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1964 vfl season | https://en.wikipedia.org/wiki/1964_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10784349-7.html.csv | ordinal | in the 1964 vfl season , the 2nd highest attendance was when melbourne was the home team . | {'row': '5', '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': 'melbourne', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; home team }'}, 'melbourne'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; melbourne } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is melbourne .'} | eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; melbourne } = true | select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is melbourne . | 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, 'melbourne_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', 'melbourne_8': 'melbourne'} | {'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], 'melbourne_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '13.11 ( 89 )', 'richmond', '7.16 ( 58 )', 'glenferrie oval', '22000', '30 may 1964'], ['geelong', '11.23 ( 89 )', 'st kilda', '13.8 ( 86 )', 'kardinia park', '28000', '30 may 1964'], ['collingwood', '22.18 ( 150 )', 'north melbourne', '6.6 ( 42 )', 'victoria park', '34222', '30 may 1964'], ['carlton', '8.12 ( 60 )', 'fitzroy', '8.11 ( 59 )', 'princes park', '18945', '30 may 1964'], ['melbourne', '12.14 ( 86 )', 'footscray', '6.8 ( 44 )', 'mcg', '33129', '30 may 1964'], ['south melbourne', '11.18 ( 84 )', 'essendon', '14.12 ( 96 )', 'lake oval', '20470', '30 may 1964']] |
utah jazz all - time roster | https://en.wikipedia.org/wiki/Utah_Jazz_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11545282-6.html.csv | majority | most of the players on the utah jazz 's all time roster were from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'nationality', 'position', 'years for jazz', 'school / club team'] | [['jim farmer', 'united states', 'guard', '1988 - 89', 'alabama'], ['derrick favors', 'united states', 'forward', '2011 - present', 'georgia tech'], ['kyrylo fesenko', 'ukraine', 'center', '2007 - 11', 'cherkasy monkeys ( ukraine )'], ['derek fisher', 'united states', 'guard', '2006 - 2007', 'arkansas - little rock'], ['greg foster', 'united states', 'center / forward', '1995 - 99', 'utep'], ['bernie fryer', 'united states', 'guard', '1975 - 76', 'byu'], ['todd fuller', 'united states', 'center', '1998 - 99', 'north carolina state'], ['terry furlow', 'united states', 'guard / forward', '1979 - 80', 'michigan state']] |
1950 washington redskins season | https://en.wikipedia.org/wiki/1950_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15124563-1.html.csv | ordinal | in the 1950 washington redskins season , the first game of october was against pittsburgh steelers . | {'scope': 'subset', 'row': '3', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'october'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'date', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; date ; october } ; date ; 1 }'}, 'opponent'], 'result': 'pittsburgh steelers', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; date ; october } ; date ; 1 } ; opponent }'}, 'pittsburgh steelers'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; date ; october } ; date ; 1 } ; opponent } ; pittsburgh steelers } = true', 'tointer': 'select the rows whose date record fuzzily matches to october . select the row whose date record of these rows is 1st minimum . the opponent record of this row is pittsburgh steelers .'} | eq { hop { nth_argmin { filter_eq { all_rows ; date ; october } ; date ; 1 } ; opponent } ; pittsburgh steelers } = true | select the rows whose date record fuzzily matches to october . select the row whose date record of these rows is 1st minimum . the opponent record of this row is pittsburgh steelers . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'october_7': 7, 'date_8': 8, '1_9': 9, 'opponent_10': 10, 'pittsburgh steelers_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'october_7': 'october', 'date_8': 'date', '1_9': '1', 'opponent_10': 'opponent', 'pittsburgh steelers_11': 'pittsburgh steelers'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'october_7': [0], 'date_8': [1], '1_9': [1], 'opponent_10': [2], 'pittsburgh steelers_11': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 17 , 1950', 'baltimore colts', 'w 38 - 14', '29000'], ['2', 'september 24 , 1950', 'green bay packers', 'l 35 - 21', '14109'], ['3', 'october 1 , 1950', 'pittsburgh steelers', 'l 26 - 7', '25008'], ['4', 'october 8 , 1950', 'new york giants', 'l 21 - 17', '19288'], ['6', 'october 22 , 1950', 'chicago cardinals', 'l 38 - 28', '27856'], ['7', 'october 29 , 1950', 'philadelphia eagles', 'l 35 - 3', '33707'], ['8', 'november 5 , 1950', 'new york giants', 'l 24 - 21', '23909'], ['9', 'november 12 , 1950', 'philadelphia eagles', 'l 33 - 0', '29407'], ['10', 'november 19 , 1950', 'cleveland browns', 'l 20 - 14', '21908'], ['11', 'november 26 , 1950', 'baltimore colts', 'w 38 - 28', '21275'], ['12', 'december 3 , 1950', 'pittsburgh steelers', 'w 24 - 7', '19741'], ['13', 'december 10 , 1950', 'cleveland browns', 'l 45 - 21', '30143']] |
2008 vanderbilt commodores baseball team | https://en.wikipedia.org/wiki/2008_Vanderbilt_Commodores_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15925327-4.html.csv | unique | may 23 was the only date that 2008 vanderbilt commodores baseball team played against south carolina . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '23 south carolina', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', '23 south carolina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to 23 south carolina .', 'tostr': 'filter_eq { all_rows ; opponent ; 23 south carolina }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent ; 23 south carolina } }', 'tointer': 'select the rows whose opponent record fuzzily matches to 23 south carolina . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', '23 south carolina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to 23 south carolina .', 'tostr': 'filter_eq { all_rows ; opponent ; 23 south carolina }'}, 'date'], 'result': 'may 23', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; 23 south carolina } ; date }'}, 'may 23'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; 23 south carolina } ; date } ; may 23 }', 'tointer': 'the date record of this unqiue row is may 23 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponent ; 23 south carolina } } ; eq { hop { filter_eq { all_rows ; opponent ; 23 south carolina } ; date } ; may 23 } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to 23 south carolina . there is only one such row in the table . the date record of this unqiue row is may 23 .'} | and { only { filter_eq { all_rows ; opponent ; 23 south carolina } } ; eq { hop { filter_eq { all_rows ; opponent ; 23 south carolina } ; date } ; may 23 } } = true | select the rows whose opponent record fuzzily matches to 23 south carolina . there is only one such row in the table . the date record of this unqiue row is may 23 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, '23 south carolina_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'may 23_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', '23 south carolina_8': '23 south carolina', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'may 23_10': 'may 23'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent_7': [0], '23 south carolina_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'may 23_10': [3]} | ['date', 'opponent', 'location', 'score', 'loss', 'record'] | [['may 21', 'florida', 'regions field', '7 - 3', 'keating ( 8 - 1 )', '38 - 18'], ['may 22', '13 lsu', 'regions field', '8 - 2', 'cotham ( 7 - 5 )', '38 - 19'], ['may 23', '23 south carolina', 'regions field', '7 - 5', 'cooper ( 5 - 6 )', '39 - 19'], ['may 24', 'ole miss', 'regions field', '7 - 4', 'mckean ( 4 - 1 )', '40 - 19'], ['may 24', 'ole miss', 'regions field', '8 - 7', 'hayes ( 2 - 1 )', '40 - 20']] |
lawrence peckham | https://en.wikipedia.org/wiki/Lawrence_Peckham | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14576140-1.html.csv | ordinal | lawrence peckham 's second lowest position in the olympic games was 10th . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'position', '2'], 'result': '10th', 'ind': 0, 'tostr': 'nth_max { all_rows ; position ; 2 }', 'tointer': 'the 2nd maximum position record of all rows is 10th .'}, '10th'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; position ; 2 } ; 10th }', 'tointer': 'the 2nd maximum position record of all rows is 10th .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'position', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; position ; 2 }'}, 'competition'], 'result': 'olympic games', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; position ; 2 } ; competition }'}, 'olympic games'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; position ; 2 } ; competition } ; olympic games }', 'tointer': 'the competition record of the row with 2nd maximum position record is olympic games .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; position ; 2 } ; 10th } ; eq { hop { nth_argmax { all_rows ; position ; 2 } ; competition } ; olympic games } } = true', 'tointer': 'the 2nd maximum position record of all rows is 10th . the competition record of the row with 2nd maximum position record is olympic games .'} | and { eq { nth_max { all_rows ; position ; 2 } ; 10th } ; eq { hop { nth_argmax { all_rows ; position ; 2 } ; competition } ; olympic games } } = true | the 2nd maximum position record of all rows is 10th . the competition record of the row with 2nd maximum position record is olympic games . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'position_8': 8, '2_9': 9, '10th_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'position_12': 12, '2_13': 13, 'competition_14': 14, 'olympic games_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'position_8': 'position', '2_9': '2', '10th_10': '10th', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'position_12': 'position', '2_13': '2', 'competition_14': 'competition', 'olympic games_15': 'olympic games'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'position_8': [0], '2_9': [0], '10th_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'position_12': [2], '2_13': [2], 'competition_14': [3], 'olympic games_15': [4]} | ['year', 'competition', 'venue', 'position', 'event'] | [['1962', 'british empire and commonwealth games', 'perth , australia', '6th', 'high jump'], ['1964', 'olympic games', 'tokyo , japan', '10th', 'high jump'], ['1966', 'british empire and commonwealth games', 'kingston , jamaica', '1st', 'high jump'], ['1968', 'olympic games', 'mexico city , mexico', '8th', 'high jump'], ['1969', 'pacific conference games', 'tokyo , japan', '1st', 'high jump'], ['1970', 'commonwealth games', 'edinburgh , scotland', '1st', 'high jump'], ['1972', 'olympic games', 'munich , west germany', '18th', 'high jump'], ['1973', 'pacific conference games', 'toronto , canada', '3rd', 'high jump'], ['1974', 'british commonwealth games', 'christchurch , new zealand', '2nd', 'high jump']] |
