14', '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', 'nbr class', '251'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nbr class record fuzzily matches to 251 .', 'tostr': 'filter_eq { all_rows ; nbr class ; 251 }'}, 'total'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nbr class ; 251 } ; total }', 'tointer': 'select the rows whose nbr class record fuzzily matches to 251 . take the total record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nbr class', '229'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nbr class record fuzzily matches to 229 .', 'tostr': 'filter_eq { all_rows ; nbr class ; 229 }'}, 'total'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nbr class ; 229 } ; total }', 'tointer': 'select the rows whose nbr class record fuzzily matches to 229 . take the total record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; nbr class ; 251 } ; total } ; hop { filter_eq { all_rows ; nbr class ; 229 } ; total } } = true', 'tointer': 'select the rows whose nbr class record fuzzily matches to 251 . take the total record of this row . select the rows whose nbr class record fuzzily matches to 229 . take the total record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; nbr class ; 251 } ; total } ; hop { filter_eq { all_rows ; nbr class ; 229 } ; total } } = true | select the rows whose nbr class record fuzzily matches to 251 . take the total record of this row . select the rows whose nbr class record fuzzily matches to 229 . take the total 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, 'nbr class_7': 7, '251_8': 8, 'total_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nbr class_11': 11, '229_12': 12, 'total_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', 'nbr class_7': 'nbr class', '251_8': '251', 'total_9': 'total', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nbr class_11': 'nbr class', '229_12': '229', 'total_13': 'total'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nbr class_7': [0], '251_8': [0], 'total_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nbr class_11': [1], '229_12': [1], 'total_13': [3]} | ['nbr class', 'type', 'introduced', 'driving wheel', 'total', 'extinct'] | [['141', '2 - 4 - 0', '1869', 'ft6in ( mm )', '2', '1915'], ['38', '2 - 4 - 0', '1869', 'ft0in ( mm )', '1', '1912'], ['418', '2 - 4 - 0', '1873', 'ft0in ( mm )', '8', '1927'], ['40', '2 - 4 - 0', '1873', 'ft0in ( mm )', '2', '1903'], ['224', '4 - 4 - 0', '1871', 'ft6in ( mm )', '2', '1919'], ['420', '4 - 4 - 0', '1873', 'ft6in ( mm )', '4', '1918'], ['251', '0 - 6 - 0', '1867', 'ft3in ( mm )', '38', '1924'], ['56', '0 - 6 - 0', '1868', 'ft0in ( mm )', '8', '1914'], ['17', '0 - 6 - 0', '1869', 'ft6in ( mm )', '1', '1914'], ['396', '0 - 6 - 0', '1867', 'ft0in ( mm )', '88', '1937'], ['293', '0 - 6 - 0', '1872', 'ft0in ( mm )', '1', '1907'], ['357', '0 - 4 - 0', '1868', 'ft3in ( mm )', '2', '1925'], ['226', '0 - 6 - 0st', '1870', 'ft0in ( mm )', '2', '1924'], ['229', '0 - 6 - 0st', '1871', 'ft0in ( mm )', '15', '1924'], ['112', '0 - 6 - 0st', '1870', 'ft6in ( mm )', '3', '1910'], ['282', '0 - 6 - 0st', '1866', 'ft1in ( mm )', '3', '1921'], ['130', '0 - 6 - 0st', '1870', 'ft3in ( mm )', '10', '1924'], ['32', '0 - 6 - 0st', '1874', 'ft6in ( mm )', '6', '1907'], ['18', '0 - 4 - 0st', '1872', 'ft0in ( mm )', '2', '1906']] |
2008 - 09 rugby - bundesliga | https://en.wikipedia.org/wiki/2008%E2%80%9309_Rugby-Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20989972-8.html.csv | superlative | hamburger rc was the club in the 2008 - 09 rugby - bundesliga that had the highest number of points against . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points against'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points against }'}, 'club'], 'result': 'hamburger rc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points against } ; club }'}, 'hamburger rc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points against } ; club } ; hamburger rc } = true', 'tointer': 'select the row whose points against record of all rows is maximum . the club record of this row is hamburger rc .'} | eq { hop { argmax { all_rows ; points against } ; club } ; hamburger rc } = true | select the row whose points against record of all rows is maximum . the club record of this row is hamburger rc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points against_5': 5, 'club_6': 6, 'hamburger rc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points against_5': 'points against', 'club_6': 'club', 'hamburger rc_7': 'hamburger rc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points against_5': [0], 'club_6': [1], 'hamburger rc_7': [2]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'difference', 'points'] | [['1', 'dsv 78 / 08 ricklingen', '18', '18', '0', '0', '1138', '135', '1003', '87'], ['2', 'tsv victoria linden', '18', '15', '0', '3', '720', '246', '474', '72'], ['3', 'usv potsdam', '18', '14', '0', '4', '804', '271', '533', '69'], ['4', 'fc st pauli rugby', '18', '11', '0', '7', '632', '311', '321', '56'], ['5', 'sg sv odin / vfr dãhren', '18', '11', '0', '7', '509', '328', '181', '52'], ['6', 'ru hohen neuendorf', '18', '9', '0', '9', '452', '401', '51', '45'], ['7', 'sc germania list', '18', '4', '0', '14', '250', '813', '- 563', '20'], ['8', 'hamburger rc', '18', '4', '0', '14', '235', '891', '- 656', '19'], ['9', 'berliner sv 92 rugby', '18', '3', '1', '14', '201', '857', '- 656', '15']] |
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 | superlative | the game played on friday , 1 august had the largest crowd size . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', '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', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'date'], 'result': 'friday , 1 august', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; date }'}, 'friday , 1 august'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; date } ; friday , 1 august } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the date record of this row is friday , 1 august .'} | eq { hop { argmax { all_rows ; crowd } ; date } ; friday , 1 august } = true | select the row whose crowd record of all rows is maximum . the date record of this row is friday , 1 august . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'date_6': 6, 'friday , 1 august_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', 'date_6': 'date', 'friday , 1 august_7': 'friday , 1 august'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'date_6': [1], 'friday , 1 august_7': [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']] |
zina garrison | https://en.wikipedia.org/wiki/Zina_Garrison | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1028356-3.html.csv | count | zina garrison played three of her championships on a grass surface . | {'scope': 'all', 'criterion': 'equal', 'value': 'grass', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to grass .', 'tostr': 'filter_eq { all_rows ; surface ; grass }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; grass } }', 'tointer': 'select the rows whose surface record fuzzily matches to grass . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; grass } } ; 3 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to grass . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; surface ; grass } } ; 3 } = true | select the rows whose surface record fuzzily matches to grass . 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, 'surface_5': 5, 'grass_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', 'surface_5': 'surface', 'grass_6': 'grass', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'grass_6': [0], '3_7': [2]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents', 'score'] | [['winner', '1987', 'australian open', 'grass', 'sherwood stewart', 'anne hobbs andrew castle', '3 - 6 , 7 - 6 ( 5 ) , 6 - 3'], ['winner', '1988', 'wimbledon', 'grass', 'sherwood stewart', 'gretchen magers kelly jones', '6 - 1 , 7 - 6 ( 3 )'], ['runner - up', '1989', 'australian open', 'hard', 'sherwood stewart', 'jana novotná jim pugh', '6 - 3 , 6 - 4'], ['runner - up', '1990', 'australian open', 'hard', 'jim pugh', 'natasha zvereva andrew castle', '4 - 6 , 6 - 2 , 6 - 3'], ['winner', '1990', 'wimbledon ( 2 )', 'grass', 'rick leach', 'elizabeth smylie john fitzgerald', '7 - 5 , 6 - 2']] |
lgbt in islam | https://en.wikipedia.org/wiki/LGBT_in_Islam | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15471-1.html.csv | unique | of these countries , only uzbekistan penalizes male homosexuality , but not female homosexuality . | {'scope': 'all', 'row': '9', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'male only', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'laws against homosexuality', 'male only'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laws against homosexuality record fuzzily matches to male only .', 'tostr': 'filter_eq { all_rows ; laws against homosexuality ; male only }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; laws against homosexuality ; male only } }', 'tointer': 'select the rows whose laws against homosexuality record fuzzily matches to male only . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'laws against homosexuality', 'male only'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laws against homosexuality record fuzzily matches to male only .', 'tostr': 'filter_eq { all_rows ; laws against homosexuality ; male only }'}, 'country'], 'result': 'uzbekistan', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; laws against homosexuality ; male only } ; country }'}, 'uzbekistan'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; laws against homosexuality ; male only } ; country } ; uzbekistan }', 'tointer': 'the country record of this unqiue row is uzbekistan .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; laws against homosexuality ; male only } } ; eq { hop { filter_eq { all_rows ; laws against homosexuality ; male only } ; country } ; uzbekistan } } = true', 'tointer': 'select the rows whose laws against homosexuality record fuzzily matches to male only . there is only one such row in the table . the country record of this unqiue row is uzbekistan .'} | and { only { filter_eq { all_rows ; laws against homosexuality ; male only } } ; eq { hop { filter_eq { all_rows ; laws against homosexuality ; male only } ; country } ; uzbekistan } } = true | select the rows whose laws against homosexuality record fuzzily matches to male only . there is only one such row in the table . the country record of this unqiue row is uzbekistan . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'laws against homosexuality_7': 7, 'male only_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'uzbekistan_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'laws against homosexuality_7': 'laws against homosexuality', 'male only_8': 'male only', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'uzbekistan_10': 'uzbekistan'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'laws against homosexuality_7': [0], 'male only_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'uzbekistan_10': [3]} | ['country', 'laws against homosexuality', 'penalty', 'same - sex unions', 'laws against discrimination'] | [['afghanistan', 'yes', 'death', 'no', 'no'], ['egypt', 'no', 'prison', 'no', 'no'], ['indonesia', 'no', '-', '-', 'no'], ['iraq', 'no', '-', '-', 'no'], ['malaysia', 'yes', 'fine to 20 years', '-', 'no'], ['nigeria', 'yes', '5 - 14 years / death', '-', 'no'], ['pakistan', 'yes', '2 years to life', '-', 'no'], ['turkey', 'no', '-', '-', 'no'], ['uzbekistan', 'male only', 'fine to 3 years', '-', 'no']] |
1969 italian grand prix | https://en.wikipedia.org/wiki/1969_Italian_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122409-1.html.csv | majority | the majority of drivers completed at least 60 laps in the 1969 italian grand prix . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '60', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'laps', '60'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are greater than 60 .', 'tostr': 'most_greater { all_rows ; laps ; 60 } = true'} | most_greater { all_rows ; laps ; 60 } = true | for the laps records of all rows , most of them are greater than 60 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '60_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '60_4': '60'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '60_4': [0]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['jackie stewart', 'matra - ford', '68', '1:39:11.26', '3'], ['jochen rindt', 'lotus - ford', '68', '+ 0.08', '1'], ['jean - pierre beltoise', 'matra - ford', '68', '+ 0.17', '6'], ['bruce mclaren', 'mclaren - ford', '68', '+ 0.19', '5'], ['piers courage', 'brabham - ford', '68', '+ 33.44', '4'], ['pedro rodrã\xadguez', 'ferrari', '66', '+ 2 laps', '12'], ['denny hulme', 'mclaren - ford', '66', '+ 2 laps', '2'], ['jo siffert', 'lotus - ford', '64', 'engine', '8'], ['graham hill', 'lotus - ford', '63', 'halfshaft', '9'], ['jacky ickx', 'brabham - ford', '61', 'out of fuel', '15'], ['john surtees', 'brm', '60', 'not classified', '10'], ['jackie oliver', 'brm', '48', 'oil pressure', '11'], ['silvio moser', 'brabham - ford', '9', 'fuel leak', '13'], ['jack brabham', 'brabham - ford', '6', 'oil leak', '7'], ['john miles', 'lotus - ford', '3', 'engine', '14']] |
2007 - 08 new orleans hornets season | https://en.wikipedia.org/wiki/2007%E2%80%9308_New_Orleans_Hornets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11963536-11.html.csv | aggregation | in the 2007-08 new orleans hornet 's season , the high points scorers scored an average of 29.5 points for the first six games in may . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '29.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'high points'], 'result': '29.5', 'ind': 0, 'tostr': 'avg { all_rows ; high points }'}, '29.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; high points } ; 29.5 } = true', 'tointer': 'the average of the high points record of all rows is 29.5 .'} | round_eq { avg { all_rows ; high points } ; 29.5 } = true | the average of the high points record of all rows is 29.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'high points_4': 4, '29.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'high points_4': 'high points', '29.5_5': '29.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'high points_4': [0], '29.5_5': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 3', 'san antonio', '101 - 82', 'west ( 30 )', 'chandler ( 15 )', 'paul ( 13 )', 'new orleans arena 18040', '1 - 0'], ['2', 'may 5', 'san antonio', '102 - 84', 'paul ( 30 )', 'chandler ( 11 )', 'paul ( 12 )', 'new orleans arena 17927', '2 - 0'], ['3', 'may 8', 'san antonio', '99 - 110', 'paul ( 35 )', 'west ( 12 )', 'paul ( 9 )', 'at & t center 18797', '2 - 1'], ['4', 'may 11', 'san antonio', '80 - 100', 'paul ( 23 )', 'armstrong , paul ( 6 )', 'paul ( 5 )', 'at & t center 18797', '2 - 2'], ['5', 'may 13', 'san antonio', '101 - 79', 'west ( 38 )', 'west ( 14 )', 'paul ( 14 )', 'new orleans arena 18246', '3 - 2'], ['6', 'may 15', 'san antonio', '80 - 99', 'paul ( 21 )', 'five - way tie ( 6 )', 'paul ( 8 )', 'at & t center 18797', '3 - 3']] |
ed elisian | https://en.wikipedia.org/wiki/Ed_Elisian | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252070-3.html.csv | unique | 1954 was the only year that ed elisian drove with a stevens type chassis . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'stevens', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'stevens'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to stevens .', 'tostr': 'filter_eq { all_rows ; chassis ; stevens }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; chassis ; stevens } }', 'tointer': 'select the rows whose chassis record fuzzily matches to stevens . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'stevens'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to stevens .', 'tostr': 'filter_eq { all_rows ; chassis ; stevens }'}, 'year'], 'result': '1954', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; chassis ; stevens } ; year }'}, '1954'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; chassis ; stevens } ; year } ; 1954 }', 'tointer': 'the year record of this unqiue row is 1954 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; chassis ; stevens } } ; eq { hop { filter_eq { all_rows ; chassis ; stevens } ; year } ; 1954 } } = true', 'tointer': 'select the rows whose chassis record fuzzily matches to stevens . there is only one such row in the table . the year record of this unqiue row is 1954 .'} | and { only { filter_eq { all_rows ; chassis ; stevens } } ; eq { hop { filter_eq { all_rows ; chassis ; stevens } ; year } ; 1954 } } = true | select the rows whose chassis record fuzzily matches to stevens . there is only one such row in the table . the year record of this unqiue row is 1954 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'chassis_7': 7, 'stevens_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1954_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', 'stevens_8': 'stevens', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1954_10': '1954'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'chassis_7': [0], 'stevens_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1954_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1954', 'ha chapman', 'stevens', 'offenhauser l4', '0'], ['1955', 'westwood gauge / wales', 'kurtis kraft 4000', 'offenhauser l4', '0'], ['1956', 'hoyt machine / fred sommer', 'kurtis kraft 500c', 'offenhauser l4', '0'], ['1957', 'mcnamara / kalamazoo sports', 'kurtis kraft 500d', 'offenhauser l4', '0'], ['1958', 'john zink', 'watson indy roadster', 'offenhauser l4', '0']] |
rowing at the 2008 summer olympics - men 's coxless pair | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_coxless_pair | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662689-6.html.csv | aggregation | the average time for rowing at the 2008 summer olympics - men 's coxless pair was 6:43.99 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '6:43.99', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '6:43.99', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '6:43.99'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 6:43.99 } = true', 'tointer': 'the average of the time record of all rows is 6:43.99 .'} | round_eq { avg { all_rows ; time } ; 6:43.99 } = true | the average of the time record of all rows is 6:43.99 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '6:43.99_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '6:43.99_5': '6:43.99'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '6:43.99_5': [1]} | ['rank', 'athlete', 'country', 'time', 'notes'] | [['1', 'dave calder , scott frandsen', 'canada', '6:34.02', 'fa'], ['2', 'nathan twaddle , george bridgewater', 'new zealand', '6:36.05', 'fa'], ['3', 'shaun keeling , ramon di clemente', 'south africa', '6:37.18', 'fa'], ['4', 'jakub makovička , václav chalupa', 'czech republic', '6:37.88', 'fb'], ['5', 'erwan peron , laurent cadot', 'france', '6:44.29', 'fb'], ['6', 'siniša skelin , nikša skelin', 'croatia', '7:14.50', 'fb']] |
united states house of representatives elections , 1966 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1966 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341843-15.html.csv | count | four of the 1966 house of representative elections in indiana feature re-elected candidates . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 're - elected', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; result ; re - elected }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re - elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re - elected } } ; 4 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 4 } = true | select the rows whose result record fuzzily matches to re - elected . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're - elected_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're - elected_6': 're - elected', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '4_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['indiana 1', 'ray j madden', 'democratic', '1942', 're - elected', 'ray j madden ( d ) 58.3 % albert harrigan ( r ) 41.7 %'], ['indiana 3', 'john brademas', 'democratic', '1958', 're - elected', 'john brademas ( d ) 55.8 % robert a ehlers ( r ) 44.2 %'], ['indiana 4', 'e ross adair', 'republican', '1950', 're - elected', 'e ross adair ( r ) 63.5 % j byron hayes ( d ) 36.5 %'], ['indiana 5', 'j edward roush', 'democratic', '1958', 're - elected', 'j edward roush ( d ) 51.1 % kenneth bowman ( r ) 48.9 %'], ['indiana 7', 'none ( district created )', 'none ( district created )', 'none ( district created )', 'new seat republican gain', 'john t myers ( r ) 54.3 % elden c tipton ( d ) 45.7 %']] |
bmw m67 | https://en.wikipedia.org/wiki/BMW_M67 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1285530-1.html.csv | majority | the majority of engines for the bmw m67 are 3.9 liter displacement engines . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '3.9', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'displacement', '3.9'], 'result': True, 'ind': 0, 'tointer': 'for the displacement records of all rows , most of them are equal to 3.9 .', 'tostr': 'most_eq { all_rows ; displacement ; 3.9 } = true'} | most_eq { all_rows ; displacement ; 3.9 } = true | for the displacement records of all rows , most of them are equal to 3.9 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'displacement_3': 3, '3.9_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'displacement_3': 'displacement', '3.9_4': '3.9'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'displacement_3': [0], '3.9_4': [0]} | ['engine', 'displacement', 'power', 'torque', 'redline', 'year'] | [['m67d40', '3.9 l ( 3901cc / 238in cubic )', '175 kw ( 234 hp ) 4000', '560 n m ( 413 lb ft ) 2000 rpm', '4700', '1999'], ['m67d40', '3.9 l ( 3901cc / 238in cubic )', '180 kw ( 241hp ) 4000', '560nm ( 413lb ft ) 1750 - 2500', '4700', '2000'], ['m67tud40', '3.9 l ( 3901cc / 238in cubic )', '190 kw ( 254hp ) 4000', '600nm ( 442lb ft ) 1900 - 2500', '4700', '2002'], ['m67d44', '4.4 l ( 4423cc / 269in cubic )', '220 kw ( 299hp ) 4000', '700n m ( 516lb ft ) 1750 - 2500', '4700', '2005'], ['m67d44', '4.4 l ( 4423cc / 269in cubic )', '242 kw ( 329hp ) 3800', '750nm ( 552lb ft ) 1900 - 2500', '4700', '2006']] |
lnb pro a | https://en.wikipedia.org/wiki/LNB_Pro_A | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1810878-1.html.csv | majority | all of the years were after the year 2000 . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '2000', 'subset': None} | {'func': 'all_greater', 'args': ['all_rows', 'year', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , all of them are greater than 2000 .', 'tostr': 'all_greater { all_rows ; year ; 2000 } = true'} | all_greater { all_rows ; year ; 2000 } = true | for the year records of all rows , all of them are greater than 2000 . | 1 | 1 | {'all_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '2000_4': 4} | {'all_greater_0': 'all_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '2000_4': '2000'} | {'all_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '2000_4': [0]} | ['year', 'champion', 'finalist', 'score', 'place'] | [['2005', 'gravelines - dunkerque', 'strasbourg', '88 - 71', 'gravelines'], ['2006', 'dijon', 'le mans', '70 - 69', 'le mans'], ['2007', 'pau lacq orthez', 'roanne', '79 - 74', 'pau'], ['2008', 'nancy', 'asvel', '76 - 73', 'nancy'], ['2009', 'asvel', 'le mans', '76 - 54', 'angers'], ['2010', 'cholet', 'orléans', '85 - 79', 'cholet'], ['2011', 'nancy', 'chalon - sur - saône', '89 - 83', 'nancy'], ['2012', 'limoges', 'chalon - sur - saône', '78 - 76', 'paris']] |