2000 buffalo bills season | https://en.wikipedia.org/wiki/2000_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16025322-1.html.csv | ordinal | the 2nd defensive end picked in the 2000 buffalo bills season was leif larsen . | {'scope': 'subset', 'row': '6', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'defensive end'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defensive end'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; defensive end }', 'tointer': 'select the rows whose position record fuzzily matches to defensive end .'}, 'pick', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; position ; defensive end } ; pick ; 2 }'}, 'player'], 'result': 'leif larsen', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; position ; defensive end } ; pick ; 2 } ; player }'}, 'leif larsen'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; position ; defensive end } ; pick ; 2 } ; player } ; leif larsen } = true', 'tointer': 'select the rows whose position record fuzzily matches to defensive end . select the row whose pick record of these rows is 2nd minimum . the player record of this row is leif larsen .'} | eq { hop { nth_argmin { filter_eq { all_rows ; position ; defensive end } ; pick ; 2 } ; player } ; leif larsen } = true | select the rows whose position record fuzzily matches to defensive end . select the row whose pick record of these rows is 2nd minimum . the player record of this row is leif larsen . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'position_6': 6, 'defensive end_7': 7, 'pick_8': 8, '2_9': 9, 'player_10': 10, 'leif larsen_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'position_6': 'position', 'defensive end_7': 'defensive end', 'pick_8': 'pick', '2_9': '2', 'player_10': 'player', 'leif larsen_11': 'leif larsen'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'position_6': [0], 'defensive end_7': [0], 'pick_8': [1], '2_9': [1], 'player_10': [2], 'leif larsen_11': [3]} | ['round', 'pick', 'player', 'position', 'college'] | [['1', '26', 'erik flowers', 'defensive end', 'arizona state'], ['2', '58', 'travares tillman', 'free safety', 'georgia tech'], ['3', '89', 'corey moore', 'linebacker', 'virginia tech'], ['4', '121', 'avion black', 'wide receiver', 'tennessee state'], ['5', '156', 'sammy morris', 'fullback', 'texas tech'], ['6', '194', 'leif larsen', 'defensive end', 'texas - el paso ( utep )'], ['7', '233', 'drew haddad', 'wide receiver', 'buffalo'], ['7', '251', 'dashon polk', 'linebacker', 'arizona']] |
united states house of representatives elections , 1970 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1970 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341718-34.html.csv | comparative | out of the candidates re-elected in 1968 , wilmer mizell had a higher percentage than earl b. ruth . | {'row_1': '3', 'row_2': '4', 'col': '6', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'wilmer mizell'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to wilmer mizell .', 'tostr': 'filter_eq { all_rows ; incumbent ; wilmer mizell }'}, 'candidates'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; wilmer mizell } ; candidates }', 'tointer': 'select the rows whose incumbent record fuzzily matches to wilmer mizell . take the candidates record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'earl b ruth'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to earl b ruth .', 'tostr': 'filter_eq { all_rows ; incumbent ; earl b ruth }'}, 'candidates'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; earl b ruth } ; candidates }', 'tointer': 'select the rows whose incumbent record fuzzily matches to earl b ruth . take the candidates record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; incumbent ; wilmer mizell } ; candidates } ; hop { filter_eq { all_rows ; incumbent ; earl b ruth } ; candidates } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to wilmer mizell . take the candidates record of this row . select the rows whose incumbent record fuzzily matches to earl b ruth . take the candidates record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; incumbent ; wilmer mizell } ; candidates } ; hop { filter_eq { all_rows ; incumbent ; earl b ruth } ; candidates } } = true | select the rows whose incumbent record fuzzily matches to wilmer mizell . take the candidates record of this row . select the rows whose incumbent record fuzzily matches to earl b ruth . take the candidates 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, 'incumbent_7': 7, 'wilmer mizell_8': 8, 'candidates_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'earl b ruth_12': 12, 'candidates_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', 'incumbent_7': 'incumbent', 'wilmer mizell_8': 'wilmer mizell', 'candidates_9': 'candidates', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'earl b ruth_12': 'earl b ruth', 'candidates_13': 'candidates'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'wilmer mizell_8': [0], 'candidates_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'earl b ruth_12': [1], 'candidates_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'lawrence h fountain', 'democratic', '1952', 're - elected', 'lawrence h fountain ( d ) unopposed'], ['north carolina 4', 'nick galifianakis', 'democratic', '1966', 're - elected', 'nick galifianakis ( d ) 52.4 % jack hawke ( r ) 47.6 %'], ['north carolina 5', 'wilmer mizell', 'republican', '1968', 're - elected', 'wilmer mizell ( r ) 58.1 % james g white ( d ) 41.9 %'], ['north carolina 8', 'earl b ruth', 'republican', '1968', 're - elected', 'earl b ruth ( r ) 56.1 % h clifton blue ( d ) 43.9 %'], ['north carolina 9', 'charles r jonas', 'republican', '1952', 're - elected', 'charles r jonas ( r ) 66.6 % cy n bahakel ( d ) 33.4 %']] |
athletics at the 1963 pan american games | https://en.wikipedia.org/wiki/Athletics_at_the_1963_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10648331-3.html.csv | ordinal | canada had the 2nd highest number of silver in athletics at the 1963 pan american games . | {'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', 'silver', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; silver ; 2 }'}, 'nation'], 'result': 'canada', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; silver ; 2 } ; nation }'}, 'canada'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; silver ; 2 } ; nation } ; canada } = true', 'tointer': 'select the row whose silver record of all rows is 2nd maximum . the nation record of this row is canada .'} | eq { hop { nth_argmax { all_rows ; silver ; 2 } ; nation } ; canada } = true | select the row whose silver record of all rows is 2nd maximum . the nation record of this row is canada . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, '2_6': 6, 'nation_7': 7, 'canada_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', 'silver_5': 'silver', '2_6': '2', 'nation_7': 'nation', 'canada_8': 'canada'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], '2_6': [0], 'nation_7': [1], 'canada_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '22', '15', '10', '47'], ['2', 'canada', '5', '5', '2', '12'], ['3', 'argentina', '2', '2', '1', '5'], ['4', 'venezuela', '1', '3', '3', '7'], ['5', 'cuba', '1', '3', '1', '5'], ['6', 'mexico', '1', '1', '1', '3'], ['7', 'chile', '1', '0', '0', '1'], ['8', 'brazil', '0', '2', '6', '8'], ['9', 'jamaica', '0', '1', '1', '2'], ['10', 'guatemala', '0', '1', '0', '1'], ['11', 'trinidad and tobago', '0', '0', '2', '2'], ['11', 'barbados', '0', '0', '2', '2'], ['13', 'panama', '0', '0', '1', '1'], ['13', 'puerto rico', '0', '0', '1', '1'], ['13', 'uruguay', '0', '0', '1', '1'], ['13', 'netherlands antilles', '0', '0', '1', '1']] |
1980 open championship | https://en.wikipedia.org/wiki/1980_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18171018-5.html.csv | count | 3 players were tied at the 2nd place in the 1980 open championship . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 't2', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'place', 't2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose place record fuzzily matches to t2 .', 'tostr': 'filter_eq { all_rows ; place ; t2 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; place ; t2 } }', 'tointer': 'select the rows whose place record fuzzily matches to t2 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; place ; t2 } } ; 3 } = true', 'tointer': 'select the rows whose place record fuzzily matches to t2 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; place ; t2 } } ; 3 } = true | select the rows whose place record fuzzily matches to t2 . 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, 'place_5': 5, 't2_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', 'place_5': 'place', 't2_6': 't2', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'place_5': [0], 't2_6': [0], '3_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'lee trevino', 'united states', '68 + 67 = 135', '- 7'], ['t2', 'ken brown', 'scotland', '70 + 68 = 138', '- 4'], ['t2', 'jerry pate', 'united states', '71 + 67 = 138', '- 4'], ['t2', 'tom watson', 'united states', '68 + 70 = 138', '- 4'], ['t5', 'seve ballesteros', 'spain', '72 + 68 = 140', '- 2'], ['t5', 'andy bean', 'united states', '71 + 69 = 140', '- 2'], ['t5', 'ben crenshaw', 'united states', '70 + 70 = 140', '- 2'], ['t5', 'gil morgan', 'united states', '70 + 70 = 140', '- 2'], ['t5', 'jack newton', 'australia', '69 + 71 = 140', '- 2'], ['t5', 'jack nicklaus', 'united states', '73 + 67 = 140', '- 2']] |
list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-50.html.csv | majority | most of the settlements in vojvodina are villages . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'village', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'type', 'village'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , most of them fuzzily match to village .', 'tostr': 'most_eq { all_rows ; type ; village } = true'} | most_eq { all_rows ; type ; village } = true | for the type records of all rows , most of them fuzzily match to village . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'village_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'village_4': 'village'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'village_4': [0]} | ['settlement', 'cyrillic name other names', 'type', 'population ( 2011 )', 'largest ethnic group ( 2002 )', 'dominant religion ( 2002 )'] | [['irig', 'ириг', 'town', '4415', 'serbs', 'orthodox christianity'], ['dobrodol', 'добродол ( hungarian : dobradópuszta )', 'village', '107', 'hungarians', 'catholic christianity'], ['grgetek', 'гргетек', 'village', '76', 'serbs', 'orthodox christianity'], ['jazak', 'јазак', 'village', '960', 'serbs', 'orthodox christianity'], ['krušedol prnjavor', 'крушедол прњавор', 'village', '234', 'serbs', 'orthodox christianity'], ['krušedol selo', 'крушедол село', 'village', '340', 'serbs', 'orthodox christianity'], ['mala remeta', 'мала ремета', 'village', '130', 'serbs', 'orthodox christianity'], ['neradin', 'нерадин', 'village', '475', 'serbs', 'orthodox christianity'], ['rivica', 'ривица', 'village', '620', 'serbs', 'orthodox christianity'], ['šatrinci', 'шатринци ( hungarian : satrinca )', 'village', '373', 'hungarians', 'catholic christianity'], ['velika remeta', 'велика ремета', 'village', '44', 'serbs', 'orthodox christianity']] |
2003 cfl draft | https://en.wikipedia.org/wiki/2003_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21321804-5.html.csv | comparative | ottawa renegades had a higher draft pick than the bc lions in picks 36 to 43 in the 2003 draft . | {'row_1': '1', 'row_2': '6', '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', 'cfl team', 'ottawa renegades'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cfl team record fuzzily matches to ottawa renegades .', 'tostr': 'filter_eq { all_rows ; cfl team ; ottawa renegades }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; cfl team ; ottawa renegades } ; pick }', 'tointer': 'select the rows whose cfl team record fuzzily matches to ottawa renegades . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cfl team', 'bc lions'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose cfl team record fuzzily matches to bc lions .', 'tostr': 'filter_eq { all_rows ; cfl team ; bc lions }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; cfl team ; bc lions } ; pick }', 'tointer': 'select the rows whose cfl team record fuzzily matches to bc lions . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; cfl team ; ottawa renegades } ; pick } ; hop { filter_eq { all_rows ; cfl team ; bc lions } ; pick } } = true', 'tointer': 'select the rows whose cfl team record fuzzily matches to ottawa renegades . take the pick record of this row . select the rows whose cfl team record fuzzily matches to bc lions . take the pick record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; cfl team ; ottawa renegades } ; pick } ; hop { filter_eq { all_rows ; cfl team ; bc lions } ; pick } } = true | select the rows whose cfl team record fuzzily matches to ottawa renegades . take the pick record of this row . select the rows whose cfl team record fuzzily matches to bc lions . take the pick 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, 'cfl team_7': 7, 'ottawa renegades_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'cfl team_11': 11, 'bc lions_12': 12, 'pick_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', 'cfl team_7': 'cfl team', 'ottawa renegades_8': 'ottawa renegades', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'cfl team_11': 'cfl team', 'bc lions_12': 'bc lions', 'pick_13': 'pick'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'cfl team_7': [0], 'ottawa renegades_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'cfl team_11': [1], 'bc lions_12': [1], 'pick_13': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['36', 'ottawa renegades', 'marc parenteau', 'og', 'boston college'], ['37', 'calgary stampeders', 'blake machan', 'sb', 'calgary'], ['38', 'hamilton tiger - cats', 'david kasouf', 'wr', 'holy cross'], ['39', 'toronto argonauts', 'derik fury', 'lb', 'mount allison'], ['40', 'saskatchewan roughriders', 'mike thomas', 'wr', 'regina'], ['41', 'bc lions', 'nicholas hoffman', 'fb', 'mcgill'], ['42', 'winnipeg blue bombers', 'cory olynick', 'wr', 'regina'], ['43', 'calgary stampeders', 'travis arnold', 'ol', 'manitoba']] |
united states house of representatives elections , 1946 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1946 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342233-17.html.csv | count | in the us house of representatives elections of ' 46 , for kentucky , 2 candidates had a vote percentage of at least 55.0 % . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '55.0 %', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'candidates', '55.0 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record is greater than or equal to 55.0 % .', 'tostr': 'filter_greater_eq { all_rows ; candidates ; 55.0 % }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; candidates ; 55.0 % } }', 'tointer': 'select the rows whose candidates record is greater than or equal to 55.0 % . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; candidates ; 55.0 % } } ; 2 } = true', 'tointer': 'select the rows whose candidates record is greater than or equal to 55.0 % . the number of such rows is 2 .'} | eq { count { filter_greater_eq { all_rows ; candidates ; 55.0 % } } ; 2 } = true | select the rows whose candidates record is greater than or equal to 55.0 % . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'candidates_5': 5, '55.0%_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', '55.0%_6': '55.0 %', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'candidates_5': [0], '55.0%_6': [0], '2_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['kentucky 4', 'frank chelf', 'democratic', '1944', 're - elected', 'frank chelf ( d ) 53.1 % don victor drye ( r ) 46.9 %'], ['kentucky 5', 'brent spence', 'democratic', '1930', 're - elected', 'brent spence ( d ) 51.2 % marion w moore ( r ) 48.8 %'], ['kentucky 6', 'virgil chapman', 'democratic', '1930', 're - elected', 'virgil chapman ( d ) 55.0 % w d rogers ( r ) 45.0 %'], ['kentucky 7', 'andrew j may', 'democratic', '1930', 'lost re - election republican gain', 'w howes meade ( r ) 59.3 % andrew j may ( d ) 40.7 %'], ['kentucky 8', 'joe b bates', 'democratic', '1930', 're - elected', 'joe b bates ( d ) 52.6 % ray schmauch ( r ) 47.4 %']] |
2008 - 09 tampa bay lightning season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Tampa_Bay_Lightning_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17360840-5.html.csv | aggregation | the average attendance for the 2008-09 lighting in games 10-23 was 16436 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '16436', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '16436', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '16436'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 16436 } = true', 'tointer': 'the average of the attendance record of all rows is 16436 .'} | round_eq { avg { all_rows ; attendance } ; 16436 } = true | the average of the attendance record of all rows is 16436 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '16436_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '16436_5': '16436'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '16436_5': [1]} | ['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points'] | [['10', 'november 1', 'ottawa senators', '3 - 2', 'st pete times forum', '16104', '4 - 3 - 3', '11'], ['11', 'november 5', 'new jersey devils', '3 - 4 so', 'prudential center', '11619', '4 - 3 - 4', '12'], ['12', 'november 6', 'new york rangers', '2 - 5', 'madison square garden', '18200', '4 - 4 - 4', '12'], ['13', 'november 8', 'philadelphia flyers', '2 - 1', 'wachovia center', '19412', '5 - 4 - 4', '14'], ['14', 'november 10', 'washington capitals', '2 - 4', 'verizon center', '17932', '5 - 5 - 4', '14'], ['15', 'november 12', 'florida panthers', '0 - 4', 'bankatlantic center', '12104', '5 - 6 - 4', '14'], ['16', 'november 13', 'detroit red wings', '3 - 4', 'st pete times forum', '20544', '5 - 7 - 4', '14'], ['17', 'november 16', 'carolina hurricanes', '2 - 3 so', 'rbc center', '13781', '5 - 7 - 5', '15'], ['18', 'november 18', 'florida panthers', '3 - 4 so', 'st pete times forum', '16176', '5 - 7 - 6', '16'], ['19', 'november 21', 'nashville predators', '4 - 1', 'st pete times forum', '16444', '6 - 7 - 6', '18'], ['20', 'november 23', 'new jersey devils', '3 - 7', 'st pete times forum', '14222', '6 - 8 - 6', '18'], ['21', 'november 26', 'new york rangers', '2 - 3 so', 'st pete times forum', '16991', '6 - 8 - 7', '19'], ['22', 'november 28', 'minnesota wild', '2 - 4', 'xcel energy center', '18568', '6 - 9 - 7', '19'], ['23', 'november 29', 'colorado avalanche', '3 - 4', 'pepsi center', '18007', '6 - 10 - 7', '19']] |
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 | ordinal | the m67d40 engine was the second earliest released engine for the bmw m67 . | {'row': '1', 'col': '6', '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', 'year', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 1 }'}, 'engine'], 'result': 'm67d40', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 1 } ; engine }'}, 'm67d40'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 1 } ; engine } ; m67d40 } = true', 'tointer': 'select the row whose year record of all rows is 1st minimum . the engine record of this row is m67d40 .'} | eq { hop { nth_argmin { all_rows ; year ; 1 } ; engine } ; m67d40 } = true | select the row whose year record of all rows is 1st minimum . the engine record of this row is m67d40 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '1_6': 6, 'engine_7': 7, 'm67d40_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', 'year_5': 'year', '1_6': '1', 'engine_7': 'engine', 'm67d40_8': 'm67d40'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '1_6': [0], 'engine_7': [1], 'm67d40_8': [2]} | ['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']] |
united states house of representatives elections , 1960 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1960 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341897-23.html.csv | majority | in the house of representatives elections , 1960 , the majority of incumbents were elected unopposed . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'unopposed', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': True, 'ind': 0, 'tointer': 'for the candidates records of all rows , most of them fuzzily match to unopposed .', 'tostr': 'most_eq { all_rows ; candidates ; unopposed } = true'} | most_eq { all_rows ; candidates ; unopposed } = true | for the candidates records of all rows , most of them fuzzily match to unopposed . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'candidates_3': 3, 'unopposed_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'candidates_3': 'candidates', 'unopposed_4': 'unopposed'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'candidates_3': [0], 'unopposed_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['massachusetts 2', 'edward boland', 'democratic', '1952', 're - elected', 'edward boland ( d ) unopposed'], ['massachusetts 3', 'philip philbin', 'democratic', '1942', 're - elected', 'philip philbin ( d ) unopposed'], ['massachusetts 4', 'harold donohue', 'democratic', '1946', 're - elected', 'harold donohue ( d ) 64.5 % robert n scola ( r ) 35.5 %'], ['massachusetts 6', 'william h bates', 'republican', '1950', 're - elected', 'william h bates ( r ) 65.9 % mary kennedy ( d ) 34.1 %'], ['massachusetts 7', 'thomas j lane', 'democratic', '1941', 're - elected', 'thomas j lane ( d ) unopposed'], ['massachusetts 11', "tip o'neill", 'democratic', '1952', 're - elected', "tip o'neill ( d ) unopposed"]] |