arizona wildcats men 's basketball | https://en.wikipedia.org/wiki/Arizona_Wildcats_men%27s_basketball | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10609116-6.html.csv | count | sean elliot was the tournament mvp in two different years . | {'scope': 'all', 'criterion': 'equal', 'value': 'sean elliott , arizona', 'result': '2', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament mvp', 'sean elliott , arizona'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament mvp record fuzzily matches to sean elliott , arizona .', 'tostr': 'filter_eq { all_rows ; tournament mvp ; sean elliott , arizona }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tournament mvp ; sean elliott , arizona } }', 'tointer': 'select the rows whose tournament mvp record fuzzily matches to sean elliott , arizona . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tournament mvp ; sean elliott , arizona } } ; 2 } = true', 'tointer': 'select the rows whose tournament mvp record fuzzily matches to sean elliott , arizona . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; tournament mvp ; sean elliott , arizona } } ; 2 } = true | select the rows whose tournament mvp record fuzzily matches to sean elliott , arizona . 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, 'tournament mvp_5': 5, 'sean elliott , arizona_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', 'tournament mvp_5': 'tournament mvp', 'sean elliott , arizona_6': 'sean elliott , arizona', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tournament mvp_5': [0], 'sean elliott , arizona_6': [0], '2_7': [2]} | ['year', 'champion', 'score', 'runner - up', 'arena', 'city', 'tournament mvp'] | [['1988', 'arizona', '93 - 67', 'oregon state', 'mckale center', 'tucson , arizona', 'sean elliott , arizona'], ['1989', 'arizona', '73 - 51', 'stanford', 'great western forum', 'inglewood , california', 'sean elliott , arizona'], ['1990', 'arizona', '94 - 78', 'ucla', 'university activity center', 'tempe , arizona', 'jud buechler , arizona'], ['2002', 'arizona', '81 - 71', 'usc', 'staples center', 'los angeles , california', 'luke walton , arizona'], ['2005', 'washington', '81 - 72', 'arizona', 'staples center', 'los angeles , california', 'salim stoudamire , arizona'], ['2011', 'washington', '77 - 75 ( ot )', 'arizona', 'staples center', 'los angeles , california', 'isaiah thomas , washington'], ['2012', 'colorado', '53 - 51', 'arizona', 'staples center', 'los angeles , california', 'carlon brown , colorado']] |
list of kent twenty20 cricket records | https://en.wikipedia.org/wiki/List_of_Kent_Twenty20_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12643669-8.html.csv | aggregation | kent twenty20 country club cricket players scored an average of 87.7 runs . | {'scope': 'all', 'col': '1', 'type': 'average', 'result': '87.7', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'runs'], 'result': '87.7', 'ind': 0, 'tostr': 'avg { all_rows ; runs }'}, '87.7'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; runs } ; 87.7 } = true', 'tointer': 'the average of the runs record of all rows is 87.7 .'} | round_eq { avg { all_rows ; runs } ; 87.7 } = true | the average of the runs record of all rows is 87.7 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'runs_4': 4, '87.7_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'runs_4': 'runs', '87.7_5': '87.7'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'runs_4': [0], '87.7_5': [1]} | ['runs', 'player', 'opponent', 'venue', 'season'] | [['112', 'andrew symonds', 'v middlesex', 'mote park , maidstone', '2004'], ['96', 'andrew symonds', 'v hampshire', 'county ground , beckenham', '2003'], ['91', 'joe denly', 'v essex', 'county ground , beckenham', '2008'], ['77', 'darren stevens', 'v somerset', 'edgbaston cricket ground , birmingham', '2009'], ['75', 'martin van jaarsveld', 'v leicestershire', 'grace road , leicester', '2006'], ['75', 'martin van jaarsveld', 'v middlesex', "lord 's cricket ground , london", '2009']] |
zorro ( musical ) | https://en.wikipedia.org/wiki/Zorro_%28musical%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17143308-1.html.csv | majority | all award of the zorro ( musical ) is the laurence olivier award . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'laurence olivier award', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'award', 'laurence olivier award'], 'result': True, 'ind': 0, 'tointer': 'for the award records of all rows , all of them fuzzily match to laurence olivier award .', 'tostr': 'all_eq { all_rows ; award ; laurence olivier award } = true'} | all_eq { all_rows ; award ; laurence olivier award } = true | for the award records of all rows , all of them fuzzily match to laurence olivier award . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'award_3': 3, 'laurence olivier award_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'award_3': 'award', 'laurence olivier award_4': 'laurence olivier award'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'award_3': [0], 'laurence olivier award_4': [0]} | ['year', 'award', 'category', 'nominee', 'result'] | [['2009', 'laurence olivier award', 'best new musical', 'best new musical', 'nominated'], ['2009', 'laurence olivier award', 'best actor in a musical', 'matt rawle', 'nominated'], ['2009', 'laurence olivier award', 'best actress in a musical', 'emma williams', 'nominated'], ['2009', 'laurence olivier award', 'best performance in a supporting role in a musical', 'lesli margherita', 'won'], ['2009', 'laurence olivier award', 'best theatre choreographer', 'rafael amargo', 'nominated']] |
ranked lists of chilean regions | https://en.wikipedia.org/wiki/Ranked_lists_of_Chilean_regions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25042332-22.html.csv | aggregation | the average chilean secondary education ( 14-17 years ) attainment is 70.95 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '70.95', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'secondary ( 14 - 17 years )'], 'result': '70.95', 'ind': 0, 'tostr': 'avg { all_rows ; secondary ( 14 - 17 years ) }'}, '70.95'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; secondary ( 14 - 17 years ) } ; 70.95 } = true', 'tointer': 'the average of the secondary ( 14 - 17 years ) record of all rows is 70.95 .'} | round_eq { avg { all_rows ; secondary ( 14 - 17 years ) } ; 70.95 } = true | the average of the secondary ( 14 - 17 years ) record of all rows is 70.95 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'secondary (14 - 17 years)_4': 4, '70.95_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'secondary (14 - 17 years)_4': 'secondary ( 14 - 17 years )', '70.95_5': '70.95'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'secondary (14 - 17 years)_4': [0], '70.95_5': [1]} | ['region', 'preschool ( 0 - 5 years )', 'primary ( 6 - 13 years )', 'secondary ( 14 - 17 years )', 'tertiary ( 18 - 24 years )'] | [['arica and parinacota', '42.92', '91.17', '76.65', '38.67'], ['tarapacá', '47.51', '94.52', '70.82', '28.16'], ['antofagasta', '38.13', '91.90', '70.78', '28.26'], ['atacama', '38.14', '94.13', '73.93', '23.01'], ['coquimbo', '47.43', '93.00', '68.95', '33.89'], ['valparaíso', '50.23', '91.37', '71.63', '42.96'], ['santiago', '43.15', '92.38', '72.91', '35.03'], ["o'higgins", '41.89', '95.41', '63.00', '28.60'], ['maule', '43.38', '93.10', '67.49', '26.31'], ['biobío', '40.76', '93.45', '71.83', '31.62'], ['araucanía', '45.49', '93.40', '73.25', '29.55'], ['los ríos', '38.49', '94.18', '69.83', '33.88'], ['los lagos', '40.42', '92.88', '71.43', '25.78'], ['aisén', '52.28', '94.39', '69.30', '22.42'], ['magallanes', '51.16', '94.40', '72.50', '43.87']] |
1996 ansett australia cup | https://en.wikipedia.org/wiki/1996_Ansett_Australia_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16388091-1.html.csv | ordinal | the carlton 's home team game recorded the 2nd highest crowd participation in the 1996 ansett australia cup competition . | {'row': '7', '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', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'home team'], 'result': 'carlton', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; home team }'}, 'carlton'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; carlton } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is carlton .'} | eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; carlton } = true | select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is carlton . | 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, 'home team_7': 7, 'carlton_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', 'home team_7': 'home team', 'carlton_8': 'carlton'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'home team_7': [1], 'carlton_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'time'] | [['adelaide', '18.16 ( 124 )', 'melbourne', '10.5 ( 65 )', 'football park', '24143', 'friday 23 february 1996', '8:00 pm'], ['hawthorn', '9.19 ( 73 )', 'st kilda', '19.13 ( 127 )', 'waverley park', '16061', 'saturday , 23 february 1996', '8:00 pm'], ['fremantle', '7.15 ( 57 )', 'west coast', '10.11 ( 71 )', 'marrara stadium', '9078', 'sunday , 25 february 1996', '7:05 pm'], ['fitzroy', '12.15 ( 87 )', 'footscray', '16.15 ( 111 )', 'waverley park', '4818', 'monday , 26 february 1996', '8:00 pm'], ['collingwood', '14.10 ( 94 )', 'richmond', '8.14 ( 62 )', 'waverley park', '13307', 'wednesday 25 february 1996', '8:00 pm'], ['sydney', '20.8 ( 128 )', 'north melbourne', '22.18 ( 150 )', 'bruce stadium', '9405', 'sunday , 2 march 1996', '2:00 pm'], ['carlton', '14.12 ( 96 )', 'essendon', '8.14 ( 62 )', 'waverley park', '23837', 'saturday , 2 march 1996', '8:00 pm'], ['brisbane', '14 . 25 ( 109 )', 'geelong', '9.9 ( 63 )', 'the gabba', '18325', 'monday , 4 march 1996', '7:00 pm']] |
margalita chakhnashvili | https://en.wikipedia.org/wiki/Margalita_Chakhnashvili | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12428755-2.html.csv | unique | the westende tournament was the only tournament that took place on a hard surface . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard .', 'tostr': 'filter_eq { all_rows ; surface ; hard }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; hard } }', 'tointer': 'select the rows whose surface record fuzzily matches to hard . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard .', 'tostr': 'filter_eq { all_rows ; surface ; hard }'}, 'tournament'], 'result': 'westende', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; hard } ; tournament }'}, 'westende'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; hard } ; tournament } ; westende }', 'tointer': 'the tournament record of this unqiue row is westende .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; hard } } ; eq { hop { filter_eq { all_rows ; surface ; hard } ; tournament } ; westende } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to hard . there is only one such row in the table . the tournament record of this unqiue row is westende .'} | and { only { filter_eq { all_rows ; surface ; hard } } ; eq { hop { filter_eq { all_rows ; surface ; hard } ; tournament } ; westende } } = true | select the rows whose surface record fuzzily matches to hard . there is only one such row in the table . the tournament record of this unqiue row is westende . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'hard_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'westende_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'hard_8': 'hard', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'westende_10': 'westende'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'hard_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'westende_10': [3]} | ['date', 'tournament', 'surface', 'tier', 'partner', 'opponents in the final', 'score'] | [['may 8 , 2006', 'antalya - belek', 'clay', 'itf 10k', 'ipek şenoğlu', 'claire de gubernatis alexandra dulgheru', '6 - 4 , 6 - 3'], ['july 3 , 2006', 'mont de marson', 'clay', 'itf 25k', 'ioana raluca olaru', 'akgul amanmuradova nina bratchikova', '7 - 5 , 1 - 6 , 6 - 1'], ['august 21 , 2009', 'westende', 'hard', 'itf 25k', 'vasilisa davydova', 'emilie bacquet jasmin wöhr', '6 - 2 , 7 - 5'], ['june 12 , 2011', 'zlin', 'clay', 'itf 50k', 'yuliya beygelzimer', 'réka - luca jani katalin marosi', '3 - 6 , 6 - 1 ,'], ['june 3 , 2012', 'grado', 'clay', 'itf 25k', 'ekaterine gorgodze', 'claudia giovine anastasia grymalska', '7 - 6 ( 7 - 2 ) , 7 - 6 ( 7 - 1 )']] |
welsh league | https://en.wikipedia.org/wiki/Welsh_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28201906-1.html.csv | majority | the majority of clubs in the welsh league lost 5 matches . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '5', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'lost', '5'], 'result': True, 'ind': 0, 'tointer': 'for the lost records of all rows , most of them are equal to 5 .', 'tostr': 'most_eq { all_rows ; lost ; 5 } = true'} | most_eq { all_rows ; lost ; 5 } = true | for the lost records of all rows , most of them are equal to 5 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'lost_3': 3, '5_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'lost_3': 'lost', '5_4': '5'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'lost_3': [0], '5_4': [0]} | ['position', 'club', 'played', 'won', 'drawn', 'lost', 'pts for', 'pts agst', 'points', 'percent'] | [['1', 'ebbw vale rlfc', '8', '7', '0', '1', '135', '21', '14', '87.50 %'], ['2', 'mid - rhondda rlfc', '9', '6', '0', '3', '59', '45', '12', '66.67 %'], ['3', 'merthyr tydfil rlfc', '10', '5', '0', '5', '101', '70', '10', '50.00 %'], ['4', 'treherbert rlfc', '9', '3', '1', '5', '64', '105', '7', '38.89 %'], ['5', 'aberdare rlfc', '8', '3', '0', '5', '64', '108', '4', '37.50 %']] |
mike sserumaga | https://en.wikipedia.org/wiki/Mike_Sserumaga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16660943-1.html.csv | unique | the 11 november 2011 game was the only one played in marrakech . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'marrakech', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'marrakech'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to marrakech .', 'tostr': 'filter_eq { all_rows ; venue ; marrakech }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; marrakech } }', 'tointer': 'select the rows whose venue record fuzzily matches to marrakech . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'marrakech'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to marrakech .', 'tostr': 'filter_eq { all_rows ; venue ; marrakech }'}, 'date'], 'result': '11 november 2011', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; marrakech } ; date }'}, '11 november 2011'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; marrakech } ; date } ; 11 november 2011 }', 'tointer': 'the date record of this unqiue row is 11 november 2011 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; marrakech } } ; eq { hop { filter_eq { all_rows ; venue ; marrakech } ; date } ; 11 november 2011 } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to marrakech . there is only one such row in the table . the date record of this unqiue row is 11 november 2011 .'} | and { only { filter_eq { all_rows ; venue ; marrakech } } ; eq { hop { filter_eq { all_rows ; venue ; marrakech } ; date } ; 11 november 2011 } } = true | select the rows whose venue record fuzzily matches to marrakech . there is only one such row in the table . the date record of this unqiue row is 11 november 2011 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'marrakech_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '11 november 2011_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'marrakech_8': 'marrakech', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '11 november 2011_10': '11 november 2011'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'marrakech_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '11 november 2011_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['29 november 2009', 'mumias sports complex , mumias', '2 - 0', '2 - 0', '2009 cecafa cup'], ['11 august 2010', 'national stadium , kampala', '1 - 1', '1 - 1', 'friendly'], ['7 november 2010', 'may 22 stadium , aden', '1 - 2', '2 - 2', 'friendly'], ['8 december 2010', 'benjamin mkapa national stadium , dar es salaam', '1 - 0', '2 - 2', '2010 cecafa cup'], ['11 november 2011', 'stade de marrakech , marrakech', '1 - 0', '1 - 0', '2011 lg cup'], ['25 november 2011', 'benjamin mkapa national stadium , dar es salaam', '2 - 1', '2 - 1', '2011 cecafa cup'], ['29 february 2012', 'stade municipal , pointe - noire', '1 - 1', '1 - 3', '2013 afcon qualification']] |
list of new jersey transit stations | https://en.wikipedia.org/wiki/List_of_New_Jersey_Transit_stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1051326-3.html.csv | count | six of the transit stations are located in essex county . | {'scope': 'all', 'criterion': 'equal', 'value': 'essex , nj', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'essex , nj'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to essex , nj .', 'tostr': 'filter_eq { all_rows ; county ; essex , nj }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; county ; essex , nj } }', 'tointer': 'select the rows whose county record fuzzily matches to essex , nj . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; county ; essex , nj } } ; 6 } = true', 'tointer': 'select the rows whose county record fuzzily matches to essex , nj . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; county ; essex , nj } } ; 6 } = true | select the rows whose county record fuzzily matches to essex , nj . 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, 'county_5': 5, 'essex , nj_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', 'county_5': 'county', 'essex , nj_6': 'essex , nj', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'county_5': [0], 'essex , nj_6': [0], '6_7': [2]} | ['station', 'municipality', 'county', 'former railroad', 'closed'] | [['ampere', 'east orange', 'essex , nj', 'lackawanna', '1991'], ['arlington', 'kearney', 'hudson , nj', 'erie', '2002'], ['benson street', 'glen ridge', 'essex , nj', 'erie', '2002'], ['fairmount avenue', 'hackensack', 'bergen , nj', 'erie', '1983'], ['finderne', 'finderne', 'somerset , nj', 'jersey central', '2006'], ['great notch', 'great notch', 'passaic , nj', 'erie', '2010'], ['grove street', 'east orange', 'essex , nj', 'lackawanna', '1991'], ['harmon cove', 'secaucus', 'hudson , nj', 'erie', '2003'], ['harrison', 'harrison', 'hudson , nj', 'lackawanna', '1984'], ['north newark', 'newark', 'essex , nj', 'lackawanna', '1984'], ['north rahway', 'rahway', 'fairfield , nj', 'pennsylvania', '1993'], ['roseville avenue', 'newark', 'essex , nj', 'lackawanna', '1984'], ['rowe street', 'bloomfield township', 'essex , nj', 'erie', '2002']] |
fabienne suter | https://en.wikipedia.org/wiki/Fabienne_Suter | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16403980-1.html.csv | aggregation | fabienne suter 's average overall standing in ski races during her career was 38 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '38', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'overall'], 'result': '38', 'ind': 0, 'tostr': 'avg { all_rows ; overall }'}, '38'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; overall } ; 38 } = true', 'tointer': 'the average of the overall record of all rows is 38 .'} | round_eq { avg { all_rows ; overall } ; 38 } = true | the average of the overall record of all rows is 38 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'overall_4': 4, '38_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'overall_4': 'overall', '38_5': '38'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'overall_4': [0], '38_5': [1]} | ['season', 'overall', 'slalom', 'giant slalom', 'super g', 'downhill', 'combined'] | [['2003', '110', '-', '48', '-', '-', '-'], ['2007', '95', '-', '46', '36', '-', '-'], ['2008', '21', '-', '35', '3', '35', '-'], ['2009', '7', '-', '20', '3', '8', '6'], ['2010', '7', '-', '27', '4', '7', '6'], ['2011', '18', '-', '31', '12', '15', '13'], ['2012', '18', '-', '36', '5', '16', '-'], ['2013', '28', '-', '44', '7', '25', '-']] |
gymnastics at the 2008 summer olympics - men 's parallel bars | https://en.wikipedia.org/wiki/Gymnastics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_parallel_bars | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662020-2.html.csv | superlative | li xiaopeng had the most total in gymnastics at the 2008 summer olympics - men 's parallel bars . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'gymnast'], 'result': 'li xiaopeng ( chn )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; gymnast }'}, 'li xiaopeng ( chn )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; gymnast } ; li xiaopeng ( chn ) } = true', 'tointer': 'select the row whose total record of all rows is maximum . the gymnast record of this row is li xiaopeng ( chn ) .'} | eq { hop { argmax { all_rows ; total } ; gymnast } ; li xiaopeng ( chn ) } = true | select the row whose total record of all rows is maximum . the gymnast record of this row is li xiaopeng ( chn ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'gymnast_6': 6, 'li xiaopeng ( chn )_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', 'gymnast_6': 'gymnast', 'li xiaopeng ( chn )_7': 'li xiaopeng ( chn )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'gymnast_6': [1], 'li xiaopeng ( chn )_7': [2]} | ['position', 'gymnast', 'a score', 'b score', 'total'] | [['1st', 'li xiaopeng ( chn )', '6.900', '9.525', '16.425'], ['2nd', 'nikolay kryukov ( rus )', '6.800', '9.375', '16.175'], ['3rd', 'anton fokin ( uzb )', '6.800', '9.350', '16.150'], ['4th', 'yoo won - chul ( kor )', '7.000', '9.150', '16.150'], ['5th', 'mitja petkovšek ( slo )', '6.600', '9.525', '16.125'], ['6th', 'yang tae - young ( kor )', '7.000', '9.100', '16.100'], ['7th', 'huang xu ( chn )', '7.000', '9.075', '16.075'], ['8th', 'fabian hambüchen ( ger )', '6.900', '9.150', '16.050']] |
1982 senior pga tour | https://en.wikipedia.org/wiki/1982_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622896-2.html.csv | ordinal | don january had the 2nd highest earnings during the 1982 senior pga tour . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'earnings', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; earnings ; 2 }'}, 'player'], 'result': 'don january', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; earnings ; 2 } ; player }'}, 'don january'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; earnings ; 2 } ; player } ; don january } = true', 'tointer': 'select the row whose earnings record of all rows is 2nd maximum . the player record of this row is don january .'} | eq { hop { nth_argmax { all_rows ; earnings ; 2 } ; player } ; don january } = true | select the row whose earnings record of all rows is 2nd maximum . the player record of this row is don january . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'earnings_5': 5, '2_6': 6, 'player_7': 7, 'don january_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', 'earnings_5': 'earnings', '2_6': '2', 'player_7': 'player', 'don january_8': 'don january'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'earnings_5': [0], '2_6': [0], 'player_7': [1], 'don january_8': [2]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'miller barber', 'united states', '106890', '10', '3'], ['2', 'don january', 'united states', '99508', '8', '2'], ['3', 'bob goalby', 'united states', '94540', '10', '1'], ['4', 'arnold palmer', 'united states', '73848', '7', '2'], ['5', 'billy casper', 'united states', '71979', '8', '2']] |
primary schools in dacorum | https://en.wikipedia.org/wiki/Primary_schools_in_Dacorum | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15089329-3.html.csv | aggregation | the total combined intake of primary schools in dacorum is 505 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '505', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'intake'], 'result': '505', 'ind': 0, 'tostr': 'sum { all_rows ; intake }'}, '505'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; intake } ; 505 } = true', 'tointer': 'the sum of the intake record of all rows is 505 .'} | round_eq { sum { all_rows ; intake } ; 505 } = true | the sum of the intake record of all rows is 505 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'intake_4': 4, '505_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'intake_4': 'intake', '505_5': '505'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'intake_4': [0], '505_5': [1]} | ['name', 'faith', 'type', 'intake', 'dcsf number', 'ofsted number'] | [['boxmoor', '-', 'primary', '30', '2041', '117107'], ['chaulden', '-', 'infants', '50', '2193', '117202'], ['chaulden', '-', 'junior', '60', '2185', '117198'], ['gade valley', '-', 'jmi', '30', '2274', '117249'], ['galley hill', '-', 'primary', '45', '3990', '135224'], ['heath lane', '-', 'nursery', '80', '1009', '117070'], ['micklem', '-', 'primary', '30', '2243', '117231'], ['pixies hill', '-', 'primary', '30', '2293', '117256'], ['st cuthbert mayne', 'rc', 'junior', '60', '3386', '117468'], ["st rose 's", 'rc', 'infants', '60', '3409', '117484'], ['south hill', '-', 'primary', '30', '2047', '117110']] |
1997 in paraguayan football | https://en.wikipedia.org/wiki/1997_in_Paraguayan_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18703133-1.html.csv | count | in the 1997 in paraguayan football , among the teams that had 5 wins , 2 of them had 4 losses each . | {'scope': 'subset', 'criterion': 'equal', 'value': '4', 'result': '2', 'col': '6', 'subset': {'col': '4', 'criterion': 'equal', 'value': '5'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '5'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; wins ; 5 }', 'tointer': 'select the rows whose wins record is equal to 5 .'}, 'losses', '4'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose wins record is equal to 5 . among these rows , select the rows whose losses record is equal to 4 .', 'tostr': 'filter_eq { filter_eq { all_rows ; wins ; 5 } ; losses ; 4 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; wins ; 5 } ; losses ; 4 } }', 'tointer': 'select the rows whose wins record is equal to 5 . among these rows , select the rows whose losses record is equal to 4 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; wins ; 5 } ; losses ; 4 } } ; 2 } = true', 'tointer': 'select the rows whose wins record is equal to 5 . among these rows , select the rows whose losses record is equal to 4 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; wins ; 5 } ; losses ; 4 } } ; 2 } = true | select the rows whose wins record is equal to 5 . among these rows , select the rows whose losses record is equal to 4 . 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, 'wins_6': 6, '5_7': 7, 'losses_8': 8, '4_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', 'wins_6': 'wins', '5_7': '5', 'losses_8': 'losses', '4_9': '4', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'wins_6': [0], '5_7': [0], 'losses_8': [1], '4_9': [1], '2_10': [3]} | ['position', 'team', 'played', 'wins', 'draws pk wins / pk losses', 'losses', 'scored', 'conceded', 'points'] | [['1', 'olimpia', '12', '7', '4 / 0', '1', '22', '7', '29'], ['2', 'cerro porteño', '12', '7', '1 / 0', '4', '23', '15', '23'], ['3', 'sol de américa', '12', '6', '0 / 2', '4', '11', '8', '20'], ['4', 'libertad', '12', '5', '0 / 5', '2', '17', '13', '20'], ['5', 'san lorenzo', '12', '5', '1 / 2', '4', '15', '17', '19'], ['6', 'guaraní', '12', '5', '1 / 2', '4', '18', '15', '19'], ['7', 'presidente hayes', '12', '4', '3 / 0', '5', '13', '17', '18'], ['8', 'sportivo luqueño', '12', '5', '0 / 1', '6', '15', '22', '16'], ['9', 'nacional', '12', '3', '2 / 3', '4', '16', '21', '16'], ['10', 'sport colombia', '12', '2', '3 / 3', '4', '17', '15', '15'], ['11', 'tembetary', '12', '4', '1 / 1', '6', '14', '16', '15'], ['12', 'atl colegiales', '12', '3', '2 / 0', '7', '9', '15', '13'], ['13', 'cerro corá', '12', '2', '2 / 1', '7', '15', '24', '11']] |
list of palestinian submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Palestinian_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26555737-1.html.csv | unique | paradise now was the only palestinian submission that had a result of being a nominee . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'nominee', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'nominee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to nominee .', 'tostr': 'filter_eq { all_rows ; result ; nominee }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; nominee } }', 'tointer': 'select the rows whose result record fuzzily matches to nominee . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'nominee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to nominee .', 'tostr': 'filter_eq { all_rows ; result ; nominee }'}, 'english title'], 'result': 'paradise now', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; nominee } ; english title }'}, 'paradise now'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; nominee } ; english title } ; paradise now }', 'tointer': 'the english title record of this unqiue row is paradise now .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; nominee } } ; eq { hop { filter_eq { all_rows ; result ; nominee } ; english title } ; paradise now } } = true', 'tointer': 'select the rows whose result record fuzzily matches to nominee . there is only one such row in the table . the english title record of this unqiue row is paradise now .'} | and { only { filter_eq { all_rows ; result ; nominee } } ; eq { hop { filter_eq { all_rows ; result ; nominee } ; english title } ; paradise now } } = true | select the rows whose result record fuzzily matches to nominee . there is only one such row in the table . the english title record of this unqiue row is paradise now . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'nominee_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'english title_9': 9, 'paradise now_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'nominee_8': 'nominee', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'english title_9': 'english title', 'paradise now_10': 'paradise now'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'nominee_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'english title_9': [2], 'paradise now_10': [3]} | ['year ( ceremony )', 'english title', 'arabic title', 'director', 'result'] | [['2003 ( 76th )', 'divine intervention', 'يد إلهية', 'elia suleiman', 'not nominated'], ['2004 ( 77th )', 'the olive harvest', 'موسم زيتون', 'hanna elias', 'not nominated'], ['2005 ( 78th )', 'paradise now', 'الجنّة الآن', 'hany abu - assad', 'nominee'], ['2008 ( 81st )', 'salt of this sea', 'ملح هذا البحر', 'annemarie jacir', 'not nominated'], ['2012 ( 85th )', 'when i saw you', 'لما شفتك', 'annemarie jacir', 'not nominated']] |
list of supernanny episodes | https://en.wikipedia.org/wiki/List_of_Supernanny_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-16.html.csv | comparative | the swift family episode was originally aired before the the potter family episode . | {'row_1': '3', 'row_2': '10', 'col': '5', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'family / families', 'the swift family'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose family / families record fuzzily matches to the swift family .', 'tostr': 'filter_eq { all_rows ; family / families ; the swift family }'}, 'original air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; family / families ; the swift family } ; original air date }', 'tointer': 'select the rows whose family / families record fuzzily matches to the swift family . take the original air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'family / families', 'the potter family'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose family / families record fuzzily matches to the potter family .', 'tostr': 'filter_eq { all_rows ; family / families ; the potter family }'}, 'original air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; family / families ; the potter family } ; original air date }', 'tointer': 'select the rows whose family / families record fuzzily matches to the potter family . take the original air date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; family / families ; the swift family } ; original air date } ; hop { filter_eq { all_rows ; family / families ; the potter family } ; original air date } } = true', 'tointer': 'select the rows whose family / families record fuzzily matches to the swift family . take the original air date record of this row . select the rows whose family / families record fuzzily matches to the potter family . take the original air date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; family / families ; the swift family } ; original air date } ; hop { filter_eq { all_rows ; family / families ; the potter family } ; original air date } } = true | select the rows whose family / families record fuzzily matches to the swift family . take the original air date record of this row . select the rows whose family / families record fuzzily matches to the potter family . take the original air 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, 'family / families_7': 7, 'the swift family_8': 8, 'original air date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'family / families_11': 11, 'the potter family_12': 12, 'original air 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', 'family / families_7': 'family / families', 'the swift family_8': 'the swift family', 'original air date_9': 'original air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'family / families_11': 'family / families', 'the potter family_12': 'the potter family', 'original air date_13': 'original air date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'family / families_7': [0], 'the swift family_8': [0], 'original air date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'family / families_11': [1], 'the potter family_12': [1], 'original air date_13': [3]} | ['no in series', 'no in season', 'family / families', 'location ( s )', 'original air date'] | [['us94', '1', 'the atkinson family', 'glen ellyn , il', '5 november 2010'], ['us95', '2', 'the peterfreund family', 'chandler , az', '12 november 2010'], ['us96', '3', 'the swift family', 'sacramento , ca', '19 november 2010'], ['us97', '4', 'the youngs family', 'whidbey island , washington', '3 december 2010'], ['us98', '5', 'the van acker family', 'oak view , ca', '10 december 2010'], ['us99', '6', 'the fernandez family', 'kissimmee , fl', '17 december 2010'], ['us100', '7', 'the george family', 'san antonio , tx', '7 january 2011'], ['us101', '8', 'the miller family', 'phoenix , az', '14 january 2011'], ['us102', '9', 'the colombo family', 'melbourne , fl', '21 january 2011'], ['us103', '10', 'the potter family', 'rochester , ny', '4 february 2011'], ['us104', '11', 'the merrill family', 'camp pendleton , ca', '18 february 2011'], ['us105', '12', 'the demott family', 'bayville , nj', '25 february 2011'], ['us106', '13', 'the froebrich family', 'fort mill , sc', '4 march 2011'], ['us107', '14', 'the federico family', 'las vegas , nv', '11 march 2011']] |
i 'm a celebrity ... get me out of here ! ( uk tv series ) | https://en.wikipedia.org/wiki/I%27m_a_Celebrity...Get_Me_Out_of_Here%21_%28UK_TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14345690-4.html.csv | superlative | of the people that starred on the uk tv series i ’m a celebrity ... get me out of here ! and left on the 16th day , the latest finishing place was 3 . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'day 16'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'exited', 'day 16'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; exited ; day 16 }', 'tointer': 'select the rows whose exited record fuzzily matches to day 16 .'}, 'finished'], 'result': '3rd', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; exited ; day 16 } ; finished }', 'tointer': 'select the rows whose exited record fuzzily matches to day 16 . the maximum finished record of these rows is 3rd .'}, '3rd'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; exited ; day 16 } ; finished } ; 3rd } = true', 'tointer': 'select the rows whose exited record fuzzily matches to day 16 . the maximum finished record of these rows is 3rd .'} | eq { max { filter_eq { all_rows ; exited ; day 16 } ; finished } ; 3rd } = true | select the rows whose exited record fuzzily matches to day 16 . the maximum finished record of these rows is 3rd . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'exited_5': 5, 'day 16_6': 6, 'finished_7': 7, '3rd_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'exited_5': 'exited', 'day 16_6': 'day 16', 'finished_7': 'finished', '3rd_8': '3rd'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'exited_5': [0], 'day 16_6': [0], 'finished_7': [1], '3rd_8': [2]} | ['celebrity', 'famous for', 'entered', 'exited', 'finished'] | [['kerry katona', 'singer in atomic kitten', 'day 1', 'day 16', '1st'], ['jennie bond', 'former royal correspondent for the bbc', 'day 1', 'day 16', '2nd'], ['peter andre', 'pop singer', 'day 1', 'day 16', '3rd'], ['lord brocket', 'aristocrat', 'day 1', 'day 15', '4th'], ['katie price ( first appearance )', 'page 3 model', 'day 1', 'day 14', '5th'], ['alex best', 'second wife of footballer george best', 'day 1', 'day 13', '6th'], ['neil ruddock', 'ex - footballer', 'day 1', 'day 11', '7th'], ['john lydon', 'sex pistols & public image ltd frontman', 'day 1', 'day 11', '8th'], ['diane modahl', 'athlete', 'day 1', 'day 10', '9th'], ['mike read', 'radio dj', 'day 1', 'day 9', '10th']] |
1979 - 80 philadelphia flyers season | https://en.wikipedia.org/wiki/1979%E2%80%9380_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208862-4.html.csv | superlative | in the 1979 - 80 philadelphia flyers season , the game with the highest attendance was on december 16th . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'december 16', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'december 16'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; december 16 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is december 16 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; december 16 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is december 16 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'december 16_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'december 16_7': 'december 16'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'december 16_7': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 1', 'philadelphia', '4 - 4', 'toronto', 'myre', '16485', '17 - 1 - 4'], ['december 2', 'detroit', '4 - 4', 'philadelphia', 'peeters', '17077', '17 - 1 - 5'], ['december 4', 'boston', '2 - 2', 'philadelphia', 'myre', '17077', '17 - 1 - 6'], ['december 6', 'los angeles', '4 - 9', 'philadelphia', 'peeters', '17077', '18 - 1 - 6'], ['december 9', 'chicago', '4 - 4', 'philadelphia', 'myre', '17077', '18 - 1 - 7'], ['december 13', 'quebec', '4 - 6', 'philadelphia', 'peeters', '17077', '19 - 1 - 7'], ['december 15', 'buffalo', '2 - 3', 'philadelphia', 'peeters', '17077', '20 - 1 - 7'], ['december 16', 'philadelphia', '1 - 1', 'ny rangers', 'myre', '17404', '20 - 1 - 8'], ['december 20', 'pittsburgh', '1 - 1', 'philadelphia', 'peeters', '17077', '20 - 1 - 9'], ['december 22', 'philadelphia', '5 - 2', 'boston', 'myre', '14673', '21 - 1 - 9'], ['december 23', 'hartford', '2 - 4', 'philadelphia', 'peeters', '17077', '22 - 1 - 9'], ['december 26', 'philadelphia', '4 - 4', 'hartford', 'myre', '7627', '22 - 1 - 10'], ['december 28', 'philadelphia', '5 - 3', 'winnipeg', 'peeters', '16038', '23 - 1 - 10'], ['december 29', 'philadelphia', '3 - 2', 'colorado', 'myre', '16452', '24 - 1 - 10']] |
list of festivals at donington park | https://en.wikipedia.org/wiki/List_of_Festivals_at_Donington_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10311801-3.html.csv | comparative | the rock and blues festival had more bands than a day at the races . | {'row_1': '1', 'row_2': '2', 'col': '6', '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', 'event', 'rock & blues festival'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to rock & blues festival .', 'tostr': 'filter_eq { all_rows ; event ; rock & blues festival }'}, 'acts'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; event ; rock & blues festival } ; acts }', 'tointer': 'select the rows whose event record fuzzily matches to rock & blues festival . take the acts record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'a day at the races'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose event record fuzzily matches to a day at the races .', 'tostr': 'filter_eq { all_rows ; event ; a day at the races }'}, 'acts'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; event ; a day at the races } ; acts }', 'tointer': 'select the rows whose event record fuzzily matches to a day at the races . take the acts record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; event ; rock & blues festival } ; acts } ; hop { filter_eq { all_rows ; event ; a day at the races } ; acts } } = true', 'tointer': 'select the rows whose event record fuzzily matches to rock & blues festival . take the acts record of this row . select the rows whose event record fuzzily matches to a day at the races . take the acts record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; event ; rock & blues festival } ; acts } ; hop { filter_eq { all_rows ; event ; a day at the races } ; acts } } = true | select the rows whose event record fuzzily matches to rock & blues festival . take the acts record of this row . select the rows whose event record fuzzily matches to a day at the races . take the acts 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, 'event_7': 7, 'rock & blues festival_8': 8, 'acts_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'event_11': 11, 'a day at the races_12': 12, 'acts_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', 'event_7': 'event', 'rock & blues festival_8': 'rock & blues festival', 'acts_9': 'acts', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'event_11': 'event', 'a day at the races_12': 'a day at the races', 'acts_13': 'acts'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'event_7': [0], 'rock & blues festival_8': [0], 'acts_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'event_11': [1], 'a day at the races_12': [1], 'acts_13': [3]} | ['year', 'date', 'event', 'days', 'stages', 'acts'] | [['2001', '23 june', 'rock & blues festival', '2 days', '1 stage', '6 bands'], ['2001', '14 july', 'a day at the races', '1 day', '1 stage', '5 bands'], ['2002', '25 may', 'ozzfest 2002', '1 day', '2 stages', '24 bands'], ['2003', '31 may - 1 june', 'download festival ft deconstruction festival', '2 days', '2 stages', '57 bands'], ['2004', '5 - 6 june', 'download festival', '2 days', '3 stages', '73 bands'], ['2005', '10 - 12 june', 'download festival with ozzfest', '3 days', '3 stages', '99 bands'], ['2006', '9 - 11 june', 'download festival', '3 days', '4 stages', '106 bands'], ['2007', '8 - 10 june', 'download festival', '3 days', '3 stages', '101 bands'], ['2008', '13 - 15 june', 'download festival', '3 days', '3 stages', '100 bands'], ['2009', '14 - 16 june', 'download festival', '3 days', '4 stages', '132 bands']] |
2008 - 09 golden state warriors season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Golden_State_Warriors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17080868-9.html.csv | majority | the majority of games during the 2008 - 09 golden state warriors season were played at oracle arena . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'oracle arena', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location attendance', 'oracle arena'], 'result': True, 'ind': 0, 'tointer': 'for the location attendance records of all rows , most of them fuzzily match to oracle arena .', 'tostr': 'most_eq { all_rows ; location attendance ; oracle arena } = true'} | most_eq { all_rows ; location attendance ; oracle arena } = true | for the location attendance records of all rows , most of them fuzzily match to oracle arena . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location attendance_3': 3, 'oracle arena_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location attendance_3': 'location attendance', 'oracle arena_4': 'oracle arena'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location attendance_3': [0], 'oracle arena_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 1', 'utah', 'l 104 - 112 ( ot )', 'corey maggette ( 27 )', 'andris biedriņš ( 12 )', 'c j watson ( 5 )', 'oracle arena 18347', '20 - 39'], ['60', 'march 3', 'minnesota', 'w 118 - 94 ( ot )', 'stephen jackson ( 23 )', 'andris biedriņš ( 13 )', 'stephen jackson ( 6 )', 'target center 14780', '21 - 39'], ['61', 'march 4', 'chicago', 'l 88 - 110 ( ot )', 'stephen jackson ( 19 )', 'anthony randolph ( 10 )', 'stephen jackson ( 6 )', 'united center 20108', '21 - 40'], ['62', 'march 6', 'detroit', 'l 91 - 108 ( ot )', 'jamal crawford ( 25 )', 'jermareo davidson ( 10 )', 'jamal crawford ( 8 )', 'the palace of auburn hills 22076', '21 - 41'], ['63', 'march 7', 'milwaukee', 'l 120 - 127 ( ot )', 'jamal crawford ( 32 )', 'anthony randolph ( 8 )', 'stephen jackson ( 11 )', 'bradley center 15569', '21 - 42'], ['64', 'march 11', 'new jersey', 'w 116 - 112 ( ot )', 'stephen jackson ( 29 )', 'andris biedriņš ( 13 )', 'stephen jackson ( 7 )', 'oracle arena 18203', '22 - 42'], ['65', 'march 13', 'dallas', 'w 119 - 110 ( ot )', 'stephen jackson ( 31 )', 'ronny turiaf ( 12 )', 'stephen jackson ( 10 )', 'oracle arena 18751', '23 - 42'], ['66', 'march 15', 'phoenix', 'l 130 - 154 ( ot )', 'monta ellis ( 26 )', 'anthony randolph , ronny turiaf ( 6 )', 'stephen jackson ( 9 )', 'oracle arena 19596', '23 - 43'], ['67', 'march 17', 'la clippers', 'w 127 - 120 ( ot )', 'monta ellis ( 29 )', 'kelenna azubuike ( 9 )', 'ronny turiaf ( 8 )', 'oracle arena 18223', '24 - 43'], ['68', 'march 19', 'la lakers', 'l 106 - 114 ( ot )', 'monta ellis ( 27 )', 'brandan wright ( 10 )', 'corey maggette ( 7 )', 'staples center 18997', '24 - 44'], ['69', 'march 20', 'philadelphia', 'w 119 - 111 ( ot )', 'brandan wright ( 25 )', 'stephen jackson ( 10 )', 'stephen jackson ( 9 )', 'oracle arena 19596', '25 - 44'], ['70', 'march 22', 'new orleans', 'l 89 - 99 ( ot )', 'stephen jackson ( 22 )', 'stephen jackson ( 10 )', 'stephen jackson ( 5 )', 'new orleans arena 16351', '25 - 45'], ['71', 'march 24', 'san antonio', 'l 106 - 107 ( ot )', 'monta ellis ( 27 )', 'anthony randolph ( 9 )', 'stephen jackson ( 4 )', 'at & t center 18797', '25 - 46'], ['72', 'march 25', 'dallas', 'l 106 - 128 ( ot )', 'anthony morrow ( 29 )', 'anthony randolph ( 6 )', 'monta ellis , stephen jackson ( 5 )', 'american airlines center 19862', '25 - 47'], ['73', 'march 28', 'denver', 'l 116 - 129 ( ot )', 'jamal crawford ( 30 )', 'anthony randolph ( 14 )', 'jamal crawford ( 5 )', 'pepsi center 19155', '25 - 48'], ['74', 'march 30', 'memphis', 'l 109 - 114 ( ot )', 'monta ellis ( 29 )', 'anthony randolph ( 12 )', 'monta ellis ( 5 )', 'oracle arena 18471', '25 - 49']] |