brad gumm | https://en.wikipedia.org/wiki/Brad_Gumm | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445678-2.html.csv | majority | the majority of these events took place in the united states . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; location ; united states } = true'} | most_eq { all_rows ; location ; united states } = true | for the location records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'united states_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['loss', '10 - 6 - 1', 'hank weis', 'submission ( guillotine choke )', 'kickdown - sturgis', '1', 'south dakota , united states'], ['loss', '10 - 5 - 1', 'don ortega', 'decision', 'pnrf - explosion', '2', 'mexico'], ['loss', '10 - 4 - 1', 'heath sims', 'submission ( strikes )', 'sf 2 - on the move', '2', 'oregon , united states'], ['loss', '10 - 3 - 1', 'carlos condit', 'tko', 'rof 11 - bring it on', '1', 'colorado , united states'], ['nc', '10 - 2 - 1', 'doug evans', 'no contest - evans kicking in groin', 'ifc - global domination', '1', 'colorado , united states'], ['win', '10 - 2 - 1', 'antoine skinner', 'submission ( omo plata )', 'battleground 1 - war cry', '2', 'illinois , united states'], ['win', '9 - 2 - 1', 'michael buell', 'tko', 'samp - showdown at mcgee park', '2', 'mexico'], ['win', '8 - 2 - 1', 'eric davila', 'decision', 'rof 5 - predators', '3', 'colorado , united states'], ['win', '7 - 2 - 1', 'brad blackburn', 'decision', 'mfc 4 - new groundz', '3', 'alberta , canada'], ['loss', '6 - 2 - 1', 'joe stevenson', 'decision', 'up 1 - ultimate pankration 1', '3', 'california , united states'], ['win', '6 - 1 - 1', 'joe stevenson', 'decision', 'gc 5 - rumble in the rockies', '3', 'colorado , united states'], ['win', '5 - 1 - 1', 'brian dunn', 'submission ( rear naked choke )', 'msf - total destruction', '2', 'south dakota , united states'], ['win', '4 - 1 - 1', 'jeff lindsay', 'decision', 'rof 3 - ring of fire 3', '3', 'colorado , united states'], ['win', '3 - 1 - 1', 'clint rather', 'submission ( rear naked choke )', 'msf - night of thunder', '1', 'colorado , united states'], ['draw', '2 - 1 - 1', 'cj fernandes', 'draw', 'ufc 27', '2', 'louisiana , united states'], ['loss', '2 - 1', 'shonie carter', 'decision', 'ufc 24', '2', 'louisiana , united states'], ['win', '2 - 0', 'dario valdez', 'submission', 'bri 5 - bas rutten invitational 5', '1', 'colorado , united states'], ['win', '1 - 0', 'jason mckeever', 'submission ( arm bar )', 'bri 1 - bas rutten invitational 1', '1', 'united states']] |
port of liverpool | https://en.wikipedia.org/wiki/Port_of_Liverpool | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1136796-1.html.csv | comparative | in 2001 , the port of liverpool handled more tonnes of grain than of timber . | {'row_1': '1', 'row_2': '2', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'product', 'grain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose product record fuzzily matches to grain .', 'tostr': 'filter_eq { all_rows ; product ; grain }'}, '2001'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; product ; grain } ; 2001 }', 'tointer': 'select the rows whose product record fuzzily matches to grain . take the 2001 record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'product', 'timber'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose product record fuzzily matches to timber .', 'tostr': 'filter_eq { all_rows ; product ; timber }'}, '2001'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; product ; timber } ; 2001 }', 'tointer': 'select the rows whose product record fuzzily matches to timber . take the 2001 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; product ; grain } ; 2001 } ; hop { filter_eq { all_rows ; product ; timber } ; 2001 } } = true', 'tointer': 'select the rows whose product record fuzzily matches to grain . take the 2001 record of this row . select the rows whose product record fuzzily matches to timber . take the 2001 record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; product ; grain } ; 2001 } ; hop { filter_eq { all_rows ; product ; timber } ; 2001 } } = true | select the rows whose product record fuzzily matches to grain . take the 2001 record of this row . select the rows whose product record fuzzily matches to timber . take the 2001 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, 'product_7': 7, 'grain_8': 8, '2001_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'product_11': 11, 'timber_12': 12, '2001_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', 'product_7': 'product', 'grain_8': 'grain', '2001_9': '2001', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'product_11': 'product', 'timber_12': 'timber', '2001_13': '2001'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'product_7': [0], 'grain_8': [0], '2001_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'product_11': [1], 'timber_12': [1], '2001_13': [3]} | ['product', '2004', '2003', '2002', '2001'] | [['grain', '2289000 tonnes', '2377000 tonnes', '2360000 tonnes', '2455000 tonnes'], ['timber', '295000 tonnes', '391000 tonnes', '406000 tonnes', '452000 tonnes'], ['bulk liquids', '774000 tonnes', '727000 tonnes', '788000 tonnes', '707000 tonnes'], ['bulk cargo', '6051000 tonnes', '6296000 tonnes', '5572000 tonnes', '5026000 tonnes'], ['oil terminal', '11406000 tonnes', '11406000 tonnes', '11604000 tonnes', '11236000 tonnes'], ['general cargo', '374000 tonnes', '556000 tonnes', '468000 tonnes', '514000 tonnes'], ['total', '32171000 tonnes', '31753000 tonnes', '30564000 tonnes', '30501000 tonnes'], ['passengers', '720000', '734000', '716000', '654000'], ['containers', '616000', '578000', '535000', '524000'], ['roro', '513000', '476000', '502000', '533000']] |
list of cold feet episodes | https://en.wikipedia.org/wiki/List_of_Cold_Feet_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12919003-3.html.csv | unique | episode 5 on the list of cold feet episodes is the only episode directed by pete travis . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'pete travis', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'pete travis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to pete travis .', 'tostr': 'filter_eq { all_rows ; director ; pete travis }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; director ; pete travis } }', 'tointer': 'select the rows whose director record fuzzily matches to pete travis . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'pete travis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to pete travis .', 'tostr': 'filter_eq { all_rows ; director ; pete travis }'}, 'episode'], 'result': 'episode 5', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; director ; pete travis } ; episode }'}, 'episode 5'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; director ; pete travis } ; episode } ; episode 5 }', 'tointer': 'the episode record of this unqiue row is episode 5 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; director ; pete travis } } ; eq { hop { filter_eq { all_rows ; director ; pete travis } ; episode } ; episode 5 } } = true', 'tointer': 'select the rows whose director record fuzzily matches to pete travis . there is only one such row in the table . the episode record of this unqiue row is episode 5 .'} | and { only { filter_eq { all_rows ; director ; pete travis } } ; eq { hop { filter_eq { all_rows ; director ; pete travis } ; episode } ; episode 5 } } = true | select the rows whose director record fuzzily matches to pete travis . there is only one such row in the table . the episode record of this unqiue row is episode 5 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'director_7': 7, 'pete travis_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'episode_9': 9, 'episode 5_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'director_7': 'director', 'pete travis_8': 'pete travis', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'episode_9': 'episode', 'episode 5_10': 'episode 5'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'director_7': [0], 'pete travis_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'episode_9': [2], 'episode 5_10': [3]} | ['', 'episode', 'writer', 'director', 'viewers ( millions )', 'original airdate'] | [['7', 'episode 1', 'mike bullen', 'tom hooper', '8.08', '26 september 1999'], ['8', 'episode 2', 'mike bullen', 'tom hooper', '7.95', '3 october 1999'], ['9', 'episode 3', 'mike bullen', 'tom vaughan', '7.96', '10 october 1999'], ['10', 'episode 4', 'mike bullen', 'tom vaughan', '8.64', '17 october 1999'], ['11', 'episode 5', 'mike bullen', 'pete travis', '9.14', '24 october 1999']] |
2008 - 09 football league trophy | https://en.wikipedia.org/wiki/2008%E2%80%9309_Football_League_Trophy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18720697-4.html.csv | unique | in the 2008 - 09 football league trophy , for games where one team did n't score any points , the only game with attendance over 4000 was when milton keynes dons was the home team . | {'scope': 'subset', 'row': '4', 'col': '5', 'col_other': '2', 'criterion': 'greater_than', 'value': '4000', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': '0'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; 0 }', 'tointer': 'select the rows whose score record fuzzily matches to 0 .'}, 'attendance', '4000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record fuzzily matches to 0 . among these rows , select the rows whose attendance record is greater than 4000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 } }', 'tointer': 'select the rows whose score record fuzzily matches to 0 . among these rows , select the rows whose attendance record is greater than 4000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; 0 }', 'tointer': 'select the rows whose score record fuzzily matches to 0 .'}, 'attendance', '4000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record fuzzily matches to 0 . among these rows , select the rows whose attendance record is greater than 4000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 }'}, 'home team'], 'result': 'milton keynes dons', 'ind': 3, 'tostr': 'hop { filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 } ; home team }'}, 'milton keynes dons'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 } ; home team } ; milton keynes dons }', 'tointer': 'the home team record of this unqiue row is milton keynes dons .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 } } ; eq { hop { filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 } ; home team } ; milton keynes dons } } = true', 'tointer': 'select the rows whose score record fuzzily matches to 0 . among these rows , select the rows whose attendance record is greater than 4000 . there is only one such row in the table . the home team record of this unqiue row is milton keynes dons .'} | and { only { filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 } } ; eq { hop { filter_greater { filter_eq { all_rows ; score ; 0 } ; attendance ; 4000 } ; home team } ; milton keynes dons } } = true | select the rows whose score record fuzzily matches to 0 . among these rows , select the rows whose attendance record is greater than 4000 . there is only one such row in the table . the home team record of this unqiue row is milton keynes dons . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'score_8': 8, '0_9': 9, 'attendance_10': 10, '4000_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'home team_12': 12, 'milton keynes dons_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'score_8': 'score', '0_9': '0', 'attendance_10': 'attendance', '4000_11': '4000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'home team_12': 'home team', 'milton keynes dons_13': 'milton keynes dons'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'score_8': [0], '0_9': [0], 'attendance_10': [1], '4000_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'home team_12': [3], 'milton keynes dons_13': [4]} | ['tie no', 'home team', 'score', 'away team', 'attendance'] | [['1', 'cheltenham town', '1 - 2', 'walsall', '1741'], ['2', 'hereford united', '1 - 2', 'swindon town', '1458'], ['3', 'wycombe wanderers', '0 - 7', 'shrewsbury town', '1730'], ['4', 'milton keynes dons', '0 - 1', 'bournemouth', '4329'], ['5', 'peterborough united', '0 - 1', 'dagenham & redbridge', '2644'], ['6', 'brighton & hove albion', '2 - 2', 'leyton orient', '2157'], ['brighton & hove albion won 5 - 4 on penalties', 'brighton & hove albion won 5 - 4 on penalties', 'brighton & hove albion won 5 - 4 on penalties', 'brighton & hove albion won 5 - 4 on penalties', 'brighton & hove albion won 5 - 4 on penalties'], ['7', 'gillingham', '0 - 1', 'colchester united', '1557'], ['8', 'luton town', '2 - 2', 'brentford', '2029'], ['luton town won 4 - 3 on penalties', 'luton town won 4 - 3 on penalties', 'luton town won 4 - 3 on penalties', 'luton town won 4 - 3 on penalties', 'luton town won 4 - 3 on penalties']] |