2005 pba draft | https://en.wikipedia.org/wiki/2005_PBA_draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11779131-3.html.csv | majority | all the players that were picked originated from the phillippines . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'philippines', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'country of origin', 'philippines'], 'result': True, 'ind': 0, 'tointer': 'for the country of origin records of all rows , all of them fuzzily match to philippines .', 'tostr': 'all_eq { all_rows ; country of origin ; philippines } = true'} | all_eq { all_rows ; country of origin ; philippines } = true | for the country of origin records of all rows , all of them fuzzily match to philippines . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country of origin_3': 3, 'philippines_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country of origin_3': 'country of origin', 'philippines_4': 'philippines'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country of origin_3': [0], 'philippines_4': [0]} | ['pick', 'player', 'country of origin', 'pba team', 'college'] | [['10', 'cesar catli', 'philippines', 'sta lucia realtors', 'feu'], ['11', 'neil raã ± eses', 'philippines', 'coca - cola tigers', 'uv'], ['12', 'al magpayo', 'philippines', 'coca - cola tigers', 'st benilde'], ['13', 'bj manalo', 'philippines', 'purefoods chunkee giants', 'de la salle'], ['14', 'larry fonacier', 'philippines', 'red bull barako', 'ateneo'], ['15', 'mark joseph kong', 'philippines', 'alaska aces', 'adamson'], ['16', 'rey mendoza', 'philippines', 'sta lucia realtors', 'nu'], ['17', 'paolo bugia', 'philippines', 'red bull barako', 'ateneo'], ['18', 'mark macapagal', 'philippines', "talk n ' text phone pals", 'san sebastian']] |
list of free multiplayer online games | https://en.wikipedia.org/wiki/List_of_free_multiplayer_online_games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17493675-2.html.csv | ordinal | valve corporation has the oldest release date on their multiplayer online game . | {'row': '8', 'col': '2', 'order': '1', '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', 'release date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; release date ; 1 }'}, 'developer ( s )'], 'result': 'valve corporation', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; release date ; 1 } ; developer ( s ) }'}, 'valve corporation'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; release date ; 1 } ; developer ( s ) } ; valve corporation } = true', 'tointer': 'select the row whose release date record of all rows is 1st minimum . the developer ( s ) record of this row is valve corporation .'} | eq { hop { nth_argmin { all_rows ; release date ; 1 } ; developer ( s ) } ; valve corporation } = true | select the row whose release date record of all rows is 1st minimum . the developer ( s ) record of this row is valve corporation . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'release date_5': 5, '1_6': 6, 'developer (s)_7': 7, 'valve corporation_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', 'release date_5': 'release date', '1_6': '1', 'developer (s)_7': 'developer ( s )', 'valve corporation_8': 'valve corporation'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'release date_5': [0], '1_6': [0], 'developer (s)_7': [1], 'valve corporation_8': [2]} | ['developer ( s )', 'release date', 'required os', 'genre', 'type'] | [['robot entertainment , gas powered games', 'august 16 , 2011', 'windows', 'mmorts', '3d'], ['ea games', '2009', 'windows', 'first - person shooter', '3d'], ['stunlock studios', '2011', 'windows', 'moba', '3d'], ['thq', '2010 - 2011', 'windows', 'real - time strategy', '3d'], ['novel , inc', '2011', 'windows', 'mmorpg', '2d'], ['masthead studios', '2013', 'windows', 'third - person shooter', '3d'], ['riot games', '2008 - 2011', 'windows , os x', 'moba', '3d'], ['valve corporation', '2007', 'windows , os x , linux', 'first - person shooter', '3d']] |
wpar | https://en.wikipedia.org/wiki/WPAR | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12840409-2.html.csv | ordinal | the wpar radio channel with the call sign w294aj operates on the second highest frequency . | {'row': '1', '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', 'frequency mhz', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; frequency mhz ; 2 }'}, 'call sign'], 'result': 'w294aj', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; call sign }'}, 'w294aj'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; call sign } ; w294aj } = true', 'tointer': 'select the row whose frequency mhz record of all rows is 2nd maximum . the call sign record of this row is w294aj .'} | eq { hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; call sign } ; w294aj } = true | select the row whose frequency mhz record of all rows is 2nd maximum . the call sign record of this row is w294aj . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, '2_6': 6, 'call sign_7': 7, 'w294aj_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', 'frequency mhz_5': 'frequency mhz', '2_6': '2', 'call sign_7': 'call sign', 'w294aj_8': 'w294aj'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], '2_6': [0], 'call sign_7': [1], 'w294aj_8': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['w294aj', '106.7', 'charlottesville , virginia', '21', 'd', 'fcc'], ['w236ad', '95.1', 'lawrenceville , virginia', '25', 'd', 'fcc'], ['w246bz', '97.1', 'crewe , virginia', '38', 'd', 'fcc'], ['w254ah', '98.7', 'farmville , virginia', '27', 'd', 'fcc'], ['w272cc', '102.3', 'smithfield , virginia', '10', 'd', 'fcc'], ['w273aa', '102.5', 'blacksburg , virginia', '10', 'd', 'fcc'], ['w274ab', '102.7', 'petersburg , virginia', '30', 'd', 'fcc'], ['w291aj', '106.1', 'waverly , virginia', '27', 'd', 'fcc'], ['w292cu', '106.3', 'christiansburg , virginia', '10', 'd', 'fcc'], ['w295ai', '106.9', 'marion , virginia', '10', 'd', 'fcc']] |
lonhro | https://en.wikipedia.org/wiki/Lonhro | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1360997-3.html.csv | aggregation | lonhro 's total time in april of 2003 was over three minutes . | {'scope': 'subset', 'col': '8', 'type': 'sum', 'result': '3:00', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'apr 2003'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'apr 2003'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; apr 2003 }', 'tointer': 'select the rows whose date record fuzzily matches to apr 2003 .'}, 'time'], 'result': '3:00', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; apr 2003 } ; time }'}, '3:00'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; apr 2003 } ; time } ; 3:00 } = true', 'tointer': 'select the rows whose date record fuzzily matches to apr 2003 . the sum of the time record of these rows is 3:00 .'} | round_eq { sum { filter_eq { all_rows ; date ; apr 2003 } ; time } ; 3:00 } = true | select the rows whose date record fuzzily matches to apr 2003 . the sum of the time record of these rows is 3:00 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'apr 2003_6': 6, 'time_7': 7, '3:00_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'apr 2003_6': 'apr 2003', 'time_7': 'time', '3:00_8': '3:00'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'apr 2003_6': [0], 'time_7': [1], '3:00_8': [2]} | ['result', 'date', 'race', 'venue', 'group', 'distance', 'weight ( kg )', 'time', 'jockey', 'winner / 2nd'] | [['won', '03 aug 2002', 'missile stakes', 'rosehill', 'g3', '1100 m', '57.5', '1:03.53', 'd beadman', '2nd - ancient song'], ['2nd', '24 aug 2002', 'warwick stakes', 'warwick farm', 'g2', '1400 m', '57.5', '1:21.85', 'd beadman', '1st - defier'], ['won', '07 sep 2002', 'chelmsford stakes', 'randwick', 'g2', '1600 m', '57.5', '1:36.30', 'd beadman', '2nd - platinum scissors'], ['4th', '29 sep 2002', 'george main stakes', 'randwick', 'g1', '1600 m', '57.5', '1:38.31', 'd beadman', '1st - defier'], ['won', '12 oct 2002', 'caulfield stakes', 'caulfield', 'g1', '2000 m', '57.5', '2:00.60', 'd beadman', '2nd - sunline'], ['6th', '26 oct 2002', 'cox plate', 'moonee valley', 'g1', '2040 m', '56.5', '2:06.27', 'd beadman', '1st - northerly'], ['won', '02 nov 2002', 'mackinnon stakes', 'flemington', 'g1', '2000 m', '57.5', '2:02.64', 'd beadman', '2nd - royal code'], ['won', '22 feb 2003', 'expressway stakes', 'randwick', 'g2', '1200 m', '57.5', '1:10.66', 'd beadman', '2nd - belle du jour'], ['won', '08 mar 2003', 'apollo stakes', 'randwick', 'g2', '1400 m', '58', '1:22.49', 'd beadman', '2nd - hoeburg'], ['won', '15 mar 2003', 'chipping norton stakes', 'warwick farm', 'g1', '1600 m', '58', '1:37.93', 'd beadman', '2nd - shogun lodge'], ['won', '05 apr 2003', 'george ryder stakes', 'rosehill', 'g1', '1500 m', '58', '1:30.71', 'd beadman', '2nd - dash for cash'], ['4th', '19 apr 2003', 'doncaster handicap', 'randwick', 'g1', '1600 m', '57.5', '1:36.85', 'd beadman', '1st - grand armee']] |
vasek pospisil | https://en.wikipedia.org/wiki/Vasek_Pospisil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13181492-2.html.csv | superlative | in vasek pospisil the most recent game on a hard surface was on august 4 , 2013 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '17', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'hard'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; hard }', 'tointer': 'select the rows whose surface record fuzzily matches to hard .'}, 'date'], 'result': 'august 4 , 2013', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; surface ; hard } ; date }', 'tointer': 'select the rows whose surface record fuzzily matches to hard . the maximum date record of these rows is august 4 , 2013 .'}, 'august 4 , 2013'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; surface ; hard } ; date } ; august 4 , 2013 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to hard . the maximum date record of these rows is august 4 , 2013 .'} | eq { max { filter_eq { all_rows ; surface ; hard } ; date } ; august 4 , 2013 } = true | select the rows whose surface record fuzzily matches to hard . the maximum date record of these rows is august 4 , 2013 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'surface_5': 5, 'hard_6': 6, 'date_7': 7, 'august 4 , 2013_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'surface_5': 'surface', 'hard_6': 'hard', 'date_7': 'date', 'august 4 , 2013_8': 'august 4 , 2013'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'hard_6': [0], 'date_7': [1], 'august 4 , 2013_8': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', 'july 13 , 2009', 'usa f17 , peoria', 'clay', 'michael venus', '7 - 6 ( 7 - 4 ) , 4 - 6 , 4 - 6'], ['winner', 'september 26 , 2009', 'italy f29 , alghero', 'hard', 'francesco piccari', '6 - 3 , 6 - 7 ( 5 - 7 ) , 6 - 3'], ['winner', 'october 3 , 2009', "italy f30 , quartu sant ' elena", 'hard', 'matteo viola', '6 - 1 , 6 - 2'], ['winner', 'november 1 , 2009', 'mexico f12 , obregón', 'hard', 'daniel garza', '7 - 6 ( 7 - 0 ) , 6 - 3'], ['winner', 'november 8 , 2009', 'mexico f14 , guadalajara', 'clay', 'césar ramírez', '6 - 2 , 6 - 2'], ['runner - up', 'february 22 , 2010', 'usa f5 , brownsville', 'hard', 'víctor estrella', '4 - 6 , 3 - 6'], ['winner', 'march 21 , 2010', 'canada f3 , sherbrooke', 'hard ( i )', 'milos raonic', '6 - 4 , 4 - 6 , 6 - 3'], ['winner', 'september 5 , 2010', 'mexico f6 , león', 'hard', 'david rice', '6 - 1 , 6 - 2'], ['winner', 'september 12 , 2010', 'mexico f7 , guadalajara', 'hard', 'adam el mihdawy', '6 - 0 , 6 - 1'], ['winner', 'october 3 , 2010', 'canada f5 , markham', 'hard ( i )', 'nicholas monroe', '6 - 3 , 6 - 2'], ['winner', 'may 29 , 2011', 'korea f2 , changwon', 'hard', 'lim yong - kyu', '7 - 5 , 6 - 4'], ['winner', 'july 31 , 2011', 'canada f4 , saskatoon', 'hard', 'érik chvojka', '7 - 5 , 6 - 2'], ['winner', 'march 25 , 2012', 'rimouski , canada', 'hard ( i )', 'maxime authom', '7 - 6 ( 8 - 6 ) , 6 - 4'], ['winner', 'july 22 , 2012', 'granby , canada', 'hard', 'igor sijsling', '7 - 6 ( 7 - 2 ) , 6 - 4'], ['runner - up', 'march 18 , 2013', 'rimouski , canada', 'hard ( i )', 'rik de voest', '6 - 7 ( 6 - 8 ) , 4 - 6'], ['winner', 'may 4 , 2013', 'johannesburg , south africa', 'hard', 'michał przysiężny', '6 - 7 ( 7 - 9 ) , 6 - 0 , 4 - 1 ret'], ['winner', 'august 4 , 2013', 'vancouver , canada', 'hard', 'daniel evans', '6 - 0 , 1 - 6 , 7 - 5']] |
united states house of representatives elections , 1918 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1918 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1346118-2.html.csv | ordinal | in the united states house of representatives election of 1918 , the 1st representative elected was j. thomas heflin , elected in 1904 . | {'row': '4', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'first elected', '1'], 'result': '1904', 'ind': 0, 'tostr': 'nth_min { all_rows ; first elected ; 1 }', 'tointer': 'the 1st minimum first elected record of all rows is 1904 .'}, '1904'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; first elected ; 1 } ; 1904 }', 'tointer': 'the 1st minimum first elected record of all rows is 1904 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'j thomas heflin', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent }'}, 'j thomas heflin'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; j thomas heflin }', 'tointer': 'the incumbent record of the row with 1st minimum first elected record is j thomas heflin .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; first elected ; 1 } ; 1904 } ; eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; j thomas heflin } } = true', 'tointer': 'the 1st minimum first elected record of all rows is 1904 . the incumbent record of the row with 1st minimum first elected record is j thomas heflin .'} | and { eq { nth_min { all_rows ; first elected ; 1 } ; 1904 } ; eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; j thomas heflin } } = true | the 1st minimum first elected record of all rows is 1904 . the incumbent record of the row with 1st minimum first elected record is j thomas heflin . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'first elected_8': 8, '1_9': 9, '1904_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'first elected_12': 12, '1_13': 13, 'incumbent_14': 14, 'j thomas heflin_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'first elected_8': 'first elected', '1_9': '1', '1904_10': '1904', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'first elected_12': 'first elected', '1_13': '1', 'incumbent_14': 'incumbent', 'j thomas heflin_15': 'j thomas heflin'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'first elected_8': [0], '1_9': [0], '1904_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'first elected_12': [2], '1_13': [2], 'incumbent_14': [3], 'j thomas heflin_15': [4]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['alabama 1', 'oscar lee gray', 'democratic', '1914', 'retired democratic hold', 'john mcduffie ( d ) unopposed'], ['alabama 2', 's hubert dent , jr', 'democratic', '1908', 're - elected', 's hubert dent , jr ( d ) unopposed'], ['alabama 3', 'henry b steagall', 'democratic', '1914', 're - elected', 'henry b steagall ( d ) unopposed'], ['alabama 5', 'j thomas heflin', 'democratic', '1904', 're - elected', 'j thomas heflin ( d ) unopposed'], ['alabama 6', 'william b oliver', 'democratic', '1914', 're - elected', 'william b oliver ( d ) unopposed'], ['alabama 8', 'edward b almon', 'democratic', '1914', 're - elected', 'edward b almon ( d ) unopposed']] |
kim hyun - joong | https://en.wikipedia.org/wiki/Kim_Hyun-joong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18629727-2.html.csv | majority | the majority of kim hun-joong 's roles have come before 2012 . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2012', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'year', '2012'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are less than 2012 .', 'tostr': 'most_less { all_rows ; year ; 2012 } = true'} | most_less { all_rows ; year ; 2012 } = true | for the year records of all rows , most of them are less than 2012 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '2012_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '2012_4': '2012'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '2012_4': [0]} | ['year', 'title', 'hangul / japanese', 'role', 'network', 'genre'] | [['2005', 'nonstop 5', '논스톱 5', 'guest ep208', 'mbc', 'sitcom'], ['2005', 'can love be refilled', '사랑도 리필이 되나요', 'william', 'kbs2', 'sitcom'], ['2007', 'hotelier', 'ホテリアー', 'cameo ep7 ( with ss501 )', 'tv asahi', 'drama'], ['2008', 'spotlight', '스포트라이트', 'cameo ( with ss501 )', 'mbc', 'drama'], ['2009', 'boys over flowers', '꽃보다 남자', 'yoon ji - hoo', 'kbs2', 'drama'], ['2010', 'playful kiss', '장난스런 키스', 'baek seung - jo', 'mbc', 'drama'], ['2011', 'dream high', '드림하이', 'cameo ep1', 'kbs2', 'drama'], ['2014', 'age of feeling', '감격시대', 'shin jung - tae', 'kbs2', 'drama']] |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-22.html.csv | count | 10 incumbents were re - elected during the 2000 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '10', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'results', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose results record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; results ; re - elected }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; results ; re - elected } }', 'tointer': 'select the rows whose results record fuzzily matches to re - elected . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; results ; re - elected } } ; 10 } = true', 'tointer': 'select the rows whose results record fuzzily matches to re - elected . the number of such rows is 10 .'} | eq { count { filter_eq { all_rows ; results ; re - elected } } ; 10 } = true | select the rows whose results record fuzzily matches to re - elected . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'results_5': 5, 're - elected_6': 6, '10_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'results_5': 'results', 're - elected_6': 're - elected', '10_7': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'results_5': [0], 're - elected_6': [0], '10_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['michigan 1', 'bart stupak', 'democratic', '1992', 're - elected', 'bart stupak ( d ) 59 % chuck yob ( r ) 41 %'], ['michigan 2', 'pete hoekstra', 'republican', '1992', 're - elected', 'pete hoekstra ( r ) 65 % bob shrauger ( d ) 34 %'], ['michigan 3', 'vern ehlers', 'republican', '1993', 're - elected', 'vern ehlers ( r ) 65 % timothy steele ( d ) 34 %'], ['michigan 5', 'james barcia', 'democratic', '1992', 're - elected', 'james barcia ( d ) 75 % ronald actis ( r ) 24 %'], ['michigan 6', 'fred upton', 'republican', '1986', 're - elected', 'fred upton ( r ) 68 % james bupp ( d ) 30 %'], ['michigan 7', 'nick smith', 'republican', '1992', 're - elected', 'nick smith ( r ) 62 % jennie crittendon ( d ) 36 %'], ['michigan 9', 'dale kildee', 'democratic', '1976', 're - elected', 'dale kildee ( d ) 62 % grant garrett ( r ) 36 %'], ['michigan 10', 'david bonior', 'democratic', '1976', 're - elected', 'david bonior ( d ) 65 % tom turner ( r ) 34 %'], ['michigan 13', 'lynn rivers', 'democratic', '1994', 're - elected', 'lynn rivers ( d ) 65 % carl barry ( r ) 33 %'], ['michigan 14', 'john conyers jr', 'democratic', '1964', 're - elected', 'john conyers jr ( d ) 90 % william ashe ( r ) 10 %']] |
nicola larini | https://en.wikipedia.org/wiki/Nicola_Larini | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226510-1.html.csv | aggregation | the ferrari engines driven by nicola larini scored a total of 6 points . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '6', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'ferrari'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'ferrari'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; engine ; ferrari }', 'tointer': 'select the rows whose engine record fuzzily matches to ferrari .'}, 'points'], 'result': '6', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; engine ; ferrari } ; points }'}, '6'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; engine ; ferrari } ; points } ; 6 } = true', 'tointer': 'select the rows whose engine record fuzzily matches to ferrari . the sum of the points record of these rows is 6 .'} | round_eq { sum { filter_eq { all_rows ; engine ; ferrari } ; points } ; 6 } = true | select the rows whose engine record fuzzily matches to ferrari . the sum of the points record of these rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'engine_5': 5, 'ferrari_6': 6, 'points_7': 7, '6_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'engine_5': 'engine', 'ferrari_6': 'ferrari', 'points_7': 'points', '6_8': '6'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'engine_5': [0], 'ferrari_6': [0], 'points_7': [1], '6_8': [2]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1987', 'enzo coloni racing car systems', 'coloni fc - 187', 'ford dfz 3.5 l v8', '0'], ['1988', 'osella squadra corse', 'osella fa1', 'osella 1.5 l v8 t', '0'], ['1989', 'osella squadra corse', 'osella fa1 m89', 'ford dfr 3.5 l v8', '0'], ['1990', 'ligier gitanes', 'ligier js33', 'ford dfr 3.5 l v8', '0'], ['1991', 'modena team spa', 'lambo 291', 'lamborghini 3512 3.5 l v12', '0'], ['1992', 'scuderia ferrari', 'ferrari f92a', 'ferrari 037 3.5 l v12', '0'], ['1994', 'scuderia ferrari', 'ferrari 412t1', 'ferrari 043 3.5 l v12', '6'], ['1997', 'red bull sauber petronas', 'sauber c16', 'petronas spe - 01 3.0 l v10', '1']] |
list of singaporean films | https://en.wikipedia.org/wiki/List_of_Singaporean_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1601229-7.html.csv | count | three of the singaporean films were ultimately left unreleased by their studios . | {'scope': 'all', 'criterion': 'equal', 'value': 'unreleased', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'unreleased'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to unreleased .', 'tostr': 'filter_eq { all_rows ; date ; unreleased }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; unreleased } }', 'tointer': 'select the rows whose date record fuzzily matches to unreleased . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; unreleased } } ; 3 } = true', 'tointer': 'select the rows whose date record fuzzily matches to unreleased . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; date ; unreleased } } ; 3 } = true | select the rows whose date record fuzzily matches to unreleased . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'unreleased_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'unreleased_6': 'unreleased', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'unreleased_6': [0], '3_7': [2]} | ['date', 'title', 'director', 'production cost', 'singapore gross'] | [['2004', '2004', '2004', '2004', '2004'], ['february 2004', 'last life in the universe', 'pen - ek ratanaruang', 'us2000000', '65000'], ['march 2004', 'the eye 2', 'danny pang / oxide pang', 'us3000000', '1577000'], ['june 2004', 'the best bet ( 突然发财 )', 'jack neo', '1500000', '2664000'], ['august 2004', 'clouds in my coffee', 'gallen mei', 'us125000', '11000'], ['unreleased', 'zombie dogs', 'toh hai leong', 'na', 'na'], ['unreleased', 'outsiders', 'sam loh', 'na', 'na'], ['unreleased', 'tequila', 'jonathan lim', 'us13000', 'na']] |
little east conference | https://en.wikipedia.org/wiki/Little_East_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974545-2.html.csv | comparative | bridgewater state university has a higher enrollment than fitchburg state university . | {'row_1': '1', 'row_2': '2', 'col': '6', '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', 'location', 'bridgewater , massachusetts'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to bridgewater , massachusetts .', 'tostr': 'filter_eq { all_rows ; location ; bridgewater , massachusetts }'}, 'enrollment'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; bridgewater , massachusetts } ; enrollment }', 'tointer': 'select the rows whose location record fuzzily matches to bridgewater , massachusetts . take the enrollment record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'fitchburg , massachusetts'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to fitchburg , massachusetts .', 'tostr': 'filter_eq { all_rows ; location ; fitchburg , massachusetts }'}, 'enrollment'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; location ; fitchburg , massachusetts } ; enrollment }', 'tointer': 'select the rows whose location record fuzzily matches to fitchburg , massachusetts . take the enrollment record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; location ; bridgewater , massachusetts } ; enrollment } ; hop { filter_eq { all_rows ; location ; fitchburg , massachusetts } ; enrollment } } = true', 'tointer': 'select the rows whose location record fuzzily matches to bridgewater , massachusetts . take the enrollment record of this row . select the rows whose location record fuzzily matches to fitchburg , massachusetts . take the enrollment record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; location ; bridgewater , massachusetts } ; enrollment } ; hop { filter_eq { all_rows ; location ; fitchburg , massachusetts } ; enrollment } } = true | select the rows whose location record fuzzily matches to bridgewater , massachusetts . take the enrollment record of this row . select the rows whose location record fuzzily matches to fitchburg , massachusetts . take the enrollment record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'bridgewater , massachusetts_8': 8, 'enrollment_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'location_11': 11, 'fitchburg , massachusetts_12': 12, 'enrollment_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'bridgewater , massachusetts_8': 'bridgewater , massachusetts', 'enrollment_9': 'enrollment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'location_11': 'location', 'fitchburg , massachusetts_12': 'fitchburg , massachusetts', 'enrollment_13': 'enrollment'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'location_7': [0], 'bridgewater , massachusetts_8': [0], 'enrollment_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'location_11': [1], 'fitchburg , massachusetts_12': [1], 'enrollment_13': [3]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'primary conference', 'lec sport'] | [['bridgewater state university', 'bridgewater , massachusetts', 'bears', '1840', 'public', '11201', 'mascac', 'field hockey tennis'], ['fitchburg state university', 'fitchburg , massachusetts', 'falcons', '1894', 'public', '5201', 'mascac', 'field hockey'], ['framingham state university', 'framingham , massachusetts', 'rams', '1839', 'public', '5903', 'mascac', 'field hockey'], ['salem state university', 'salem , massachusetts', 'vikings', '1854', 'public', '10125', 'mascac', "field hockey men 's lacrosse tennis"], ['westfield state university', 'westfield , massachusetts', 'owls', '1838', 'public', '5500', 'mascac', 'field hockey']] |
1970 - 71 cleveland cavaliers season | https://en.wikipedia.org/wiki/1970%E2%80%9371_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16275352-5.html.csv | majority | all games of the cleveland cavaliers in the 1970 - 71 season were scheduled for the month of november . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'november', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to november .', 'tostr': 'all_eq { all_rows ; date ; november } = true'} | all_eq { all_rows ; date ; november } = true | for the date records of all rows , all of them fuzzily match to november . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'november_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'november_4': 'november'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'november_4': [0]} | ['date', 'h / a / n', 'opponent', 'score', 'record'] | [['november 1', 'h', 'atlanta hawks', '107 - 130', '0 - 10'], ['november 2', 'a', 'philadelphia 76ers', '87 - 141', '0 - 11'], ['november 4', 'h', 'milwaukee bucks', '108 - 110', '0 - 12'], ['november 7', 'a', 'buffalo braves', '91 - 103', '0 - 13'], ['november 8', 'h', 'seattle supersonics', '105 - 111', '0 - 14'], ['november 10', 'a', 'san francisco warriors', '74 - 109', '0 - 15'], ['november 12', 'a', 'portland trail blazers', '105 - 103', '1 - 15'], ['november 13', 'a', 'seattle supersonics', '91 - 111', '1 - 16'], ['november 14', 'a', 'portland trail blazers', '110 - 125', '1 - 17'], ['november 16', 'a', 'baltimore bullets', '86 - 98', '1 - 18'], ['november 18', 'h', 'baltimore bullets', '98 - 111', '1 - 19'], ['november 20', 'a', 'boston celtics', '112 - 116', '1 - 20'], ['november 21', 'a', 'new york knicks', '94 - 102', '1 - 21'], ['november 22', 'h', 'phoenix suns', '99 - 114', '1 - 22'], ['november 25', 'h', 'san francisco warriors', '99 - 108', '1 - 23'], ['november 27', 'h', 'portland trail blazers', '102 - 111', '1 - 24'], ['november 28', 'a', 'cincinnati royals', '86 - 105', '1 - 25'], ['november 29', 'h', 'detroit pistons', '99 - 120', '1 - 26']] |
united states house of representatives elections , 1834 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1834 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668199-2.html.csv | unique | robert ramsey is the only incumbent who retired anti - jacksonian gain . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'anti - jacksonian gain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'anti - jacksonian gain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to anti - jacksonian gain .', 'tostr': 'filter_eq { all_rows ; result ; anti - jacksonian gain }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; anti - jacksonian gain } }', 'tointer': 'select the rows whose result record fuzzily matches to anti - jacksonian gain . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'anti - jacksonian gain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to anti - jacksonian gain .', 'tostr': 'filter_eq { all_rows ; result ; anti - jacksonian gain }'}, 'incumbent'], 'result': 'robert ramsey', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; anti - jacksonian gain } ; incumbent }'}, 'robert ramsey'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; anti - jacksonian gain } ; incumbent } ; robert ramsey }', 'tointer': 'the incumbent record of this unqiue row is robert ramsey .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; anti - jacksonian gain } } ; eq { hop { filter_eq { all_rows ; result ; anti - jacksonian gain } ; incumbent } ; robert ramsey } } = true', 'tointer': 'select the rows whose result record fuzzily matches to anti - jacksonian gain . there is only one such row in the table . the incumbent record of this unqiue row is robert ramsey .'} | and { only { filter_eq { all_rows ; result ; anti - jacksonian gain } } ; eq { hop { filter_eq { all_rows ; result ; anti - jacksonian gain } ; incumbent } ; robert ramsey } } = true | select the rows whose result record fuzzily matches to anti - jacksonian gain . there is only one such row in the table . the incumbent record of this unqiue row is robert ramsey . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'anti - jacksonian gain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'robert ramsey_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'anti - jacksonian gain_8': 'anti - jacksonian gain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'robert ramsey_10': 'robert ramsey'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'anti - jacksonian gain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'robert ramsey_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 1', 'joel b sutherland', 'jacksonian', '1826', 're - elected', 'joel b sutherland ( j ) 61.7 % james gowen 38.3 %'], ['pennsylvania 5', 'joel k mann', 'jacksonian', '1830', 'retired jacksonian hold', 'jacob fry , jr ( j ) 55.3 % james royer 44.7 %'], ['pennsylvania 6', 'robert ramsey', 'jacksonian', '1832', 'retired anti - jacksonian gain', 'mathias morris ( aj ) 52.4 % henry chapman ( j ) 47.6 %'], ['pennsylvania 10', 'william clark', 'anti - masonic', '1832', 're - elected', 'william clark ( am ) 54.0 % john c bucher ( j ) 46.0 %'], ['pennsylvania 12', 'george chambers', 'anti - masonic', '1832', 're - elected', 'george chambers ( am ) 59.8 % ludwig heck ( j ) 40.2 %'], ['pennsylvania 13', 'jesse miller', 'jacksonian', '1832', 're - elected', 'jesse miller ( j ) 51.4 % thomas whiteside ( am ) 48.6 %'], ['pennsylvania 17', 'john laporte', 'jacksonian', '1832', 're - elected', 'john laporte ( j ) 56.8 % horrace williston 43.2 %'], ['pennsylvania 18', 'george burd', 'anti - jacksonian', '1830', 'retired jacksonian gain', 'job mann ( j ) 54.6 % charles ogle ( am ) 45.4 %'], ['pennsylvania 22', 'harmar denny', 'anti - masonic', '1829 ( special )', 're - elected', 'harmar denny ( am ) 53.5 % john m snowden ( j ) 46.5 %'], ['pennsylvania 24', 'john banks', 'anti - masonic', '1830', 're - elected', 'john banks ( am ) 52.2 % samuel power ( j ) 47.8 %']] |
1985 - 86 philadelphia flyers season | https://en.wikipedia.org/wiki/1985%E2%80%9386_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14320222-6.html.csv | aggregation | the 1985-66 philadelphia flyers scored on average 80 points a game . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '80', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '80', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '80'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 80 } = true', 'tointer': 'the average of the points record of all rows is 80 .'} | round_eq { avg { all_rows ; points } ; 80 } = true | the average of the points record of all rows is 80 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '80_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '80_5': '80'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '80_5': [1]} | ['game', 'february', 'opponent', 'score', 'record', 'points'] | [['52', '1', 'quebec nordiques', '2 - 2 ot', '35 - 15 - 2', '72'], ['53', '6', 'st louis blues', '4 - 3', '36 - 15 - 2', '74'], ['54', '8', 'minnesota north stars', '3 - 3 ot', '36 - 15 - 3', '75'], ['55', '9', 'chicago black hawks', '2 - 2 ot', '36 - 15 - 4', '76'], ['56', '12', 'buffalo sabres', '4 - 0', '37 - 15 - 4', '78'], ['57', '13', 'new york islanders', '6 - 3', '38 - 15 - 4', '80'], ['58', '15', 'montreal canadiens', '3 - 5', '38 - 16 - 4', '80'], ['59', '17', 'winnipeg jets', '8 - 4', '39 - 16 - 4', '82'], ['60', '20', 'los angeles kings', '5 - 3', '40 - 16 - 4', '84'], ['61', '22', 'washington capitals', '3 - 1', '41 - 16 - 4', '86'], ['62', '27', 'calgary flames', '4 - 7', '41 - 17 - 4', '86'], ['63', '28', 'vancouver canucks', '1 - 3', '41 - 18 - 4', '86']] |
1972 - 73 philadelphia flyers season | https://en.wikipedia.org/wiki/1972%E2%80%9373_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14294324-15.html.csv | comparative | bill barber was drafted in an earlier round than jim watson in the 1972-73 philadelphia flyers ' season . | {'row_1': '2', 'row_2': '3', 'col': '1', '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', 'player', 'tom bladon'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to tom bladon .', 'tostr': 'filter_eq { all_rows ; player ; tom bladon }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; tom bladon } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to tom bladon . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jim watson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to jim watson .', 'tostr': 'filter_eq { all_rows ; player ; jim watson }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; jim watson } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to jim watson . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; tom bladon } ; round } ; hop { filter_eq { all_rows ; player ; jim watson } ; round } } = true', 'tointer': 'select the rows whose player record fuzzily matches to tom bladon . take the round record of this row . select the rows whose player record fuzzily matches to jim watson . take the round record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; tom bladon } ; round } ; hop { filter_eq { all_rows ; player ; jim watson } ; round } } = true | select the rows whose player record fuzzily matches to tom bladon . take the round record of this row . select the rows whose player record fuzzily matches to jim watson . take the round 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, 'player_7': 7, 'tom bladon_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'jim watson_12': 12, 'round_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', 'player_7': 'player', 'tom bladon_8': 'tom bladon', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'jim watson_12': 'jim watson', 'round_13': 'round'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'tom bladon_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'jim watson_12': [1], 'round_13': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'bill barber', 'left wing', 'canada', 'kitchener rangers ( oha )'], ['2', 'tom bladon', 'defense', 'canada', 'edmonton oil kings ( wchl )'], ['3', 'jim watson', 'defense', 'canada', 'calgary centennials ( wchl )'], ['4', 'al macadam', 'right wing', 'canada', 'charlottetown islanders ( mjhl )'], ['5', 'darryl fedorak', 'goaltender', 'canada', 'victoria cougars ( wchl )'], ['6', 'dave hastings', 'goaltender', 'canada', 'charlottetown islanders ( mjhl )'], ['7', 'serge beaudoin', 'defense', 'canada', 'trois - riviã ¨ res ducs ( qmjhl )'], ['8', 'pat russell', 'right wing', 'canada', 'vancouver nats ( wchl )'], ['9', 'ray boutin', 'goaltender', 'canada', 'sorel black hawks ( qmjhl )']] |
1983 - 84 houston rockets season | https://en.wikipedia.org/wiki/1983%E2%80%9384_Houston_Rockets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17383465-1.html.csv | aggregation | the players had a mean pick of about 94 in the 1983-884 houston rockets season . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '94', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pick'], 'result': '94', 'ind': 0, 'tostr': 'avg { all_rows ; pick }'}, '94'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pick } ; 94 } = true', 'tointer': 'the average of the pick record of all rows is 94 .'} | round_eq { avg { all_rows ; pick } ; 94 } = true | the average of the pick record of all rows is 94 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pick_4': 4, '94_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pick_4': 'pick', '94_5': '94'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pick_4': [0], '94_5': [1]} | ['round', 'pick', 'player', 'nationality', 'college'] | [['1', '1', 'ralph sampson', 'united states', 'virginia'], ['1', '3', 'rodney mccray', 'united states', 'louisville'], ['3', '48', 'craig ehlo', 'united states', 'washington state'], ['4', '71', 'darrell browder', 'united states', 'texas christian'], ['5', '94', 'chuck barnett', 'united states', 'oklahoma'], ['6', '117', 'jim stack', 'united states', 'northwestern'], ['7', '140', 'brian kellerman', 'united states', 'idaho'], ['8', '163', 'jeff bolding', 'united states', 'arkansas state'], ['9', '185', 'james campbell', 'united states', 'oklahoma city']] |
1992 open championship | https://en.wikipedia.org/wiki/1992_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18122130-3.html.csv | comparative | tom watson had a higher total than tom weiskopf did in the 1992 open championship . | {'row_1': '5', 'row_2': '2', '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', 'player', 'tom watson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to tom watson .', 'tostr': 'filter_eq { all_rows ; player ; tom watson }'}, 'total'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; tom watson } ; total }', 'tointer': 'select the rows whose player record fuzzily matches to tom watson . take the total record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'tom weiskopf'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to tom weiskopf .', 'tostr': 'filter_eq { all_rows ; player ; tom weiskopf }'}, 'total'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; tom weiskopf } ; total }', 'tointer': 'select the rows whose player record fuzzily matches to tom weiskopf . take the total record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; tom watson } ; total } ; hop { filter_eq { all_rows ; player ; tom weiskopf } ; total } } = true', 'tointer': 'select the rows whose player record fuzzily matches to tom watson . take the total record of this row . select the rows whose player record fuzzily matches to tom weiskopf . take the total record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; tom watson } ; total } ; hop { filter_eq { all_rows ; player ; tom weiskopf } ; total } } = true | select the rows whose player record fuzzily matches to tom watson . take the total record of this row . select the rows whose player record fuzzily matches to tom weiskopf . take the total 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, 'player_7': 7, 'tom watson_8': 8, 'total_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'tom weiskopf_12': 12, 'total_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', 'player_7': 'player', 'tom watson_8': 'tom watson', 'total_9': 'total', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'tom weiskopf_12': 'tom weiskopf', 'total_13': 'total'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'tom watson_8': [0], 'total_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'tom weiskopf_12': [1], 'total_13': [3]} | ['player', 'country', 'year ( s ) won', 'total', 'to par'] | [['seve ballesteros', 'spain', '1979 , 1984 , 1988', '145', '+ 1'], ['tom weiskopf', 'united states', '1973', '145', '+ 1'], ['gary player', 'south africa', '1959 , 1968 , 1974', '146', '+ 2'], ['jack nicklaus', 'united states', '1966 , 1970 , 1978', '148', '+ 4'], ['tom watson', 'united states', '1975 , 1977 , 1980 , 1982 , 1983', '148', '+ 4']] |
athletics at the 2008 summer olympics - women 's 200 metres | https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_200_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569021-5.html.csv | ordinal | the second highest ranked athlete in the women 's 200 metres at the 2008 summer olympics was marshevet hooker . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'rank', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; rank ; 2 }'}, 'athlete'], 'result': 'marshevet hooker', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 2 } ; athlete }'}, 'marshevet hooker'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 2 } ; athlete } ; marshevet hooker } = true', 'tointer': 'select the row whose rank record of all rows is 2nd minimum . the athlete record of this row is marshevet hooker .'} | eq { hop { nth_argmin { all_rows ; rank ; 2 } ; athlete } ; marshevet hooker } = true | select the row whose rank record of all rows is 2nd minimum . the athlete record of this row is marshevet hooker . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, '2_6': 6, 'athlete_7': 7, 'marshevet hooker_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', 'rank_5': 'rank', '2_6': '2', 'athlete_7': 'athlete', 'marshevet hooker_8': 'marshevet hooker'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], '2_6': [0], 'athlete_7': [1], 'marshevet hooker_8': [2]} | ['rank', 'lane', 'athlete', 'country', 'time', 'react'] | [['1', '7', 'allyson felix', 'united states', '22.33', '0.181'], ['2', '9', 'marshevet hooker', 'united states', '22.50', '0.196'], ['3', '5', 'sherone simpson', 'jamaica', '22.50', '0.175'], ['4', '3', 'cydonie mothersille', 'cayman islands', '22.61', '0.212'], ['5', '4', 'muriel hurtis - houairi', 'france', '22.71', '0.188'], ['6', '6', 'roqaya al - gassra', 'bahrain', '22.72', '0.259'], ['7', '8', 'emily freeman', 'great britain', '22.83', '0.201'], ['8', '2', 'aleksandra fedoriva', 'russia', '23.22', '0.202']] |
50 cent : the money and the power | https://en.wikipedia.org/wiki/50_Cent%3A_The_Money_and_the_Power | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19810459-1.html.csv | aggregation | the average age of the players on team money is 22.8 years . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '22.8', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'team money'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original team', 'team money'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original team ; team money }', 'tointer': 'select the rows whose original team record fuzzily matches to team money .'}, 'age'], 'result': '22.8', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; original team ; team money } ; age }'}, '22.8'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; original team ; team money } ; age } ; 22.8 } = true', 'tointer': 'select the rows whose original team record fuzzily matches to team money . the average of the age record of these rows is 22.8 .'} | round_eq { avg { filter_eq { all_rows ; original team ; team money } ; age } ; 22.8 } = true | select the rows whose original team record fuzzily matches to team money . the average of the age record of these rows is 22.8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'original team_5': 5, 'team money_6': 6, 'age_7': 7, '22.8_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'original team_5': 'original team', 'team money_6': 'team money', 'age_7': 'age', '22.8_8': '22.8'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original team_5': [0], 'team money_6': [0], 'age_7': [1], '22.8_8': [2]} | ['contestant', 'background', 'original team', 'age', 'hometown', 'result'] | [['ryan mayberry', 'internet dreamer', 'team power', '24', 'lancaster , pennsylvania', 'winner'], ['larry wade', 'financial consultant', 'team money', '26', 'tampa , florida', 'runner - up'], ['maurice cornbreadd', 'aspiring music mogul', 'team money', '26', 'houston , texas', '3rd place'], ['mehgan james', 'business major', 'team power', '18', 'houston , texas', '4th place'], ['derrick hargrove', 'civil servant', 'team power', '18', 'plant city , florida', '5th place'], ['nikki shallwani', 'advertising rep', 'team money', '26', 'aurora , illinois', '6th place'], ['lawrence musso', 'bartender / entrepreneur', 'team power', '23', 'brooklyn , new york', '7th place'], ['jennifer jenn', 'merchandising major', 'team money', '18', 'san diego , california', '8th place'], ['dajuan watkins', 'independent promoter', 'team power', '22', 'gary , indiana', '9th place'], ['rebecca clark', 'yoga instructor', 'team power', '21', 'santa monica , california', '10th place'], ['precious bogard', 'small business owner', 'team money', '20', 'lancaster , california', '11th place'], ['nima blue eyes', 'advertising rep', 'team money', '21', 'thousand oaks , california', '12th place'], ['nathan strickland', 'marketing director', 'team power', '20', 'calhoun , georgia', '13th place']] |