list of how it 's made episodes | https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15187735-3.html.csv | aggregation | the average episode number for this list of how it 's made episodes is 32.5 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '32.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'episode'], 'result': '32.5', 'ind': 0, 'tostr': 'avg { all_rows ; episode }'}, '32.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; episode } ; 32.5 } = true', 'tointer': 'the average of the episode record of all rows is 32.5 .'} | round_eq { avg { all_rows ; episode } ; 32.5 } = true | the average of the episode record of all rows is 32.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'episode_4': 4, '32.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'episode_4': 'episode', '32.5_5': '32.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'episode_4': [0], '32.5_5': [1]} | ['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d'] | [['3 - 01', '27', 's02e01', 'pre - inked stamps', 'cranberries', 'cotton yarn', 'road signs'], ['3 - 02', '28', 's02e02', 'combination locks', 'pottery', 's recreational vehicle', 's eraser'], ['3 - 03', '29', 's02e03', 'wheel loaders', 'vegetable oil', 'hand tools', 'cotton swabs'], ['3 - 04', '30', 's02e04', 'temporary metal fences', 'asphalt shingles', 'expanded polystyrene products', 'hard candies'], ['3 - 05', '31', 's02e05', 's horse - drawn carriage', 'artificial eyes', 'dog and cat food', 's mirror'], ['3 - 06', '32', 's02e06', 'yogurt', 'candles', 'neon signs', 's bookbinding'], ['3 - 07', '33', 's02e07', 'prepared mustard', 's violin', 'nuts and bolts', 'toilet paper'], ['3 - 08', '34', 's02e08', 'fresh cut flowers', 'adhesive tape', 'tofu', 's lottery ticket'], ['3 - 09', '35', 's02e09', 'inflatable watercraft', 'couscous', 'modelling dough', 'wicker products'], ['3 - 10', '36', 's02e10', 'wind generators', 'pvc gloves', 'thermo - formed glass', 'fire trucks'], ['3 - 11', '37', 's02e11', 'car radiators', 'hatchery chicks', 'phyllo dough', 'cross - country skis'], ['3 - 12', '38', 's02e12', 'electric baseboard heaters', 'ed mould pulp containers', 'chicken', 's video game']] |
elena pampoulova | https://en.wikipedia.org/wiki/Elena_Pampoulova | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18330817-8.html.csv | ordinal | the second to last tournament for elena pampoulova was the tournament in croatia . | {'row': '12', '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', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date ; 2 }'}, 'tournament'], 'result': 'makarska , croatia itf 75000', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date ; 2 } ; tournament }'}, 'makarska , croatia itf 75000'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; date ; 2 } ; tournament } ; makarska , croatia itf 75000 } = true', 'tointer': 'select the row whose date record of all rows is 2nd maximum . the tournament record of this row is makarska , croatia itf 75000 .'} | eq { hop { nth_argmax { all_rows ; date ; 2 } ; tournament } ; makarska , croatia itf 75000 } = true | select the row whose date record of all rows is 2nd maximum . the tournament record of this row is makarska , croatia itf 75000 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'tournament_7': 7, 'makarska , croatia itf 75000_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', 'date_5': 'date', '2_6': '2', 'tournament_7': 'tournament', 'makarska , croatia itf 75000_8': 'makarska , croatia itf 75000'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'tournament_7': [1], 'makarska , croatia itf 75000_8': [2]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['runner - ups', 'november 4 , 1988', 'melbourne , australia itf 10000', 'hard', 'kristin godridge', 'natalia leipus bernadette randall - marshall', '4 - 6 , 7 - 6 ( 7 - 5 ) , 2 - 6'], ['winners', 'april 9 , 1989', 'bari , italy itf 10000', 'clay', 'marion maruska', 'andrea noszály eva maria schuerhoff', 'w / o'], ['winners', 'june 14 , 1992', 'modena , italy itf 25000', 'clay', 'ruxandra dragomir', 'alexandra fusai nathalie tschan', '6 - 3 , 7 - 6 ( 7 - 5 )'], ['runner - ups', 'august 4 , 1992', 'vaihingen , germany itf 25000', 'clay', 'joannette kruger', 'eva martincová pavlína rajzlová', '4 - 6 , 0 - 6'], ['runner - ups', 'november 15 , 1992', 'manchester , united kingdom itf 25000', 'carpet ( i )', 'nathalie tschan', 'elena likhovtseva elena makarova', '3 - 6 , 4 - 6'], ['winners', 'november 22 , 1992', 'nottingham , united kingdom itf 25000', 'carpet ( i )', 'els callens', 'ruxandra dragomir irina spîrlea', '7 - 6 ( 7 - 3 ) , 6 - 4'], ['winners', 'april 11 , 1993', 'limoges , france itf 25000', 'carpet ( i )', 'silvia farina elia', 'stephanie reece danielle scott', '6 - 2 , 6 - 7 ( 5 - 7 ) , 6 - 2'], ['winners', 'april 11 , 1993', 'poitiers , france itf 25000', 'hard', 'olga lugina', 'els callens nancy feber', '6 - 4 , 3 - 6 , 6 - 3'], ['winners', 'december 11 , 1994', 'cergy - pontoise , france itf 50000', 'hard ( i )', 'angelique olivier', 'kateřina šišková eva melicharová', '6 - 1 , 6 - 4'], ['winners', 'october 29 , 1995', 'lakeland , fl , usa itf 50000', 'hard', 'eva martincová', 'sandra cacic tracey rodgers', '1 - 6 , 6 - 2 , 6 - 1'], ['runner - ups', 'december 3 , 1995', 'limoges , france itf 50000', 'hard', 'eva martincová', 'eva melicharová helena vildová', '3 - 6 , 6 - 0 , 4 - 6'], ['winners', 'october 29 , 1997', 'makarska , croatia itf 75000', 'clay', 'olga lugina', 'maria goloviznina evgenia kulikovskaya', '5 - 7 , 7 - 5 , 7 - 5'], ['runner - ups', 'april 26 , 1998', 'prostějov , czech republic itf 75000', 'clay', 'olga lugina', 'lenka cenková kateřina šišková', '4 - 6 , 6 - 4 , 4 - 6']] |
1998 icc knockout trophy | https://en.wikipedia.org/wiki/1998_ICC_KnockOut_Trophy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11950720-4.html.csv | ordinal | for the players in the 1998 icc knockout trophy , the player who is the 2nd to youngest was matthew bell . | {'row': '5', 'col': '3', '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', 'date of birth', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date of birth ; 2 }'}, 'player'], 'result': 'matthew bell', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date of birth ; 2 } ; player }'}, 'matthew bell'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; date of birth ; 2 } ; player } ; matthew bell } = true', 'tointer': 'select the row whose date of birth record of all rows is 2nd maximum . the player record of this row is matthew bell .'} | eq { hop { nth_argmax { all_rows ; date of birth ; 2 } ; player } ; matthew bell } = true | select the row whose date of birth record of all rows is 2nd maximum . the player record of this row is matthew bell . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date of birth_5': 5, '2_6': 6, 'player_7': 7, 'matthew bell_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', 'date of birth_5': 'date of birth', '2_6': '2', 'player_7': 'player', 'matthew bell_8': 'matthew bell'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date of birth_5': [0], '2_6': [0], 'player_7': [1], 'matthew bell_8': [2]} | ['no', 'player', 'date of birth', 'batting style', 'bowling style', 'first class team'] | [['88', 'stephen fleming ( captain )', '1 april 1973', 'left hand bat', 'right arm medium', 'cantebury wellington'], ['98', 'geoff allott', '24 december 1971', 'right hand bat', 'left arm fast - medium', 'cantebury'], ['93', 'nathan astle', '15 september 1971', 'right hand bat', 'right arm medium', 'cantebury'], ['106', 'mark bailey', '26 november 1970', 'right hand bat', 'right arm medium', 'northern districts'], ['107', 'matthew bell', '25 february 1977', 'right hand bat', 'right arm off break', 'wellington northern districts'], ['78', 'simon doull', '6 august 1969', 'right hand bat', 'right arm medium', 'northern districts'], ['72', 'chris harris', '20 november 1969', 'left hand bat', 'right arm medium', 'cantebury'], ['99', 'matt horne', '5 december 1970', 'right hand bat', 'right arm medium', 'otago'], ['102', 'craig mcmillan', '13 september 1976', 'right hand bat', 'right arm medium', 'cantebury'], ['103', "shayne o'connor", '15 november 1973', 'left hand bat', 'left arm fast - medium', 'otago'], ['80', 'adam parore ( wicket - keeper )', '23 january 1971', 'right hand bat', 'wicket - keeper', 'auckland'], ['108', 'alex tait', '13 june 1972', 'right hand bat', 'right arm medium', 'northern districts'], ['100', 'daniel vettori', '27 january 1979', 'left hand bat', 'left arm orthodox spin', 'northern districts'], ['105', 'paul wiseman', '4 may 1970', 'right hand bat', 'right arm off break', 'otago cantebury']] |