miss united continent | https://en.wikipedia.org/wiki/Miss_United_Continent | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17522854-6.html.csv | ordinal | the dominican republic was ranked 1st in the miss united continent . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'rank', '1'], 'result': '1', 'ind': 0, 'tostr': 'nth_min { all_rows ; rank ; 1 }', 'tointer': 'the 1st minimum rank record of all rows is 1 .'}, '1'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; rank ; 1 } ; 1 }', 'tointer': 'the 1st minimum rank record of all rows is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'rank', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; rank ; 1 }'}, 'country'], 'result': 'dominican republic', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 1 } ; country }'}, 'dominican republic'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 1 } ; country } ; dominican republic }', 'tointer': 'the country record of the row with 1st minimum rank record is dominican republic .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; rank ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; rank ; 1 } ; country } ; dominican republic } } = true', 'tointer': 'the 1st minimum rank record of all rows is 1 . the country record of the row with 1st minimum rank record is dominican republic .'} | and { eq { nth_min { all_rows ; rank ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; rank ; 1 } ; country } ; dominican republic } } = true | the 1st minimum rank record of all rows is 1 . the country record of the row with 1st minimum rank record is dominican republic . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'rank_8': 8, '1_9': 9, '1_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'rank_12': 12, '1_13': 13, 'country_14': 14, 'dominican republic_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'rank_8': 'rank', '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', 'rank_12': 'rank', '1_13': '1', 'country_14': 'country', 'dominican republic_15': 'dominican republic'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'rank_8': [0], '1_9': [0], '1_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'rank_12': [2], '1_13': [2], 'country_14': [3], 'dominican republic_15': [4]} | ['rank', 'country', 'miss united continent', 'virreina', '1st ru', '2nd ru', '3rd ru', '4th ru', 'semifinalists', 'total'] | [['1', 'dominican republic', '2', '1', '0', '0', '0', '0', '2', '5'], ['2', 'ecuador', '2', '0', '2', '0', '0', '0', '1', '5'], ['3', 'mexico', '1', '1', '2', '0', '0', '0', '1', '5'], ['4', 'brazil', '1', '1', '1', '0', '0', '0', '3', '6'], ['5', 'colombia', '1', '0', '0', '0', '0', '0', '3', '4'], ['6', 'peru', '1', '0', '0', '0', '0', '0', '2', '3'], ['7', 'venezuela', '0', '1', '1', '0', '0', '0', '4', '6'], ['8', 'panama', '0', '1', '0', '0', '0', '1', '2', '4'], ['9', 'puerto rico', '0', '1', '0', '0', '0', '0', '1', '2'], ['10', 'uruguay', '0', '1', '0', '0', '1', '0', '0', '2'], ['11', 'india', '0', '1', '0', '0', '0', '0', '0', '1'], ['12', 'chile', '0', '0', '1', '0', '0', '0', '1', '2'], ['13', 'argentina', '0', '0', '1', '0', '0', '0', '0', '1'], ['14', 'belgium', '0', '0', '0', '1', '0', '0', '0', '1'], ['15', 'canada', '0', '0', '0', '0', '0', '0', '1', '1'], ['15', 'honduras', '0', '0', '0', '0', '0', '0', '1', '1'], ['15', 'costa rica', '0', '0', '0', '0', '0', '0', '1', '1'], ['15', 'paraguay', '0', '0', '0', '0', '0', '0', '1', '1']] |
hyperon | https://en.wikipedia.org/wiki/Hyperon | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1129026-1.html.csv | aggregation | the average rest mass of hyperon particles is about 1352 mev/c 2 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1352', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'rest mass mev / c 2'], 'result': '1352', 'ind': 0, 'tostr': 'avg { all_rows ; rest mass mev / c 2 }'}, '1352'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; rest mass mev / c 2 } ; 1352 } = true', 'tointer': 'the average of the rest mass mev / c 2 record of all rows is 1352 .'} | round_eq { avg { all_rows ; rest mass mev / c 2 } ; 1352 } = true | the average of the rest mass mev / c 2 record of all rows is 1352 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'rest mass mev / c 2_4': 4, '1352_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'rest mass mev / c 2_4': 'rest mass mev / c 2', '1352_5': '1352'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'rest mass mev / c 2_4': [0], '1352_5': [1]} | ['particle', 'symbol', 'makeup', 'rest mass mev / c 2', 'isospin i', 'spin ( parity ) j p', 'commonly decays to'] | [['lambda', 'λ 0', 'u d s', '1 115.683 ( 6 )', '0', '1⁄2 +', 'p + + π or n 0 + π 0'], ['sigma', 'σ +', 'u u s', '1189.37 ( 0.7 )', '1', '1⁄2 +', 'p + + π 0 or n 0 + π +'], ['sigma', 'σ 0', 'u d s', '1192.642 ( 24 )', '1', '1⁄2 +', 'λ 0 + γ'], ['sigma', 'σ', 'd d s', '1197.449 ( 30 )', '1', '1⁄2 +', 'n 0 + π'], ['sigma resonance', 'σ ∗ + ( 1385 )', 'u u s', '1382.8 ( 4 )', '1', '3⁄2 +', 'λ + π or σ + π'], ['sigma resonance', 'σ ∗ 0 ( 1385 )', 'u d s', '1383.7 ± 1.0', '1', '3⁄2 +', 'λ + π or σ + π'], ['sigma resonance', 'σ ∗ ( 1385 )', 'd d s', '1387.2 ( 5 )', '1', '3⁄2 +', 'λ + π or σ + π'], ['xi', 'ξ 0', 'u s s', '1314.83 ( 20 )', '1⁄2', '1⁄2 +', 'λ 0 + π 0'], ['xi', 'ξ', 'd s s', '1321.31 ( 13 )', '1⁄2', '1⁄2 +', 'λ 0 + π'], ['xi resonance', 'ξ ∗ 0 ( 1530 )', 'u s s', '1531.80 ( 32 )', '1⁄2', '3⁄2 +', 'ξ + π'], ['xi resonance', 'ξ ∗ ( 1530 )', 'd s s', '1535.0 ( 6 )', '1⁄2', '3⁄2 +', 'ξ + π'], ['omega', 'ω', 's s s', '1672.45 ( 29 )', '0', '3⁄2 +', 'λ 0 + k or ξ 0 + π or ξ + π 0']] |
luke donald | https://en.wikipedia.org/wiki/Luke_Donald | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1590652-4.html.csv | ordinal | luke donald 's second highest golf tournament winning score was 272 . | {'row': '1', 'col': '4', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'winning score', '2'], 'result': '69 + 65 + 69 + 69 = 272', 'ind': 0, 'tostr': 'nth_max { all_rows ; winning score ; 2 }', 'tointer': 'the 2nd maximum winning score record of all rows is 69 + 65 + 69 + 69 = 272 .'}, '69 + 65 + 69 + 69 = 272'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; winning score ; 2 } ; 69 + 65 + 69 + 69 = 272 } = true', 'tointer': 'the 2nd maximum winning score record of all rows is 69 + 65 + 69 + 69 = 272 .'} | eq { nth_max { all_rows ; winning score ; 2 } ; 69 + 65 + 69 + 69 = 272 } = true | the 2nd maximum winning score record of all rows is 69 + 65 + 69 + 69 = 272 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_max_0': 0, 'all_rows_3': 3, 'winning score_4': 4, '2_5': 5, '69 + 65 + 69 + 69 = 272_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_max_0': 'nth_max', 'all_rows_3': 'all_rows', 'winning score_4': 'winning score', '2_5': '2', '69 + 65 + 69 + 69 = 272_6': '69 + 65 + 69 + 69 = 272'} | {'eq_1': [2], 'result_2': [], 'nth_max_0': [1], 'all_rows_3': [0], 'winning score_4': [0], '2_5': [0], '69 + 65 + 69 + 69 = 272_6': [1]} | ['no', 'date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up'] | [['1', '1 aug 2004', 'scandinavian masters by carlsberg', '69 + 65 + 69 + 69 = 272', '16', '5 strokes', 'peter hanson'], ['2', '5 sep 2004', 'omega european masters', '67 + 67 + 65 + 66 = 265', '19', '5 strokes', 'miguel ángel jiménez'], ['3', '30 may 2010', 'madrid masters', '65 + 67 + 68 + 67 = 267', '21', '1 stroke', 'rhys davies'], ['4', '27 feb 2011', 'wgc - accenture match play championship', '3 and 2', '3 and 2', '3 and 2', 'martin kaymer'], ['5', '29 may 2011', 'bmw pga championship', '64 + 72 + 72 + 70 = 278', '6', 'playoff', 'lee westwood'], ['6', '10 jul 2011', 'barclays scottish open', '67 + 67 + 63 = 197', '19', '4 strokes', 'fredrik andersson hed']] |
roberto moreno | https://en.wikipedia.org/wiki/Roberto_Moreno | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226554-3.html.csv | aggregation | from 1982 to 1995 , roberto moreno earned an average of 3.92 points per race . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '3.92', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '3.92', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '3.92'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 3.92 } = true', 'tointer': 'the average of the points record of all rows is 3.92 .'} | round_eq { avg { all_rows ; points } ; 3.92 } = true | the average of the points record of all rows is 3.92 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '3.92_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '3.92_5': '3.92'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '3.92_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1982', 'john player lotus', 'lotus 91', 'cosworth v8', '0'], ['1987', 'team ags', 'ags jh22', 'cosworth v8', '1'], ['1989', 'coloni spa', 'coloni fc188b', 'cosworth v8', '0'], ['1989', 'coloni spa', 'coloni c3', 'cosworth v8', '0'], ['1990', 'eurobrun racing', 'eurobrun er189', 'judd v8', '6'], ['1990', 'eurobrun racing', 'eurobrun er189b', 'judd v8', '6'], ['1990', 'benetton formula', 'benetton b190', 'ford v8', '6'], ['1991', 'camel benetton ford', 'benetton b190b', 'ford v8', '8'], ['1991', 'camel benetton ford', 'benetton b191', 'ford v8', '8'], ['1991', 'team 7up jordan', 'jordan 191', 'ford v8', '8'], ['1991', 'minardi team', 'minardi m191', 'ferrari v12', '8'], ['1992', 'andrea moda formula', 'andrea moda s921', 'judd v10', '0'], ['1995', 'parmalat forti ford', 'forti fg01', 'ford v8', '0']] |
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/1-17355408-9.html.csv | unique | during this period of the 2008-09 denver nuggets season , the denver nuggets experienced their only loss against the la lakers on april 9th . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to l .', 'tostr': 'filter_eq { all_rows ; score ; l }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; l } }', 'tointer': 'select the rows whose score record fuzzily matches to l . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to l .', 'tostr': 'filter_eq { all_rows ; score ; l }'}, 'team'], 'result': 'la lakers', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; l } ; team }'}, 'la lakers'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; l } ; team } ; la lakers }', 'tointer': 'the team record of this unqiue row is la lakers .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; l } } ; eq { hop { filter_eq { all_rows ; score ; l } ; team } ; la lakers } } = true', 'tointer': 'select the rows whose score record fuzzily matches to l . there is only one such row in the table . the team record of this unqiue row is la lakers .'} | and { only { filter_eq { all_rows ; score ; l } } ; eq { hop { filter_eq { all_rows ; score ; l } ; team } ; la lakers } } = true | select the rows whose score record fuzzily matches to l . there is only one such row in the table . the team record of this unqiue row is la lakers . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, 'l_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'la lakers_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', 'l_8': 'l', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'la lakers_10': 'la lakers'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], 'l_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'la lakers_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 2', 'utah', 'w 114 - 104 ( ot )', 'j r smith ( 28 )', 'chris andersen ( 10 )', 'j r smith ( 7 )', 'pepsi center 17969', '50 - 26'], ['77', 'april 4', 'la clippers', 'w 120 - 104 ( ot )', 'j r smith ( 34 )', 'chris andersen ( 8 )', 'chauncey billups ( 9 )', 'pepsi center 17880', '51 - 26'], ['78', 'april 5', 'minnesota', 'w 110 - 87 ( ot )', 'carmelo anthony ( 23 )', 'carmelo anthony , chris andersen ( 8 )', 'chauncey billups ( 7 )', 'target center 16839', '52 - 26'], ['79', 'april 8', 'oklahoma city', 'w 122 - 112 ( ot )', 'carmelo anthony ( 31 )', 'nenê ( 10 )', 'chauncey billups ( 9 )', 'pepsi center 16536', '53 - 26'], ['80', 'april 9', 'la lakers', 'l 102 - 116 ( ot )', 'carmelo anthony ( 23 )', 'nenê ( 10 )', 'chauncey billups ( 8 )', 'staples center 18997', '53 - 27'], ['81', 'april 13', 'sacramento', 'w 118 - 98 ( ot )', 'j r smith ( 45 )', 'chris andersen ( 10 )', 'carmelo anthony ( 9 )', 'pepsi center 15823', '54 - 27']] |
list of lancashire county cricket club records | https://en.wikipedia.org/wiki/List_of_Lancashire_County_Cricket_Club_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14176339-7.html.csv | majority | most of the records include a score of over 350 runs . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '350', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'score', '350'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them are greater than 350 .', 'tostr': 'most_greater { all_rows ; score ; 350 } = true'} | most_greater { all_rows ; score ; 350 } = true | for the score records of all rows , most of them are greater than 350 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '350_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '350_4': '350'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '350_4': [0]} | ['score', 'opposition', 'venue', 'city', 'year'] | [['423 runs', 'somerset', 'aigurth', 'liverpool', '1911'], ['385 runs', 'somerset', 'aigburth', 'liverpool', '1908'], ['372 runs', 'worcestershire', 'amblecote', 'stourbridge', '1911'], ['370 runs', 'oxford university', 'the university parks', 'oxford', '1985'], ['361 runs', 'middlesex', 'old trafford', 'manchester', '1994'], ['350 runs', 'durham', 'riverside ground', 'chester - le - street', '1998'], ['345 runs', 'durham', 'riverside ground', 'chester - le - street', '1996'], ['336 runs', 'somerset', 'stanley park', 'blackpool', '2002']] |
list of list a cricket records | https://en.wikipedia.org/wiki/List_of_List_A_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11303072-5.html.csv | count | a total of two different batting duos scored exactly 203 runs in the cricket records . | {'scope': 'all', 'criterion': 'equal', 'value': '203', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'runs', '203'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runs record is equal to 203 .', 'tostr': 'filter_eq { all_rows ; runs ; 203 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; runs ; 203 } }', 'tointer': 'select the rows whose runs record is equal to 203 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; runs ; 203 } } ; 2 } = true', 'tointer': 'select the rows whose runs record is equal to 203 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; runs ; 203 } } ; 2 } = true | select the rows whose runs record is equal to 203 . 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, 'runs_5': 5, '203_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'runs_5': 'runs', '203_6': '203', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'runs_5': [0], '203_6': [0], '2_7': [2]} | ['wicket', 'runs', 'batting partners', 'batting team', 'fielding team', 'venue', 'season'] | [['1st', '326', 'ghulam ali and sohail jaffar', 'pakistan international airlines', 'agriculture development bank', 'jinnah stadium , sialkot', '2000 - 01'], ['2nd', '331', 'sachin tendulkar and rahul dravid', 'india', 'new zealand', 'lal bahadur shastri stadium , hyderabad', '1999 - 00'], ['3rd', '309', 'tim curtis and tom moody', 'worcestershire', 'surrey', 'the oval , london', '1994'], ['4th', '276', 'mominul haque and roshen silva', 'prime doleshwar', 'abahani limited', 'shaheed chandu stadium , bogra', '2013 - 14'], ['5th', '267', 'minhajul abedin and khaled mahmud', 'bangladesh', 'bahawalpur', 'united bank limited sports complex , karachi', '1997 - 98'], ['6th', '226', 'nigel llong and matthew fleming', 'kent', 'cheshire', 'south downs road , bowdon', '1999'], ['7th', '203', 'thilina kandamby and rangana herath', 'sri lanka a', 'south africa a', 'willowmoore park , benoni', '2008'], ['8th', '203', 'shahid iqbal and haaris ayaz', 'karachi whites', 'hyderabad', 'united bank limited sports complex , karachi', '1998 - 99'], ['9th', '155', 'chris read and andrew harris', 'nottinghamshire', 'durham', 'trent bridge , nottingham', '2006']] |
norwegian european communities membership referendum , 1972 | https://en.wikipedia.org/wiki/Norwegian_European_Communities_membership_referendum%2C_1972 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1289762-1.html.csv | comparative | nordland had a higher number electorate than troms in the 1972 nowegian european communities membership referendum . | {'row_1': '17', 'row_2': '18', 'col': '2', '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', 'constituency', 'nordland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constituency record fuzzily matches to nordland .', 'tostr': 'filter_eq { all_rows ; constituency ; nordland }'}, 'electorate'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; constituency ; nordland } ; electorate }', 'tointer': 'select the rows whose constituency record fuzzily matches to nordland . take the electorate record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constituency', 'troms'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose constituency record fuzzily matches to troms .', 'tostr': 'filter_eq { all_rows ; constituency ; troms }'}, 'electorate'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; constituency ; troms } ; electorate }', 'tointer': 'select the rows whose constituency record fuzzily matches to troms . take the electorate record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; constituency ; nordland } ; electorate } ; hop { filter_eq { all_rows ; constituency ; troms } ; electorate } } = true', 'tointer': 'select the rows whose constituency record fuzzily matches to nordland . take the electorate record of this row . select the rows whose constituency record fuzzily matches to troms . take the electorate record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; constituency ; nordland } ; electorate } ; hop { filter_eq { all_rows ; constituency ; troms } ; electorate } } = true | select the rows whose constituency record fuzzily matches to nordland . take the electorate record of this row . select the rows whose constituency record fuzzily matches to troms . take the electorate 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, 'constituency_7': 7, 'nordland_8': 8, 'electorate_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'constituency_11': 11, 'troms_12': 12, 'electorate_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', 'constituency_7': 'constituency', 'nordland_8': 'nordland', 'electorate_9': 'electorate', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'constituency_11': 'constituency', 'troms_12': 'troms', 'electorate_13': 'electorate'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'constituency_7': [0], 'nordland_8': [0], 'electorate_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'constituency_11': [1], 'troms_12': [1], 'electorate_13': [3]} | ['constituency', 'electorate', 's spoilt vote', 'total poll ( % )', 'for ( % )', 'against ( % )'] | [['østfold', '152837', '392', '121498 ( 80 )', '58931 ( 49 )', '62567 ( 51 )'], ['akershus', '217851', '542', '180503 ( 83 )', '102521 ( 57 )', '77982 ( 43 )'], ['oslo', '356153', '619', '291654 ( 82 )', '193980 ( 67 )', '97674 ( 33 )'], ['hedmark', '124960', '519', '99508 ( 80 )', '44150 ( 44 )', '55358 ( 56 )'], ['oppland', '120082', '314', '94114 ( 79 )', '37550 ( 40 )', '56564 ( 60 )'], ['buskerud', '139999', '400', '110387 ( 79 )', '59532 ( 54 )', '50855 ( 46 )'], ['vestfold', '155338', '247', '94355 ( 79 )', '53515 ( 57 )', '40840 ( 43 )'], ['telemark', '108485', '211', '84056 ( 78 )', '32284 ( 38 )', '51772 ( 62 )'], ['aust - agder', '55276', '138', '40909 ( 74 )', '18659 ( 46 )', '22250 ( 54 )'], ['vest - agder', '81707', '177', '64100 ( 79 )', '27510 ( 43 )', '36590 ( 57 )'], ['rogaland', '174925', '309', '138601 ( 79 )', '62096 ( 45 )', '76505 ( 55 )'], ['hordaland', '248675', '511', '198095 ( 80 )', '96996 ( 49 )', '101099 ( 51 )'], ['sogn og fjordane', '67335', '153', '51705 ( 77 )', '15923 ( 31 )', '35782 ( 69 )'], ['møre og romsdal', '146917', '240', '114709 ( 78 )', '33504 ( 29 )', '81205 ( 71 )'], ['sør - trøndelag', '159730', '248', '122092 ( 77 )', '51827 ( 42 )', '70265 ( 58 )'], ['nord - trøndelag', '77954', '107', '60495 ( 78 )', '19101 ( 32 )', '41394 ( 68 )'], ['nordland', '157183', '549', '120979 ( 77 )', '33228 ( 27 )', '87751 ( 73 )'], ['troms', '88174', '385', '66499 ( 76 )', '19820 ( 30 )', '46679 ( 70 )']] |
1987 world rhythmic gymnastics championships | https://en.wikipedia.org/wiki/1987_World_Rhythmic_Gymnastics_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18170681-5.html.csv | unique | the only participant in the 1987 world rhythmic gymnastics championships to receive a 9.700 in rope is maria isabel lloret . | {'scope': 'all', 'row': '8', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '9.7', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rope', '9.7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rope record is equal to 9.7 .', 'tostr': 'filter_eq { all_rows ; rope ; 9.7 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; rope ; 9.7 } }', 'tointer': 'select the rows whose rope record is equal to 9.7 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rope', '9.7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rope record is equal to 9.7 .', 'tostr': 'filter_eq { all_rows ; rope ; 9.7 }'}, 'name'], 'result': 'maria isabel lloret', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; rope ; 9.7 } ; name }'}, 'maria isabel lloret'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; rope ; 9.7 } ; name } ; maria isabel lloret }', 'tointer': 'the name record of this unqiue row is maria isabel lloret .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; rope ; 9.7 } } ; eq { hop { filter_eq { all_rows ; rope ; 9.7 } ; name } ; maria isabel lloret } } = true', 'tointer': 'select the rows whose rope record is equal to 9.7 . there is only one such row in the table . the name record of this unqiue row is maria isabel lloret .'} | and { only { filter_eq { all_rows ; rope ; 9.7 } } ; eq { hop { filter_eq { all_rows ; rope ; 9.7 } ; name } ; maria isabel lloret } } = true | select the rows whose rope record is equal to 9.7 . there is only one such row in the table . the name record of this unqiue row is maria isabel lloret . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'rope_7': 7, '9.7_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'maria isabel lloret_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'rope_7': 'rope', '9.7_8': '9.7', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'maria isabel lloret_10': 'maria isabel lloret'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'rope_7': [0], '9.7_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'maria isabel lloret_10': [3]} | ['place', 'name', 'all around', 'rope', 'total'] | [['1', 'adriana dunavska', '10.000', '10.000', '20.000'], ['1', 'bianka panova', '10.000', '10.000', '20.000'], ['3', 'anna kotchneva', '9.900', '9.900', '19.800'], ['3', 'marina lobatch', '9.900', '9.900', '19.800'], ['5', 'florentina butaru', '9.800', '9.900', '19.700'], ['6', 'milena reljin', '9.800', '9.750', '19.550'], ['7', 'andrea sinko', '9.700', '9.800', '19.500'], ['8', 'maria isabel lloret', '9.700', '9.700', '19.400']] |
list of ngc objects ( 6001 - 7000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%286001%E2%80%937000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11051842-3.html.csv | majority | the majority of the object types are labeled globular clusters . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'globular cluster', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'object type', 'globular cluster'], 'result': True, 'ind': 0, 'tointer': 'for the object type records of all rows , most of them fuzzily match to globular cluster .', 'tostr': 'most_eq { all_rows ; object type ; globular cluster } = true'} | most_eq { all_rows ; object type ; globular cluster } = true | for the object type records of all rows , most of them fuzzily match to globular cluster . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'object type_3': 3, 'globular cluster_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'object type_3': 'object type', 'globular cluster_4': 'globular cluster'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'object type_3': [0], 'globular cluster_4': [0]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )', 'apparent magnitude'] | [['6205', 'globular cluster', 'hercules', '16h41 m41s', 'degree27 ′ 37 ″', '5.8'], ['6210', 'planetary nebula', 'hercules', '16h44 m29 .5 s', 'degree48 ′ 00 ″', '12.3'], ['6218', 'globular cluster', 'ophiuchus', '16h47 m14 .5 s', 'degree56 ′ 52 ″', '8.5'], ['6231', 'open cluster', 'scorpius', '16h54 m08 .5 s', 'degree49 ′ 36 ″', '2.8'], ['6240', 'irregular galaxy', 'ophiuchus', '16h52 m59 .0 s', 'degree24 ′ 02 ″', '14.7'], ['6242', 'open cluster', 'scorpius', '16h55 m', 'degree28 ′', '7.1'], ['6254', 'globular cluster', 'ophiuchus', '16h57 m09 .0 s', 'degree05 ′ 58 ″', '6.4'], ['6266', 'globular cluster', 'ophiuchus', '17h01 m12 .6 s', 'degree06 ′ 45 ″', '8.6'], ['6273', 'globular cluster', 'ophiuchus', '17h02 m37 .7 s', 'degree16 ′ 05 ″', '8.5']] |