2010 - 11 robert morris colonials men 's basketball team | https://en.wikipedia.org/wiki/2010%E2%80%9311_Robert_Morris_Colonials_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29970488-2.html.csv | count | there were 5 sophomore players that played on the 2010-11 morris colonials men 's basketball team . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'sophomore', 'result': '5', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', 'sophomore'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to sophomore .', 'tostr': 'filter_eq { all_rows ; year ; sophomore }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year ; sophomore } }', 'tointer': 'select the rows whose year record fuzzily matches to sophomore . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year ; sophomore } } ; 5 } = true', 'tointer': 'select the rows whose year record fuzzily matches to sophomore . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; year ; sophomore } } ; 5 } = true | select the rows whose year record fuzzily matches to sophomore . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, 'sophomore_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', 'sophomore_6': 'sophomore', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], 'sophomore_6': [0], '5_7': [2]} | ['name', '-', 'position', 'height', 'weight ( lb )', 'year', 'hometown', 'previous school'] | [['karon abraham', '4', 'guard', 'ft9in ( m )', '150', '2 sophomore', 'paterson , nj', 'paterson eastside hs'], ['lawrence bridges', '24', 'forward', 'ft5in ( m )', '220', '2 junior', 'detroit , mi', 'columbus state community college'], ['yann charles', '25', 'forward', 'ft5in ( m )', '220', '2 freshman', 'longueuil , qc , canada', 'champlain saint - albert hs'], ['russell johnson', '34', 'forward', 'ft6in ( m )', '180', '2 sophomore ( rs )', 'chester , pa', 'chester hs'], ['velton jones', '2', 'guard', 'ft0in ( m )', '170', '2 sophomore ( rs )', 'philadelphia , pa', 'northeast catholic hs'], ['treadwell lewis', '10', 'guard', 'ft10in ( m )', '170', '2 sophomore', 'shelton , ct', 'christian heritage school'], ['anthony myers', '5', 'guard', 'ft11in ( m )', '170', '2 freshman', 'washington , dc', 'charis prep'], ['elton roy', '15', 'guard', 'ft2in ( m )', '195', '2 freshman', 'houston , tx', 'yates hs'], ['lijah thompson', '11', 'forward / center', 'ft7in ( m )', '200', '2 sophomore', 'philadelphia , pa', 'monsignor bonner hs'], ['deion turman', '1', 'forward / center', 'ft8in ( m )', '215', '2 freshman', 'pittsburgh , pa', 'mt lebanon hs'], ['gary wallace', '14', 'guard', 'ft3in ( m )', '200', '2 senior', 'montclair , nj', 'seton hall preparatory school']] |
2008 - 09 united states network television schedule | https://en.wikipedia.org/wiki/2008%E2%80%9309_United_States_network_television_schedule | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15708593-12.html.csv | count | the office is playing on 2 channels at 9:00 . | {'scope': 'all', 'criterion': 'equal', 'value': 'the office', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '9:00', 'the office'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 9:00 record fuzzily matches to the office .', 'tostr': 'filter_eq { all_rows ; 9:00 ; the office }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; 9:00 ; the office } }', 'tointer': 'select the rows whose 9:00 record fuzzily matches to the office . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; 9:00 ; the office } } ; 2 } = true', 'tointer': 'select the rows whose 9:00 record fuzzily matches to the office . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; 9:00 ; the office } } ; 2 } = true | select the rows whose 9:00 record fuzzily matches to the office . 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, '9:00_5': 5, 'the office_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', '9:00_5': '9:00', 'the office_6': 'the office', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '9:00_5': [0], 'the office_6': [0], '2_7': [2]} | ['8:00', '8:30', '9:00', '9:30', '10:00'] | [['in the motherhood', 'samantha who', "grey 's anatomy", "grey 's anatomy", 'private practice'], ['ugly betty', 'ugly betty', "grey 's anatomy", "grey 's anatomy", 'private practice'], ['survivor : tocantins - the brazilian highlands', 'survivor : tocantins - the brazilian highlands', 'csi : crime scene investigation', 'csi : crime scene investigation', "harper 's island"], ['survivor : tocantins - the brazilian highlands', 'survivor : tocantins - the brazilian highlands', 'csi : crime scene investigation', 'csi : crime scene investigation', 'various crimetime programs ( reruns )'], ['smallville', 'smallville', 'supernatural', 'supernatural', 'local programming'], ['bones', 'bones', "hell 's kitchen", "hell 's kitchen", 'local programming'], ['my thursday night movie', 'my thursday night movie', 'my thursday night movie', 'my thursday night movie', 'local programming'], ['my name is earl', 'kath & kim', 'the office', '30 rock', 'southland'], ['my name is earl', 'parks and recreation', 'the office', '30 rock', 'southland']] |
latin americans | https://en.wikipedia.org/wiki/Latin_Americans | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1333612-1.html.csv | comparative | the dominican republic has a higher percentage of asian people than costa rica . | {'row_1': '8', 'row_2': '6', 'col': '9', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'dominican republic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to dominican republic .', 'tostr': 'filter_eq { all_rows ; country ; dominican republic }'}, 'asians'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; dominican republic } ; asians }', 'tointer': 'select the rows whose country record fuzzily matches to dominican republic . take the asians record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'costa rica'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to costa rica .', 'tostr': 'filter_eq { all_rows ; country ; costa rica }'}, 'asians'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; costa rica } ; asians }', 'tointer': 'select the rows whose country record fuzzily matches to costa rica . take the asians record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; country ; dominican republic } ; asians } ; hop { filter_eq { all_rows ; country ; costa rica } ; asians } } = true', 'tointer': 'select the rows whose country record fuzzily matches to dominican republic . take the asians record of this row . select the rows whose country record fuzzily matches to costa rica . take the asians record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; country ; dominican republic } ; asians } ; hop { filter_eq { all_rows ; country ; costa rica } ; asians } } = true | select the rows whose country record fuzzily matches to dominican republic . take the asians record of this row . select the rows whose country record fuzzily matches to costa rica . take the asians 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, 'country_7': 7, 'dominican republic_8': 8, 'asians_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'costa rica_12': 12, 'asians_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', 'country_7': 'country', 'dominican republic_8': 'dominican republic', 'asians_9': 'asians', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'costa rica_12': 'costa rica', 'asians_13': 'asians'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'dominican republic_8': [0], 'asians_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'costa rica_12': [1], 'asians_13': [3]} | ['country', 'population', 'native american', 'whites', 's mestizo', 'es mulatto', 'blacks', 's zambo', 'asians'] | [['argentina', '40134425', '1.0 %', '85.0 %', '11.1 %', '0.0 %', '0.0 %', '0.0 %', '2.9 %'], ['bolivia', '10907778', '55.0 %', '15.0 %', '28.0 %', '2.0 %', '0.0 %', '0.0 %', '0.0 %'], ['brazil', '192272890', '0.4 %', '53.8 %', '0.0 %', '39.1 %', '6.2 %', '0.0 %', '0.5 %'], ['chile', '17063000', '3.2 %', '52.7 %', '44.1 %', '0.0 %', '0.0 %', '0.0 %', '0.0 %'], ['colombia', '45393050', '1.8 %', '20.0 %', '53.2 %', '21.0 %', '3.9 %', '0.1 %', '0.0 %'], ['costa rica', '4253897', '0.8 %', '82.0 %', '15.0 %', '0.0 %', '0.0 %', '2.0 %', '0.2 %'], ['cuba', '11236444', '0.0 %', '37.0 %', '0.0 %', '51.0 %', '11.0 %', '0.0 %', '1.0 %'], ['dominican republic', '8562541', '0.0 %', '14.6 %', '0.0 %', '75.0 %', '7.7 %', '2.3 %', '0.4 %'], ['ecuador', '13625000', '39.0 %', '9.9 %', '41.0 %', '5.0 %', '5.0 %', '0.0 %', '0.1 %'], ['el salvador', '6134000', '1.0 %', '12.0 %', '86.0 %', '0.0 %', '0.0 %', '0.0 %', '0.0 %'], ['guatemala', '13276517', '53.0 %', '4.0 %', '42.0 %', '0.0 %', '0.0 %', '0.2 %', '0.8 %'], ['honduras', '7810848', '7.7 %', '1.0 %', '85.6 %', '1.7 %', '0.0 %', '3.3 %', '0.7 %'], ['mexico', '112322757', '14 %', '15 %', '70 %', '0.5 %', '0.0 %', '0.0 %', '0.5 %'], ['nicaragua', '5891199', '6.9 %', '14.0 %', '78.3 %', '0.0 %', '0.0 %', '0.6 %', '0.2 %'], ['panama', '3322576', '8.0 %', '10.0 %', '32.0 %', '27.0 %', '5.0 %', '14.0 %', '4.0 %'], ['paraguay', '6349000', '1.5 %', '20.0 %', '74.5 %', '3.5 %', '0.0 %', '0.0 %', '0.5 %'], ['peru', '29461933', '45.5 %', '12.0 %', '32.0 %', '9.7 %', '0.0 %', '0.0 %', '0.8 %'], ['puerto rico', '3967179', '0.0 %', '74.8 %', '0.0 %', '10.0 %', '15.0 %', '0.0 %', '0.2 %'], ['uruguay', '3494382', '0.0 %', '88.0 %', '8.0 %', '4.0 %', '0.0 %', '0.0 %', '0.0 %'], ['venezuela', '26814843', '2.7 %', '42.2 %', '42.9 %', '0.7 %', '2.8 %', '0.0 %', '2.2 %']] |
2000 new orleans saints season | https://en.wikipedia.org/wiki/2000_New_Orleans_Saints_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16710999-1.html.csv | majority | in december of 2000 , there were less than 67000 in the crowd for most of the saints games . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '67000', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'december'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; december }', 'tointer': 'select the rows whose date record fuzzily matches to december .'}, 'attendance', '67000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december . for the attendance records of these rows , most of them are less than 67000 .', 'tostr': 'most_less { filter_eq { all_rows ; date ; december } ; attendance ; 67000 } = true'} | most_less { filter_eq { all_rows ; date ; december } ; attendance ; 67000 } = true | select the rows whose date record fuzzily matches to december . for the attendance records of these rows , most of them are less than 67000 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'december_5': 5, 'attendance_6': 6, '67000_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'december_5': 'december', 'attendance_6': 'attendance', '67000_7': '67000'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'december_5': [0], 'attendance_6': [1], '67000_7': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 3 , 2000', 'detroit lions', 'l 14 - 10', '64900'], ['2', 'september 10 , 2000', 'san diego chargers', 'w 28 - 27', '51300'], ['3', 'september 17 , 2000', 'seattle seahawks', 'l 20 - 10', '59513'], ['4', 'september 24 , 2000', 'philadelphia eagles', 'l 21 - 7', '64900'], ['6', 'october 8 , 2000', 'chicago bears', 'w 31 - 10', '66944'], ['7', 'october 15 , 2000', 'carolina panthers', 'w 24 - 6', '50015'], ['8', 'october 22 , 2000', 'atlanta falcons', 'w 21 - 19', '56508'], ['9', 'october 29 , 2000', 'arizona cardinals', 'w 21 - 10', '35016'], ['10', 'november 5 , 2000', 'san francisco 49ers', 'w 31 - 15', '64900'], ['11', 'november 12 , 2000', 'carolina panthers', 'w 20 - 10', '72981'], ['12', 'november 19 , 2000', 'oakland raiders', 'l 31 - 22', '64900'], ['13', 'november 26 , 2000', 'st louis rams', 'w 31 - 24', '66064'], ['14', 'december 3 , 2000', 'denver broncos', 'l 38 - 23', '64900'], ['15', 'december 10 , 2000', 'san francisco 49ers', 'w 31 - 27', '67892'], ['16', 'december 17 , 2000', 'atlanta falcons', 'w 23 - 7', '64900'], ['17', 'december 24 , 2000', 'st louis rams', 'l 26 - 21', '64900']] |
2000 england rugby union tour of south africa | https://en.wikipedia.org/wiki/2000_England_rugby_union_tour_of_South_Africa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17891863-1.html.csv | aggregation | opposing teams made on average 21 points against the 2000 england rugby team in the union tour of south africa . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '21', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'against'], 'result': '21', 'ind': 0, 'tostr': 'avg { all_rows ; against }'}, '21'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; against } ; 21 } = true', 'tointer': 'the average of the against record of all rows is 21 .'} | round_eq { avg { all_rows ; against } ; 21 } = true | the average of the against record of all rows is 21 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'against_4': 4, '21_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'against_4': 'against', '21_5': '21'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'against_4': [0], '21_5': [1]} | ['opposing team', 'against', 'date', 'venue', 'status', 'report'] | [['north west leopards', '22', '13 june 2000', 'olãn park , potchefstroom', 'tour match', 'bbc sport'], ['south africa', '18', '17 june 2000', 'loftus versfeld , pretoria', 'first test', 'bbc sport'], ['nashua griquas', '16', '20 june 2000', 'asba park , kimberley', 'tour match', 'bbc sport'], ['south africa', '22', '24 june 2000', 'vodacom park , bloemfontein', 'second test', 'bbc sport'], ['gauteng falcons', '27', '28 june 2000', 'bosman stadium , brakpan', 'tour match', 'bbc sport']] |
1973 - 74 segunda división | https://en.wikipedia.org/wiki/1973%E2%80%9374_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12252458-2.html.csv | unique | in the 1973-4 segunda division , cordoba cf were the only team to have a goal difference of 0 . | {'scope': 'all', 'row': '13', 'col': '10', 'col_other': '2', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goal difference', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goal difference record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; goal difference ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; goal difference ; 0 } }', 'tointer': 'select the rows whose goal difference record is equal to 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goal difference', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goal difference record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; goal difference ; 0 }'}, 'club'], 'result': 'córdoba cf', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; goal difference ; 0 } ; club }'}, 'córdoba cf'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; goal difference ; 0 } ; club } ; córdoba cf }', 'tointer': 'the club record of this unqiue row is córdoba cf .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; goal difference ; 0 } } ; eq { hop { filter_eq { all_rows ; goal difference ; 0 } ; club } ; córdoba cf } } = true', 'tointer': 'select the rows whose goal difference record is equal to 0 . there is only one such row in the table . the club record of this unqiue row is córdoba cf .'} | and { only { filter_eq { all_rows ; goal difference ; 0 } } ; eq { hop { filter_eq { all_rows ; goal difference ; 0 } ; club } ; córdoba cf } } = true | select the rows whose goal difference record is equal to 0 . there is only one such row in the table . the club record of this unqiue row is córdoba cf . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'goal difference_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'córdoba cf_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'goal difference_7': 'goal difference', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'córdoba cf_10': 'córdoba cf'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'goal difference_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'córdoba cf_10': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'real betis', '38', '51 + 13', '19', '13', '6', '69', '31', '+ 38'], ['2', 'hércules cf', '38', '49 + 11', '20', '9', '9', '51', '34', '+ 17'], ['3', 'ud salamanca', '38', '48 + 10', '20', '8', '10', '53', '39', '+ 14'], ['4', 'cd tenerife', '38', '46 + 8', '19', '8', '11', '57', '41', '+ 16'], ['5', 'cádiz cf', '38', '46 + 8', '18', '10', '10', '52', '37', '+ 15'], ['6', 'gimnástico de tarragona', '38', '41 + 3', '16', '9', '13', '46', '40', '+ 6'], ['7', 'real valladolid', '38', '41 + 3', '16', '9', '13', '61', '50', '+ 11'], ['8', 'cd san andrés', '38', '39 + 1', '16', '7', '15', '47', '38', '+ 9'], ['9', 'sevilla fc', '38', '39 + 1', '15', '9', '14', '48', '40', '+ 8'], ['10', 'baracaldo cf', '38', '39 + 1', '14', '11', '13', '49', '52', '- 3'], ['11', 'rcd mallorca', '38', '39 + 1', '12', '15', '11', '36', '32', '+ 4'], ['12', 'cd orense', '38', '38', '13', '12', '13', '43', '45', '- 2'], ['13', 'córdoba cf', '38', '38', '16', '6', '16', '58', '58', '0'], ['14', 'rayo vallecano', '38', '33 - 5', '14', '5', '19', '39', '51', '- 12'], ['15', 'cd sabadell', '38', '33 - 5', '11', '11', '16', '35', '52', '- 17'], ['16', 'burgos cf', '38', '32 - 6', '13', '6', '19', '34', '44', '- 10'], ['17', 'ca osasuna', '38', '28 - 10', '10', '8', '20', '36', '63', '- 27'], ['18', 'deportivo de la coruña', '38', '28 - 10', '11', '6', '21', '30', '56', '- 26'], ['19', 'levante ud', '38', '27 - 11', '10', '7', '21', '37', '48', '- 11'], ['20', 'linares cf', '38', '25 - 13', '8', '9', '21', '29', '59', '- 30']] |
list of australian rugby league grand final records | https://en.wikipedia.org/wiki/List_of_Australian_rugby_league_grand_final_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16633950-2.html.csv | count | the canterbury - bankstown bulldogs were runners up two times in australian rugby league grand final records . | {'scope': 'all', 'criterion': 'equal', 'value': 'canterbury - bankstown bulldogs', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runners up', 'canterbury - bankstown bulldogs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runners up record fuzzily matches to canterbury - bankstown bulldogs .', 'tostr': 'filter_eq { all_rows ; runners up ; canterbury - bankstown bulldogs }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; runners up ; canterbury - bankstown bulldogs } }', 'tointer': 'select the rows whose runners up record fuzzily matches to canterbury - bankstown bulldogs . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; runners up ; canterbury - bankstown bulldogs } } ; 2 } = true', 'tointer': 'select the rows whose runners up record fuzzily matches to canterbury - bankstown bulldogs . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; runners up ; canterbury - bankstown bulldogs } } ; 2 } = true | select the rows whose runners up record fuzzily matches to canterbury - bankstown bulldogs . 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, 'runners up_5': 5, 'canterbury - bankstown bulldogs_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', 'runners up_5': 'runners up', 'canterbury - bankstown bulldogs_6': 'canterbury - bankstown bulldogs', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'runners up_5': [0], 'canterbury - bankstown bulldogs_6': [0], '2_7': [2]} | ['points', 'score', 'premiers', 'runners up', 'details'] | [['42', '42 - 14', 'south sydney rabbitohs', 'manly - warringah sea eagles', '1951 nswrfl grand final'], ['40', '40 - 0', 'manly - warringah sea eagles', 'melbourne storm', '2008 nrl grand final'], ['38', '38 - 0', 'eastern suburbs', 'st george dragons', '1975 nswrfl grand final'], ['38', '38 - 12', 'brisbane broncos', 'canterbury - bankstown bulldogs', '1998 nrl grand final'], ['36', '36 - 12', 'canberra raiders', 'canterbury - bankstown bulldogs', '1994 nswrl grand final']] |
2007 - 08 birmingham city f.c. season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Birmingham_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15120038-1.html.csv | count | 2 of the games in the 2007-08 birmingham city f.c. season had a score of 3-0 . | {'scope': 'all', 'criterion': 'equal', 'value': '3-0', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score f - a', '3-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score f - a record fuzzily matches to 3-0 .', 'tostr': 'filter_eq { all_rows ; score f - a ; 3-0 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score f - a ; 3-0 } }', 'tointer': 'select the rows whose score f - a record fuzzily matches to 3-0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score f - a ; 3-0 } } ; 2 } = true', 'tointer': 'select the rows whose score f - a record fuzzily matches to 3-0 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; score f - a ; 3-0 } } ; 2 } = true | select the rows whose score f - a record fuzzily matches to 3-0 . 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, 'score f - a_5': 5, '3-0_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', 'score f - a_5': 'score f - a', '3-0_6': '3-0', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score f - a_5': [0], '3-0_6': [0], '2_7': [2]} | ['date', 'opponents', 'venue', 'result', 'score f - a'] | [['16 july 2007', 'hollenbach / hohenlohe auswahl', 'a', 'w', '2 - 0'], ['18 july 2007', '1 . fc heidenheim', 'a', 'w', '2 - 0'], ['23 july 2007', 'fc schweinfurt 05', 'a', 'w', '5 - 2'], ['28 july 2007', 'walsall', 'a', 'w', '2 - 0'], ['31 july 2007', 'peterborough united', 'a', 'w', '3 - 0'], ['4 august 2007', 'sheffield wednesday', 'a', 'w', '3 - 0']] |