1960 dallas cowboys season | https://en.wikipedia.org/wiki/1960_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17946716-1.html.csv | superlative | the highest attended dallas cowboys game in 1960 was against the new york giants . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '11', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'new york giants', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'new york giants'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; opponent } ; new york giants } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the opponent record of this row is new york giants .'} | eq { hop { argmax { all_rows ; attendance } ; opponent } ; new york giants } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is new york giants . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'new york giants_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', 'opponent_6': 'opponent', 'new york giants_7': 'new york giants'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'new york giants_7': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 24 , 1960', 'pittsburgh steelers', 'l 28 - 35', 'cotton bowl', '0 - 1', '30000'], ['2', 'september 30 , 1960', 'philadelphia eagles', 'l 25 - 27', 'cotton bowl', '0 - 2', '18500'], ['3', 'october 9 , 1960', 'washington redskins', 'l 14 - 26', 'griffith stadium', '0 - 3', '21142'], ['4', 'october 16 , 1960', 'cleveland browns', 'l 7 - 48', 'cotton bowl', '0 - 4', '28500'], ['5', 'october 23 , 1960', 'st louis cardinals', 'l 10 - 12', 'busch stadium', '0 - 5', '23128'], ['6', 'october 30 , 1960', 'baltimore colts', 'l 7 - 45', 'cotton bowl', '0 - 6', '25500'], ['7', 'november 6 , 1960', 'los angeles rams', 'l 13 - 38', 'cotton bowl', '0 - 7', '16000'], ['8', 'november 13 , 1960', 'green bay packers', 'l 7 - 41', 'lambeau field', '0 - 8', '32294'], ['9', 'november 20 , 1960', 'san francisco 49ers', 'l 14 - 26', 'cotton bowl', '0 - 9', '10000'], ['10', 'november 27 , 1960', 'chicago bears', 'l 7 - 17', 'wrigley field', '0 - 10', '39951'], ['11', 'december 4 , 1960', 'new york giants', 't 31 - 31', 'yankee stadium', '0 - 10 - 1', '55033'], ['12', 'december 11 , 1960', 'detroit lions', 'l 14 - 23', 'briggs stadium', '0 - 11 - 1', '43272'], ['13', '-', '-', '-', '-', '-', '']] |
russian football premier league | https://en.wikipedia.org/wiki/Russian_Football_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1167698-1.html.csv | comparative | dynamo moscow was the runner-up before lokomotiv moscow was . | {'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', 'runner - up', 'dynamo moscow'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runner - up record fuzzily matches to dynamo moscow .', 'tostr': 'filter_eq { all_rows ; runner - up ; dynamo moscow }'}, 'season'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; runner - up ; dynamo moscow } ; season }', 'tointer': 'select the rows whose runner - up record fuzzily matches to dynamo moscow . take the season record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner - up', 'lokomotiv moscow'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose runner - up record fuzzily matches to lokomotiv moscow .', 'tostr': 'filter_eq { all_rows ; runner - up ; lokomotiv moscow }'}, 'season'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; runner - up ; lokomotiv moscow } ; season }', 'tointer': 'select the rows whose runner - up record fuzzily matches to lokomotiv moscow . take the season record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; runner - up ; dynamo moscow } ; season } ; hop { filter_eq { all_rows ; runner - up ; lokomotiv moscow } ; season } } = true', 'tointer': 'select the rows whose runner - up record fuzzily matches to dynamo moscow . take the season record of this row . select the rows whose runner - up record fuzzily matches to lokomotiv moscow . take the season record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; runner - up ; dynamo moscow } ; season } ; hop { filter_eq { all_rows ; runner - up ; lokomotiv moscow } ; season } } = true | select the rows whose runner - up record fuzzily matches to dynamo moscow . take the season record of this row . select the rows whose runner - up record fuzzily matches to lokomotiv moscow . take the season 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, 'runner - up_7': 7, 'dynamo moscow_8': 8, 'season_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'runner - up_11': 11, 'lokomotiv moscow_12': 12, 'season_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', 'runner - up_7': 'runner - up', 'dynamo moscow_8': 'dynamo moscow', 'season_9': 'season', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'runner - up_11': 'runner - up', 'lokomotiv moscow_12': 'lokomotiv moscow', 'season_13': 'season'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'runner - up_7': [0], 'dynamo moscow_8': [0], 'season_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'runner - up_11': [1], 'lokomotiv moscow_12': [1], 'season_13': [3]} | ['season', 'champion', 'runner - up', 'third place', 'top scorer'] | [['1994', 'spartak moscow ( 3 )', 'dynamo moscow', 'lokomotiv moscow', 'igor simutenkov ( dinamo moscow , 21 goals )'], ['1995', 'alania vladikavkaz', 'lokomotiv moscow', 'spartak moscow', 'oleg veretennikov ( rotor volgograd , 25 goals )'], ['1996', 'spartak moscow ( 4 )', 'alania vladikavkaz', 'rotor volgograd', 'aleksandr maslov ( rostselmash , 23 goals )'], ['1997', 'spartak moscow ( 5 )', 'rotor volgograd', 'dynamo moscow', 'oleg veretennikov ( rotor volgograd , 22 goals )'], ['1998', 'spartak moscow ( 6 )', 'cska moscow', 'lokomotiv moscow', 'oleg veretennikov ( rotor volgograd , 22 goals )'], ['1999', 'spartak moscow ( 7 )', 'lokomotiv moscow', 'cska moscow', 'georgi demetradze ( alania vladikavkaz , 21 goals )'], ['2000', 'spartak moscow ( 8 )', 'lokomotiv moscow', 'torpedo moscow', 'dmitri loskov ( lokomotiv moscow , 18 goals )'], ['2001', 'spartak moscow ( 9 )', 'lokomotiv moscow', 'zenit saint petersburg', 'dmitri vyazmikin ( torpedo moscow , 18 goals )'], ['2003', 'cska moscow', 'zenit saint petersburg', 'rubin kazan', 'dmitri loskov ( lokomotiv moscow , 14 goals )'], ['2005', 'cska moscow ( 2 )', 'spartak moscow', 'lokomotiv moscow', 'dmitri kirichenko ( fc moscow , 14 goals )'], ['2006', 'cska moscow ( 3 )', 'spartak moscow', 'lokomotiv moscow', 'roman pavlyuchenko ( spartak moscow , 18 goals )'], ['2008', 'rubin kazan', 'cska moscow', 'dynamo moscow', 'vã ¡ gner love ( cska moscow , 20 goals )'], ['2009', 'rubin kazan ( 2 )', 'spartak moscow', 'zenit saint petersburg', 'welliton ( spartak moscow , 21 goals )'], ['2010', 'zenit saint petersburg ( 2 )', 'cska moscow', 'rubin kazan', 'welliton ( spartak moscow , 19 goals )']] |
ji \ xc5 \ x99 \ xc3 \ xad nov \ xc3 \ xa1k | https://en.wikipedia.org/wiki/Ji%C5%99%C3%AD_Nov%C3%A1k | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1554049-2.html.csv | count | three of jin novak 's seven first place singles wins were in switzerland . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'switzerland', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'switzerland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to switzerland .', 'tostr': 'filter_eq { all_rows ; tournament ; switzerland }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tournament ; switzerland } }', 'tointer': 'select the rows whose tournament record fuzzily matches to switzerland . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tournament ; switzerland } } ; 3 } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to switzerland . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; tournament ; switzerland } } ; 3 } = true | select the rows whose tournament record fuzzily matches to switzerland . 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, 'tournament_5': 5, 'switzerland_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', 'tournament_5': 'tournament', 'switzerland_6': 'switzerland', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tournament_5': [0], 'switzerland_6': [0], '3_7': [2]} | ['date', 'tournament', 'surface', 'opponent', 'score'] | [['january 14 , 1996', 'auckland , new zealand', 'hard', 'brett steven', '6 - 4 , 6 - 4'], ['november 1 , 1998', 'mexico city , mexico', 'clay', 'xavier malisse', '6 - 3 , 6 - 3'], ['may 6 , 2001', 'munich , germany', 'clay', 'antony dupuis', '6 - 4 , 7 - 5'], ['july 15 , 2001', 'gstaad , switzerland', 'clay', 'juan carlos ferrero', '6 - 1 , 6 - 7 ( 5 - 7 ) , 7 - 5'], ['july 13 , 2003', 'gstaad , switzerland', 'clay', 'roger federer', '5 - 7 , 6 - 3 , 6 - 3 , 1 - 6 , 6 - 3'], ['october 10 , 2004', 'tokyo , japan', 'hard', 'taylor dent', '5 - 7 , 6 - 1 , 6 - 3'], ['november 3 , 2004', 'basel , switzerland', 'carpet ( i )', 'david nalbandian', '5 - 7 , 6 - 3 , 6 - 4 , 1 - 6 , 6 - 2']] |
2010 - 11 detroit pistons season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Detroit_Pistons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27755603-7.html.csv | majority | the majority of the games ended in losses for the detroit pistons . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; score ; l } = true'} | most_eq { all_rows ; score ; l } = true | for the score 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, 'score_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], 'l_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['20', 'december 3', 'orlando', 'l 91 - 104 ( ot )', 'tayshaun prince ( 30 )', 'ben gordon ( 9 )', 'rodney stuckey ( 7 )', 'the palace of auburn hills 18433', '6 - 14'], ['21', 'december 5', 'cleveland', 'w 102 - 92 ( ot )', 'richard hamilton ( 27 )', 'ben wallace ( 9 )', 'rodney stuckey ( 11 )', 'the palace of auburn hills 13081', '7 - 14'], ['22', 'december 7', 'houston', 'l 83 - 97 ( ot )', 'rodney stuckey ( 18 )', 'tayshaun prince , ben wallace ( 8 )', 'rodney stuckey ( 5 )', 'toyota center 14798', '7 - 15'], ['23', 'december 8', 'new orleans', 'l 74 - 93 ( ot )', 'ben gordon ( 19 )', 'ben wallace ( 7 )', 'tracy mcgrady ( 3 )', 'new orleans arena 10823', '7 - 16'], ['24', 'december 10', 'minnesota', 'l 99 - 109 ( ot )', 'richard hamilton ( 26 )', 'greg monroe ( 15 )', 'rodney stuckey ( 6 )', 'target center 13988', '7 - 17'], ['25', 'december 11', 'toronto', 'l 116 - 120 ( ot )', 'rodney stuckey , ben wallace ( 23 )', 'ben wallace ( 14 )', 'rodney stuckey ( 12 )', 'the palace of auburn hills 13343', '7 - 18'], ['26', 'december 14', 'atlanta', 'w 103 - 80 ( ot )', 'richard hamilton ( 24 )', 'charlie villanueva ( 11 )', 'rodney stuckey ( 10 )', 'the palace of auburn hills 12526', '8 - 18'], ['27', 'december 17', 'la clippers', 'l 88 - 109 ( ot )', 'charlie villanueva ( 18 )', 'charlie villanueva ( 9 )', 'tracy mcgrady ( 5 )', 'the palace of auburn hills 16046', '8 - 19'], ['28', 'december 19', 'new orleans', 'w 111 - 108 ( ot )', 'tayshaun prince ( 28 )', 'tayshaun prince ( 12 )', 'will bynum ( 9 )', 'the palace of auburn hills 16452', '9 - 19'], ['29', 'december 22', 'toronto', 'w 115 - 93 ( ot )', 'richard hamilton ( 35 )', 'tracy mcgrady ( 7 )', 'tracy mcgrady ( 7 )', 'air canada centre 15303', '10 - 19'], ['30', 'december 26', 'chicago', 'l 92 - 95 ( ot )', 'tayshaun prince ( 17 )', 'charlie villanueva ( 10 )', 'tayshaun prince ( 6 )', 'the palace of auburn hills 20765', '10 - 20'], ['31', 'december 27', 'charlotte', 'l 100 - 105 ( ot )', 'charlie villanueva ( 25 )', 'chris wilcox ( 8 )', 'will bynum ( 7 )', 'time warner cable arena 14418', '10 - 21'], ['32', 'december 29', 'boston', 'w 104 - 92 ( ot )', 'tracy mcgrady ( 21 )', 'chris wilcox ( 8 )', 'tracy mcgrady ( 8 )', 'the palace of auburn hills 22076', '11 - 21']] |
wru division two east | https://en.wikipedia.org/wiki/WRU_Division_Two_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12807904-3.html.csv | superlative | the gilfach goch rfc club had the most points in the wru division two east league games . | {'scope': 'all', 'col_superlative': '12', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'club'], 'result': 'gilfach goch rfc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; club }'}, 'gilfach goch rfc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; club } ; gilfach goch rfc } = true', 'tointer': 'select the row whose points record of all rows is maximum . the club record of this row is gilfach goch rfc .'} | eq { hop { argmax { all_rows ; points } ; club } ; gilfach goch rfc } = true | select the row whose points record of all rows is maximum . the club record of this row is gilfach goch rfc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'club_6': 6, 'gilfach goch rfc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'club_6': 'club', 'gilfach goch rfc_7': 'gilfach goch rfc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'club_6': [1], 'gilfach goch rfc_7': [2]} | ['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['gilfach goch rfc', '22', '16', '1', '5', '560', '343', '65', '37', '7', '3', '76'], ['treorchy rfc', '22', '15', '0', '7', '636', '382', '79', '44', '10', '2', '72'], ['rhydyfelin rfc', '22', '13', '2', '7', '525', '431', '73', '51', '11', '4', '71'], ['mountain ash rfc', '22', '13', '3', '6', '404', '292', '50', '33', '6', '3', '67'], ['brynmawr rfc', '22', '11', '0', '11', '508', '406', '65', '47', '9', '7', '60'], ['ynysybwl rfc', '22', '10', '0', '12', '416', '453', '55', '54', '7', '5', '52'], ['llantrisant rfc', '22', '10', '1', '11', '438', '532', '54', '69', '5', '5', '52'], ['penallta rfc', '22', '11', '0', '11', '416', '488', '50', '63', '2', '2', '48'], ['llantwit fardre rfc', '22', '10', '1', '11', '392', '470', '50', '60', '2', '1', '45'], ['abercynon rfc', '22', '8', '0', '14', '418', '546', '41', '73', '5', '3', '40'], ['newport saracens rfc', '22', '6', '1', '15', '365', '453', '49', '56', '3', '6', '35'], ['garndiffaith rfc', '22', '4', '1', '17', '393', '675', '45', '89', '5', '4', '27']] |
presidents cup | https://en.wikipedia.org/wiki/Presidents_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122682-1.html.csv | aggregation | at the presidents cup , the winning team averages a score of 19.05 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '19.05', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '19.05', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '19.05'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 19.05 } = true', 'tointer': 'the average of the score record of all rows is 19.05 .'} | round_eq { avg { all_rows ; score } ; 19.05 } = true | the average of the score record of all rows is 19.05 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '19.05_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '19.05_5': '19.05'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '19.05_5': [1]} | ['year', 'venue', 'location', 'winning team', 'score', 'us captain', 'international captain'] | [['2013', 'muirfield village', 'dublin , ohio', 'united states', '18 ½ - 15 ½', 'fred couples', 'nick price'], ['2011', 'royal melbourne golf club', 'melbourne , australia', 'united states', '19 - 15', 'fred couples', 'greg norman'], ['2009', 'harding park golf club', 'san francisco , california', 'united states', '19 ½ - 14 ½', 'fred couples', 'greg norman'], ['2007', 'royal montreal golf club', 'montreal , canada', 'united states', '19 ½ - 14 ½', 'jack nicklaus', 'gary player'], ['2005', 'robert trent jones golf club', 'gainesville , virginia', 'united states', '18 ½ - 15 ½', 'jack nicklaus', 'gary player'], ['2003', 'fancourt hotel and country club', 'george , western cape , south africa', 'tied', '17 - 17', 'jack nicklaus', 'gary player'], ['2000', 'robert trent jones golf club', 'gainesville , virginia', 'united states', '21 ½ - 10 ½', 'ken venturi', 'peter thomson'], ['1998', 'royal melbourne golf club', 'melbourne , australia', 'international', '20 ½ - 11 ½', 'jack nicklaus', 'peter thomson'], ['1996', 'robert trent jones golf club', 'gainesville , virginia', 'united states', '16 ½ - 15 ½', 'arnold palmer', 'peter thomson'], ['1994', 'robert trent jones golf club', 'gainesville , virginia', 'united states', '20 - 12', 'hale irwin', 'david graham']] |
1957 vfl season | https://en.wikipedia.org/wiki/1957_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-4.html.csv | comparative | the game between collingwood and south melbourne had a bigger crowd than the game between carlton and geelong . | {'row_1': '3', 'row_2': '4', 'col': '6', 'col_other': '1,3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'collingwood'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to collingwood .', 'tostr': 'filter_eq { all_rows ; home team ; collingwood }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; home team ; collingwood } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to collingwood . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'carlton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team record fuzzily matches to carlton .', 'tostr': 'filter_eq { all_rows ; home team ; carlton }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; home team ; carlton } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to carlton . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; home team ; collingwood } ; crowd } ; hop { filter_eq { all_rows ; home team ; carlton } ; crowd } }', 'tointer': 'select the rows whose home team record fuzzily matches to collingwood . take the crowd record of this row . select the rows whose home team record fuzzily matches to carlton . take the crowd record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'collingwood'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to collingwood .', 'tostr': 'filter_eq { all_rows ; home team ; collingwood }'}, 'away team'], 'result': 'south melbourne', 'ind': 5, 'tostr': 'hop { filter_eq { all_rows ; home team ; collingwood } ; away team }'}, 'south melbourne'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; home team ; collingwood } ; away team } ; south melbourne }', 'tointer': 'the away team record of the first row is south melbourne .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'carlton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team record fuzzily matches to carlton .', 'tostr': 'filter_eq { all_rows ; home team ; carlton }'}, 'away team'], 'result': 'geelong', 'ind': 7, 'tostr': 'hop { filter_eq { all_rows ; home team ; carlton } ; away team }'}, 'geelong'], 'result': True, 'ind': 8, 'tostr': 'eq { hop { filter_eq { all_rows ; home team ; carlton } ; away team } ; geelong }', 'tointer': 'the away team record of the second row is geelong .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { hop { filter_eq { all_rows ; home team ; collingwood } ; away team } ; south melbourne } ; eq { hop { filter_eq { all_rows ; home team ; carlton } ; away team } ; geelong } }', 'tointer': 'the away team record of the first row is south melbourne . the away team record of the second row is geelong .'}], 'result': True, 'ind': 10, 'tostr': 'and { greater { hop { filter_eq { all_rows ; home team ; collingwood } ; crowd } ; hop { filter_eq { all_rows ; home team ; carlton } ; crowd } } ; and { eq { hop { filter_eq { all_rows ; home team ; collingwood } ; away team } ; south melbourne } ; eq { hop { filter_eq { all_rows ; home team ; carlton } ; away team } ; geelong } } } = true', 'tointer': 'select the rows whose home team record fuzzily matches to collingwood . take the crowd record of this row . select the rows whose home team record fuzzily matches to carlton . take the crowd record of this row . the first record is greater than the second record . the away team record of the first row is south melbourne . the away team record of the second row is geelong .'} | and { greater { hop { filter_eq { all_rows ; home team ; collingwood } ; crowd } ; hop { filter_eq { all_rows ; home team ; carlton } ; crowd } } ; and { eq { hop { filter_eq { all_rows ; home team ; collingwood } ; away team } ; south melbourne } ; eq { hop { filter_eq { all_rows ; home team ; carlton } ; away team } ; geelong } } } = true | select the rows whose home team record fuzzily matches to collingwood . take the crowd record of this row . select the rows whose home team record fuzzily matches to carlton . take the crowd record of this row . the first record is greater than the second record . the away team record of the first row is south melbourne . the away team record of the second row is geelong . | 13 | 11 | {'and_10': 10, 'result_11': 11, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_12': 12, 'home team_13': 13, 'collingwood_14': 14, 'crowd_15': 15, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_16': 16, 'home team_17': 17, 'carlton_18': 18, 'crowd_19': 19, 'and_9': 9, 'str_eq_6': 6, 'str_hop_5': 5, 'away team_20': 20, 'south melbourne_21': 21, 'str_eq_8': 8, 'str_hop_7': 7, 'away team_22': 22, 'geelong_23': 23} | {'and_10': 'and', 'result_11': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_12': 'all_rows', 'home team_13': 'home team', 'collingwood_14': 'collingwood', 'crowd_15': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_16': 'all_rows', 'home team_17': 'home team', 'carlton_18': 'carlton', 'crowd_19': 'crowd', 'and_9': 'and', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'away team_20': 'away team', 'south melbourne_21': 'south melbourne', 'str_eq_8': 'str_eq', 'str_hop_7': 'str_hop', 'away team_22': 'away team', 'geelong_23': 'geelong'} | {'and_10': [11], 'result_11': [], 'greater_4': [10], 'num_hop_2': [4], 'filter_str_eq_0': [2, 5], 'all_rows_12': [0], 'home team_13': [0], 'collingwood_14': [0], 'crowd_15': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3, 7], 'all_rows_16': [1], 'home team_17': [1], 'carlton_18': [1], 'crowd_19': [3], 'and_9': [10], 'str_eq_6': [9], 'str_hop_5': [6], 'away team_20': [5], 'south melbourne_21': [6], 'str_eq_8': [9], 'str_hop_7': [8], 'away team_22': [7], 'geelong_23': [8]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '6.15 ( 51 )', 'melbourne', '4.9 ( 33 )', 'glenferrie oval', '20000', '11 may 1957'], ['essendon', '11.14 ( 80 )', 'footscray', '4.14 ( 38 )', 'windy hill', '30000', '11 may 1957'], ['collingwood', '14.9 ( 93 )', 'south melbourne', '11.17 ( 83 )', 'victoria park', '32500', '11 may 1957'], ['carlton', '15.12 ( 102 )', 'geelong', '13.11 ( 89 )', 'princes park', '28888', '11 may 1957'], ['st kilda', '16.5 ( 101 )', 'north melbourne', '12.12 ( 84 )', 'junction oval', '20000', '11 may 1957'], ['richmond', '16.10 ( 106 )', 'fitzroy', '10.31 ( 91 )', 'punt road oval', '16500', '11 may 1957']] |
2010 - 11 philadelphia 76ers season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Philadelphia_76ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27698941-2.html.csv | ordinal | the 1st game of the 2010 - 11 philadelphia 76ers season against new jersey was played on october 5 . | {'scope': 'subset', 'row': '1', 'col': '2', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'new jersey'}} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'new jersey'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; new jersey }', 'tointer': 'select the rows whose team record fuzzily matches to new jersey .'}, 'date', '1'], 'result': 'october 5', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; team ; new jersey } ; date ; 1 }', 'tointer': 'select the rows whose team record fuzzily matches to new jersey . the 1st minimum date record of these rows is october 5 .'}, 'october 5'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; team ; new jersey } ; date ; 1 } ; october 5 } = true', 'tointer': 'select the rows whose team record fuzzily matches to new jersey . the 1st minimum date record of these rows is october 5 .'} | eq { nth_min { filter_eq { all_rows ; team ; new jersey } ; date ; 1 } ; october 5 } = true | select the rows whose team record fuzzily matches to new jersey . the 1st minimum date record of these rows is october 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'new jersey_6': 6, 'date_7': 7, '1_8': 8, 'october 5_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'new jersey_6': 'new jersey', 'date_7': 'date', '1_8': '1', 'october 5_9': 'october 5'} | {'eq_2': [3], 'result_3': [], 'nth_min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'new jersey_6': [0], 'date_7': [1], '1_8': [1], 'october 5_9': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['1', 'october 5', 'new jersey', 'l 96 - 103 ( ot )', 'marreese speights ( 19 )', 'marreese speights ( 9 )', 'jrue holiday ( 4 )', 'roanoke civic center 4114', '0 - 1'], ['3', 'october 9', 'new jersey', 'l 89 - 90 ( ot )', 'andre iguodala ( 20 )', 'elton brand ( 11 )', 'evan turner ( 7 )', 'prudential center 6252', '0 - 3'], ['4', 'october 12', 'boston', 'w 103 - 92 ( ot )', 'marreese speights ( 19 )', 'jrue holiday ( 7 )', 'jrue holiday ( 7 )', 'wells fargo center 7835', '1 - 3'], ['5', 'october 13', 'toronto', 'l 116 - 119 ( 2ot )', 'jrue holiday ( 18 )', 'evan turner ( 12 )', 'jrue holiday ( 12 )', 'air canada centre 12078', '1 - 4'], ['6', 'october 19', 'cleveland', 'l 95 - 111 ( ot )', 'andre iguodala ( 19 )', 'andre iguodala ( 10 )', 'andre iguodala , evan turner ( 6 )', 'us bank arena 6217', '1 - 5']] |
felice herrig | https://en.wikipedia.org/wiki/Felice_Herrig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16182887-2.html.csv | count | there were 10 events where felice herrig was in the third round . | {'scope': 'all', 'criterion': 'equal', 'value': '3', 'result': '10', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'round', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; round ; 3 }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; round ; 3 } }', 'tointer': 'select the rows whose round record is equal to 3 . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; round ; 3 } } ; 10 } = true', 'tointer': 'select the rows whose round record is equal to 3 . the number of such rows is 10 .'} | eq { count { filter_eq { all_rows ; round ; 3 } } ; 10 } = true | select the rows whose round record is equal to 3 . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'round_5': 5, '3_6': 6, '10_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'round_5': 'round', '3_6': '3', '10_7': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'round_5': [0], '3_6': [0], '10_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '9 - 4', 'heather clark', 'decision ( split )', 'bellator 94', '3', '5:00', 'tampa , florida , united states'], ['win', '8 - 4', 'patricia vidonic', 'decision ( unanimous )', 'bellator 84', '3', '5:00', 'hammond , indiana , united states'], ['win', '7 - 4', 'simona soukupova', 'decision ( unanimous )', 'xfc 19 : charlotte showdown', '3', '5:00', 'charlotte , north carolina , united states'], ['win', '6 - 4', 'patricia vidonic', 'decision ( unanimous )', 'xfc 17 : apocalypse', '3', '5:00', 'jackson , tennessee , united states'], ['loss', '5 - 4', 'carla esparza', 'decision ( unanimous )', 'xfc 15 : tribute', '3', '5:00', 'tampa , florida , united states'], ['win', '5 - 3', 'nicdali rivera - calanoc', 'decision ( unanimous )', 'xtreme fighting organization 39', '3', '5:00', 'hoffman estates , illinois , united states'], ['win', '4 - 3', 'andrea miller', 'tko ( punches )', 'chicago cagefighting championship 3', '1', '3:30', 'villa park , illinois , united states'], ['loss', '3 - 3', 'barb honchak', 'decision ( unanimous )', 'hoosier fight club 6 : new years nemesis', '3', '5:00', 'valparaiso , indiana , united states'], ['win', '3 - 2', 'amanda lavoy', 'submission ( armbar )', 'xtreme fighting organization 37', '1', '3:35', 'chicago , illinois , united states'], ['win', '2 - 2', 'jessica rakoczy', 'decision ( split )', 'bellator 14', '3', '5:00', 'chicago , illinois , united states'], ['win', '1 - 2', 'michele gutierrez', 'submission ( armbar )', 'unconquered 1 : november reign', '2', '2:03', 'coral gables , florida , united states'], ['loss', '0 - 2', 'valerie coolbaugh', 'decision ( split )', 'xtreme fighting organization 29', '3', '5:00', 'lakemoor , illinois , united states'], ['loss', '0 - 1', 'iman achhal', 'decision ( split )', 'uwc : man o war', '3', '5:00', 'fairfax , virginia , united states']] |
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/2-11734041-3.html.csv | majority | most of the players played in forward position . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'forward', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'position', 'forward'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them fuzzily match to forward .', 'tostr': 'most_eq { all_rows ; position ; forward } = true'} | most_eq { all_rows ; position ; forward } = true | for the position records of all rows , most of them fuzzily match to forward . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'forward_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'forward_4': 'forward'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'forward_4': [0]} | ['player', 'no ( s )', 'height in ft', 'position', 'years for rockets', 'school / club team / country'] | [['caldwell , adrian adrian caldwell', '44', '6 - 8', 'forward', '1989 - 91 , 1994 - 95', 'lamar'], ['carr , antoine antoine carr', '55', '6 - 9', 'forward', '1998 - 99', 'wichita state'], ['carroll , joe barry joe barry carroll', '2', '7 - 1', 'center / forward', '1987 - 88', 'purdue'], ['cassell , sam sam cassell', '10', '6 - 3', 'guard', '1993 - 96', 'florida state'], ['cato , kelvin kelvin cato', '13', '6 - 11', 'center', '1999 - 2004', 'iowa state'], ['chievous , derrick derrick chievous', '3', '6 - 7', 'guard / forward', '1988 - 90', 'missouri'], ['chilcutt , pete pete chilcutt', '32', '6 - 10', 'forward', '1994 - 96', 'north carolina'], ['coleman , ec ec coleman', '12 , 44', '6 - 8', 'forward', '1973 - 74 , 1978 - 79', 'houston baptist'], ['collier , jason jason collier', '52', '7 - 0', 'forward / center', '2000 - 03', 'georgia tech'], ['colson , sean sean colson', '20', '6 - 0', 'guard', '2000 - 01', 'unc - charlotte'], ['conner , lester lester conner', '7', '6 - 4', 'guard', '1987 - 88', 'oregon state'], ['cook , brian brian cook', '43', '6 - 9', 'forward', '2009 - 10', 'illinois'], ['cunningham , dick dick cunningham', '34', '6 - 10', 'center', '1971 - 72', 'murray state'], ['cureton , earl earl cureton', '35', '6 - 9', 'forward / center', '1993 - 94', 'detroit , robert morris'], ['curley , bill bill curley', '15', '6 - 9', 'forward', '1999 - 2000', 'boston college']] |
2001 masters tournament | https://en.wikipedia.org/wiki/2001_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514667-2.html.csv | comparative | at the 2001 masters tournament , lee janzen 's score was one less than chris perry 's score . | {'row_1': '5', 'row_2': '9', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'lee janzen'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to lee janzen .', 'tostr': 'filter_eq { all_rows ; player ; lee janzen }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; lee janzen } ; score }', 'tointer': 'select the rows whose player record fuzzily matches to lee janzen . take the score record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'chris perry'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to chris perry .', 'tostr': 'filter_eq { all_rows ; player ; chris perry }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; chris perry } ; score }', 'tointer': 'select the rows whose player record fuzzily matches to chris perry . take the score record of this row .'}], 'result': '-1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; lee janzen } ; score } ; hop { filter_eq { all_rows ; player ; chris perry } ; score } }'}, '-1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; lee janzen } ; score } ; hop { filter_eq { all_rows ; player ; chris perry } ; score } } ; -1 } = true', 'tointer': 'select the rows whose player record fuzzily matches to lee janzen . take the score record of this row . select the rows whose player record fuzzily matches to chris perry . take the score record of this row . the second record is 1 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; player ; lee janzen } ; score } ; hop { filter_eq { all_rows ; player ; chris perry } ; score } } ; -1 } = true | select the rows whose player record fuzzily matches to lee janzen . take the score record of this row . select the rows whose player record fuzzily matches to chris perry . take the score record of this row . the second record is 1 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'lee janzen_9': 9, 'score_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'chris perry_13': 13, 'score_14': 14, '-1_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'lee janzen_9': 'lee janzen', 'score_10': 'score', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'chris perry_13': 'chris perry', 'score_14': 'score', '-1_15': '-1'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'lee janzen_9': [0], 'score_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'chris perry_13': [1], 'score_14': [3], '-1_15': [5]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'chris dimarco', 'united states', '65', '- 7'], ['t2', 'ángel cabrera', 'argentina', '66', '- 6'], ['t2', 'steve stricker', 'united states', '66', '- 6'], ['t4', 'john huston', 'united states', '67', '- 5'], ['t4', 'lee janzen', 'united states', '67', '- 5'], ['t4', 'phil mickelson', 'united states', '67', '- 5'], ['t7', 'james driscoll ( a )', 'united states', '68', '- 4'], ['t7', 'miguel ángel jiménez', 'spain', '68', '- 4'], ['t7', 'chris perry', 'united states', '68', '- 4'], ['t7', 'kirk triplett', 'united states', '68', '- 4']] |
2009 masters tournament | https://en.wikipedia.org/wiki/2009_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18812411-7.html.csv | comparative | at the 2009 masters tournament , chad campbell 's score was one lower than jim furyk 's score . | {'row_1': '3', 'row_2': '4', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'chad campbell'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to chad campbell .', 'tostr': 'filter_eq { all_rows ; player ; chad campbell }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; chad campbell } ; score }', 'tointer': 'select the rows whose player record fuzzily matches to chad campbell . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jim furyk'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to jim furyk .', 'tostr': 'filter_eq { all_rows ; player ; jim furyk }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; jim furyk } ; score }', 'tointer': 'select the rows whose player record fuzzily matches to jim furyk . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; chad campbell } ; score } ; hop { filter_eq { all_rows ; player ; jim furyk } ; score } } = true', 'tointer': 'select the rows whose player record fuzzily matches to chad campbell . take the score record of this row . select the rows whose player record fuzzily matches to jim furyk . take the score record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; chad campbell } ; score } ; hop { filter_eq { all_rows ; player ; jim furyk } ; score } } = true | select the rows whose player record fuzzily matches to chad campbell . take the score record of this row . select the rows whose player record fuzzily matches to jim furyk . take the score 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, 'player_7': 7, 'chad campbell_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'jim furyk_12': 12, 'score_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', 'player_7': 'player', 'chad campbell_8': 'chad campbell', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'jim furyk_12': 'jim furyk', 'score_13': 'score'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'chad campbell_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'jim furyk_12': [1], 'score_13': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'ángel cabrera', 'argentina', '68 + 68 + 69 = 205', '- 11'], ['t1', 'kenny perry', 'united states', '68 + 67 + 70 = 205', '- 11'], ['3', 'chad campbell', 'united states', '65 + 70 + 72 = 207', '- 9'], ['4', 'jim furyk', 'united states', '66 + 74 + 68 = 208', '- 8'], ['5', 'steve stricker', 'united states', '72 + 69 + 68 = 209', '- 7'], ['t6', 'todd hamilton', 'united states', '68 + 70 + 72 = 210', '- 6'], ['t6', 'shingo katayama', 'japan', '67 + 73 + 70 = 210', '- 6'], ['t6', 'rory sabbatini', 'south africa', '73 + 67 + 70 = 210', '- 6'], ['9', 'tim clark', 'south africa', '68 + 71 + 72 = 211', '- 5'], ['t10', 'stephen ames', 'canada', '73 + 68 + 71 = 212', '- 4'], ['t10', 'anthony kim', 'united states', '75 + 65 + 72 = 212', '- 4'], ['t10', 'hunter mahan', 'united states', '66 + 75 + 71 = 212', '- 4'], ['t10', 'phil mickelson', 'united states', '73 + 68 + 71 = 212', '- 4'], ['t10', "sean o'hair", 'united states', '68 + 76 + 68 = 212', '- 4'], ['t10', 'ian poulter', 'england', '71 + 73 + 68 = 212', '- 4'], ['t10', 'lee westwood', 'england', '70 + 72 + 70 = 212', '- 4'], ['t10', 'tiger woods', 'united states', '70 + 72 + 70 = 212', '- 4']] |
b " finland 's next top model " | https://en.wikipedia.org/wiki/Finland%27s_Next_Top_Model | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16805656-1.html.csv | count | in finland 's next top model , of the cycles where the number of contestants has been determined , three of the cycles had eleven contestants . | {'scope': 'all', 'criterion': 'equal', 'value': '11', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'number of contestants', '11'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose number of contestants record is equal to 11 .', 'tostr': 'filter_eq { all_rows ; number of contestants ; 11 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; number of contestants ; 11 } }', 'tointer': 'select the rows whose number of contestants record is equal to 11 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; number of contestants ; 11 } } ; 3 } = true', 'tointer': 'select the rows whose number of contestants record is equal to 11 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; number of contestants ; 11 } } ; 3 } = true | select the rows whose number of contestants record is equal to 11 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'number of contestants_5': 5, '11_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'number of contestants_5': 'number of contestants', '11_6': '11', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'number of contestants_5': [0], '11_6': [0], '3_7': [2]} | ['cycle', 'premiere date', 'winner', 'runner - up', 'number of contestants', 'international destinations'] | [['1', 'april 6 , 2008', 'ani alitalo', 'darina shved', '12', 'stockholm turkey'], ['2', 'april 13 , 2009', 'nanna grundfeldt', 'anna - kaisa tyrväinen', '11', 'paris gran canaria'], ['3', 'april 12 , 2010', 'jenna kuokkanen', 'saara sihvonen', '11', 'milan egypt'], ['4', 'september 12 , 2011', 'anna - sofia ali - sisto', 'helen preis', '12', 'london lisbon'], ['5', 'september 3 , 2012', 'meri ikonen', 'matleena helander', '11', 'reykjavík kenya'], ['6', 'tba', 'tba', 'tba', 'tba', 'tba']] |
wuji county | https://en.wikipedia.org/wiki/Wuji_County | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12425097-1.html.csv | unique | wuji town is the only entry with 25 villages . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '25', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'villages', '25'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose villages record is equal to 25 .', 'tostr': 'filter_eq { all_rows ; villages ; 25 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; villages ; 25 } }', 'tointer': 'select the rows whose villages record is equal to 25 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'villages', '25'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose villages record is equal to 25 .', 'tostr': 'filter_eq { all_rows ; villages ; 25 }'}, 'name'], 'result': 'wuji town', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; villages ; 25 } ; name }'}, 'wuji town'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; villages ; 25 } ; name } ; wuji town }', 'tointer': 'the name record of this unqiue row is wuji town .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; villages ; 25 } } ; eq { hop { filter_eq { all_rows ; villages ; 25 } ; name } ; wuji town } } = true', 'tointer': 'select the rows whose villages record is equal to 25 . there is only one such row in the table . the name record of this unqiue row is wuji town .'} | and { only { filter_eq { all_rows ; villages ; 25 } } ; eq { hop { filter_eq { all_rows ; villages ; 25 } ; name } ; wuji town } } = true | select the rows whose villages record is equal to 25 . there is only one such row in the table . the name record of this unqiue row is wuji town . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'villages_7': 7, '25_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'wuji town_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'villages_7': 'villages', '25_8': '25', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'wuji town_10': 'wuji town'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'villages_7': [0], '25_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'wuji town_10': [3]} | ['name', 'hanzi', 'area ( km square )', 'population', 'villages'] | [['wuji town', '无极镇', '57', '76851', '25'], ['qiji town', '七汲镇', '54', '41584', '20'], ['zhangduangu town', '张段固镇', '51', '40916', '20'], ['beisu town', '北苏镇', '54', '54639', '18'], ['guozhuang town', '郭庄镇', '43', '43636', '23'], ['dachen town', '大陈镇', '42', '31297', '13'], ['haozhuang township', '郝庄乡', '55', '37786', '19'], ['donghoufang township', '东侯坊乡', '56', '48665', '24'], ['lichengdao township', '里城道乡', '44', '40411', '19'], ['nanliu township', '南流乡', '30', '24802', '12'], ['gaotou hui autonomous township', '高头回族乡', '32', '33722', '15']] |
1935 vfl season | https://en.wikipedia.org/wiki/1935_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790651-8.html.csv | aggregation | the average crowd attendance for games in the 1935 vfl season was 14924 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '14924', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '14924', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '14924'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 14924 } = true', 'tointer': 'the average of the crowd record of all rows is 14924 .'} | round_eq { avg { all_rows ; crowd } ; 14924 } = true | the average of the crowd record of all rows is 14924 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '14924_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '14924_5': '14924'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '14924_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '9.23 ( 77 )', 'south melbourne', '17.14 ( 116 )', 'glenferrie oval', '12000', '15 june 1935'], ['geelong', '13.12 ( 90 )', 'richmond', '10.16 ( 76 )', 'corio oval', '13000', '15 june 1935'], ['essendon', '9.7 ( 61 )', 'fitzroy', '14.19 ( 103 )', 'windy hill', '17000', '15 june 1935'], ['collingwood', '16.30 ( 126 )', 'north melbourne', '6.10 ( 46 )', 'victoria park', '8000', '15 june 1935'], ['st kilda', '14.10 ( 94 )', 'footscray', '7.13 ( 55 )', 'junction oval', '20000', '15 june 1935'], ['melbourne', '7.12 ( 54 )', 'carlton', '9.12 ( 66 )', 'mcg', '19546', '15 june 1935']] |
cube ( film series ) | https://en.wikipedia.org/wiki/Cube_%28film_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2933761-1.html.csv | unique | kazan is the only character in the cube film series with an alive status after leaving the cube . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'alive after exiting the cube', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'alive after exiting the cube'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to alive after exiting the cube .', 'tostr': 'filter_eq { all_rows ; status ; alive after exiting the cube }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; status ; alive after exiting the cube } }', 'tointer': 'select the rows whose status record fuzzily matches to alive after exiting the cube . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'alive after exiting the cube'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to alive after exiting the cube .', 'tostr': 'filter_eq { all_rows ; status ; alive after exiting the cube }'}, 'name'], 'result': 'kazan', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; status ; alive after exiting the cube } ; name }'}, 'kazan'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; status ; alive after exiting the cube } ; name } ; kazan }', 'tointer': 'the name record of this unqiue row is kazan .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; status ; alive after exiting the cube } } ; eq { hop { filter_eq { all_rows ; status ; alive after exiting the cube } ; name } ; kazan } } = true', 'tointer': 'select the rows whose status record fuzzily matches to alive after exiting the cube . there is only one such row in the table . the name record of this unqiue row is kazan .'} | and { only { filter_eq { all_rows ; status ; alive after exiting the cube } } ; eq { hop { filter_eq { all_rows ; status ; alive after exiting the cube } ; name } ; kazan } } = true | select the rows whose status record fuzzily matches to alive after exiting the cube . there is only one such row in the table . the name record of this unqiue row is kazan . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'status_7': 7, 'alive after exiting the cube_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'kazan_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'status_7': 'status', 'alive after exiting the cube_8': 'alive after exiting the cube', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'kazan_10': 'kazan'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'status_7': [0], 'alive after exiting the cube_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'kazan_10': [3]} | ['name', 'occupation', 'gender', 'prison connection', 'played by', 'status'] | [['kazan', 'autistic savant', 'male', 'kazan prison ( russia )', 'andrew miller', 'alive after exiting the cube'], ['david worth', 'architect', 'male', 'leavenworth prison ( usa )', 'david hewlett', 'dead'], ['quentin', 'police officer', 'male', 'san quentin state prison ( usa )', 'maurice dean wint', 'dead'], ['joan leaven', 'mathematics student', 'female', 'leavenworth prison ( usa )', 'nicole de boer', 'dead'], ['dr helen holloway', 'free clinic doctor', 'female', "holloway women 's prison ( uk )", 'nicky guadagni', 'dead'], ['rennes', 'prison escapist', 'male', 'centre pãnitentiaire de rennes ( france )', 'wayne robson', 'dead']] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.