greek government - debt crisis | https://en.wikipedia.org/wiki/Greek_government-debt_crisis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27146868-1.html.csv | superlative | the most debt was owed by the greek government in the year of 2014 . | {'scope': 'all', 'col_superlative': '24', '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', '2014 2'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 2014 2 }'}, 'greek national account'], 'result': 'public debt 8 ( billion )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; 2014 2 } ; greek national account }'}, 'public debt 8 ( billion )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; 2014 2 } ; greek national account } ; public debt 8 ( billion ) } = true', 'tointer': 'select the row whose 2014 2 record of all rows is maximum . the greek national account record of this row is public debt 8 ( billion ) .'} | eq { hop { argmax { all_rows ; 2014 2 } ; greek national account } ; public debt 8 ( billion ) } = true | select the row whose 2014 2 record of all rows is maximum . the greek national account record of this row is public debt 8 ( billion ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, '2014 2_5': 5, 'greek national account_6': 6, 'public debt 8 (billion )_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', '2014 2_5': '2014 2', 'greek national account_6': 'greek national account', 'public debt 8 (billion )_7': 'public debt 8 ( billion )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], '2014 2_5': [0], 'greek national account_6': [1], 'public debt 8 (billion )_7': [2]} | ['greek national account', '1970', '1980', '1990', '1995', '1996', '1997', '1998', '1999', '2000', '2001 1', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013 2', '2014 2', '2015 3'] | [['public revenue ( % of gdp )', 'n / a', 'n / a', '31.0', '37.0', '37.8', '39.3', '40.9', '41.8', '43.4', '41.3', '40.6', '39.4', '38.4', '39.0', '39.2', '40.7', '40.7', '38.3', '40.6', '42.4', '44.7', '43.5', '43.9', 'n / a'], ['public expenditure 4 ( % of gdp )', 'n / a', 'n / a', '45.2', '46.2', '44.5', '45.3', '44.7', '44.8', '47.1', '45.8', '45.4', '45.1', '46.0', '44.4', '45.0', '47.2', '50.5', '54.0', '51.3', '51.9', '54.7', '47.3', '46.5', 'n / a'], ['budget deficit 4 ( % of gdp )', 'n / a', 'n / a', '14.2', '9.1', '6.7', '5.9', '3.9', '3.1', '3.7', '4.5', '4.8', '5.7', '7.6', '5.5', '5.7', '6.5', '9.8', '15.6', '10.7', '9.5', '10.0', '3.8', '2.6', 'tba'], ['structural deficit 5 ( % of gdp )', 'n / a', 'n / a', '14.8', '9.1', '6.6', '6.1', '4.1', '3.3', '4.0', '4.6', '4.3', '5.6', '7.8', '5.3', '6.8', '7.9', '9.6', '14.8', '8.8', '5.4', '1.0', '- 2.0', '- 2.0', 'n / a'], ['hicp inflation ( annual % )', 'n / a', 'n / a', 'n / a', '8.9', '7.9', '5.4', '4.5', '2.1', '2.9', '3.7', '3.9', '3.4', '3.0', '3.5', '3.3', '3.0', '4.2', '1.3', '4.7', '3.1', '1.0', '- 0.8', '- 0.4', 'n / a'], ['gdp deflator 6 ( annual % )', '3.8', '19.3', '20.7', '9.8', '7.3', '6.8', '5.2', '3.0', '3.4', '3.1', '3.4', '3.9', '2.9', '2.8', '2.4', '3.3', '4.7', '2.3', '1.1', '1.0', '- 0.8', '- 1.1', '- 0.4', 'tba'], ['real gdp growth 7 ( % )', '8.9', '0.7', '0.0', '2.1', '2.4', '3.6', '3.4', '3.4', '4.5', '4.2', '3.4', '5.9', '4.4', '2.3', '5.5', '3.5', '0.2', '3.1', '4.9', '7.1', '6.4', '- 4.2', '0.6', 'tba'], ['public debt 8 ( billion )', '0.2', '1.5', '31.1', '86.9', '97.8', '105.2', '111.9', '118.6', '141.0', '151.9', '159.2', '168.0', '183.2', '195.4', '224.2', '239.3', '263.3', '299.7', '329.5', '355.2', '303.9', '321.5', '322.2', 'tba']] |
dustley mulder | https://en.wikipedia.org/wiki/Dustley_Mulder | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11415108-1.html.csv | count | dustley mulder scored had exactly 37 appearances in two different seasons . | {'scope': 'all', 'criterion': 'equal', 'value': '37', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'apps', '37'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose apps record is equal to 37 .', 'tostr': 'filter_eq { all_rows ; apps ; 37 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; apps ; 37 } }', 'tointer': 'select the rows whose apps record is equal to 37 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; apps ; 37 } } ; 2 } = true', 'tointer': 'select the rows whose apps record is equal to 37 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; apps ; 37 } } ; 2 } = true | select the rows whose apps record is equal to 37 . 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, 'apps_5': 5, '37_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'apps_5': 'apps', '37_6': '37', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'apps_5': [0], '37_6': [0], '2_7': [2]} | ['season', 'club', 'apps', 'goals', 'division'] | [['2004 / 05', 'excelsior', '22', '3', '2'], ['2005 / 06', 'excelsior', '24', '1', '2'], ['2005 / 06', 'rkc waalwijk', '11', '0', '1'], ['2006 / 07', 'rkc waalwijk', '25', '1', '1'], ['2007 / 08', 'rkc waalwijk', '37', '1', '2'], ['2008 / 09', 'rkc waalwijk', '37', '1', '2'], ['2009 / 10', 'rkc waalwijk', '32', '1', '1']] |
list of make it or break it episodes | https://en.wikipedia.org/wiki/List_of_Make_It_or_Break_It_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23399481-3.html.csv | superlative | the movie title , the new normal , directed by michael lange has had the most u.s views of all the other titles . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '11', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3,4', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( in millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( in millions ) }'}, 'title'], 'result': 'the new normal', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( in millions ) } ; title }'}, 'the new normal'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( in millions ) } ; title } ; the new normal }', 'tointer': 'select the row whose us viewers ( in millions ) record of all rows is maximum . the title record of this row is the new normal .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( in millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( in millions ) }'}, 'directed by'], 'result': 'michael lange', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; us viewers ( in millions ) } ; directed by }'}, 'michael lange'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( in millions ) } ; directed by } ; michael lange }', 'tointer': 'the directed by record of this row is michael lange .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; us viewers ( in millions ) } ; title } ; the new normal } ; eq { hop { argmax { all_rows ; us viewers ( in millions ) } ; directed by } ; michael lange } } = true', 'tointer': 'select the row whose us viewers ( in millions ) record of all rows is maximum . the title record of this row is the new normal . the directed by record of this row is michael lange .'} | and { eq { hop { argmax { all_rows ; us viewers ( in millions ) } ; title } ; the new normal } ; eq { hop { argmax { all_rows ; us viewers ( in millions ) } ; directed by } ; michael lange } } = true | select the row whose us viewers ( in millions ) record of all rows is maximum . the title record of this row is the new normal . the directed by record of this row is michael lange . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'us viewers (in millions)_8': 8, 'title_9': 9, 'the new normal_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'directed by_11': 11, 'michael lange_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', 'us viewers (in millions)_8': 'us viewers ( in millions )', 'title_9': 'title', 'the new normal_10': 'the new normal', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'directed by_11': 'directed by', 'michael lange_12': 'michael lange'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'us viewers (in millions)_8': [0], 'title_9': [1], 'the new normal_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'directed by_11': [3], 'michael lange_12': [4]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( in millions )'] | [['21', '1', 'friends close , enemies closer', 'patrick norris', 'joanna johnson', 'june 28 , 2010', '1.83'], ['22', '2', 'all or nothing', 'fred gerber', 'kerry lenhart & john j sakmar', 'july 5 , 2010', '1.72'], ['23', '3', 'battle of the flexes', 'j miller tobin', 'amy turner', 'july 13 , 2010', '1.56'], ['24', '4', 'and the rocky goes to', 'bethany rooney', 'holly sorensen', 'july 20 , 2010', '1.46'], ['25', '5', "i wo n't dance , do n't ask me", 'david paymer', 'michael gans & richard register', 'july 27 , 2010', '1.66'], ['26', '6', 'party gone out of bounds', 'felix alcala', 'joanna johnson', 'august 3 , 2010', '1.75'], ['27', '7', 'what are you made of', 'glenn l steelman', 'holly sorensen', 'august 10 , 2010', '1.56'], ['28', '8', 'rock bottom', 'chris grismer', 'liz maccie', 'august 17 , 2010', '1.30'], ['29', '9', 'if only', 'david paymer', 'michael gans & richard register', 'august 24 , 2010', '1.42'], ['30', '10', 'the edge of the worlds', 'chris grismer', 'kerry lenhart & john j sakmar', 'august 31 , 2010', '1.44'], ['31', '11', 'the new normal', 'michael lange', 'holly sorensen', 'march 28 , 2011', '2.06'], ['32', '12', 'free people', 'fred gerber', 'joanna johnson', 'april 4 , 2011', '1.69'], ['33', '13', 'the buddy system', 'glenn l steelman', 'amy turner', 'april 11 , 2011', '1.64'], ['34', '14', 'life or death', 'david paymer', 'michael gans & richard register', 'april 18 , 2011', '1.58'], ['35', '15', 'hungary heart', 'rod hardy', 'kerry lenhart & john j sakmar', 'april 25 , 2011', '1.64'], ['36', '16', 'requiem for a dream', 'michael schultz', 'holly sorenson', 'may 2 , 2011', '1.65'], ['37', '17', 'to thine own self be true', 'john behring', 'liz maccie', 'may 9 , 2011', '1.51'], ['38', '18', 'dog eat dog', 'chris grismer', 'michael gans & richard register', 'may 16 , 2011', '1.64'], ['39', '19', 'what lies beneath', 'david paymer', 'joanna johnson', 'may 23 , 2011', '1.49']] |
2005 - 06 kansas jayhawks men 's basketball team | https://en.wikipedia.org/wiki/2005%E2%80%9306_Kansas_Jayhawks_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16503541-2.html.csv | majority | most of the players have a height that is at least six feet . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '6 -', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'height', '6 -'], 'result': True, 'ind': 0, 'tointer': 'for the height records of all rows , most of them fuzzily match to 6 - .', 'tostr': 'most_eq { all_rows ; height ; 6 - } = true'} | most_eq { all_rows ; height ; 6 - } = true | for the height records of all rows , most of them fuzzily match to 6 - . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'height_3': 3, '6 -_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'height_3': 'height', '6 -_4': '6 -'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'height_3': [0], '6 -_4': [0]} | ['name', 'position', 'height', 'weight', 'year', 'home town'] | [['jeremy case', 'guard', '6 - 1', '170', 'sophomore', 'mcalester , ok'], ['mario chalmers', 'guard', '6 - 1', '182', 'freshman', 'anchorage , ak'], ['cj giles', 'center', '6 - 10', '235', 'sophomore', 'seattle , wa'], ['jeff hawkins', 'guard', '5 - 11', '180', 'senior', 'kansas city , ks'], ['darnell jackson', 'forward', '6 - 8', '240', 'sophomore', 'oklahoma city , ok'], ['sasha kaun', 'center', '6 - 11', '246', 'sophomore', 'melbourne , fl'], ['matt kleinmann', 'center', '6 - 10', '237', 'freshman', 'overland park , ks'], ['christian moody', 'forward', '6 - 8', '220', 'senior', 'asheville , nc'], ['russell robinson', 'guard', '6 - 1', '196', 'sophomore', 'new york city , ny'], ['brandon rush', 'guard', '6 - 6', '202', 'freshman', 'kansas city , mo'], ['rodrick stewart', 'guard', '6 - 4', '201', 'sophomore', 'seattle , wa'], ['stephen vinson', 'guard', '6 - 2', '195', 'senior', 'lawrence , ks'], ['julian wright', 'forward', '6 - 8', '218', 'freshman', 'chicago heights , il']] |
2008 - 09 tampa bay lightning season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Tampa_Bay_Lightning_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17360840-5.html.csv | ordinal | in the 2008-2009 tampa bay lightning season , the first game in st. pete times forum attracted 16,104 fans . | {'scope': 'subset', 'row': '1', 'col': '1', 'order': '1', 'col_other': '5,6', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'st pete times forum'}} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'st pete times forum'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; st pete times forum }', 'tointer': 'select the rows whose location record fuzzily matches to st pete times forum .'}, 'game', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; location ; st pete times forum } ; game ; 1 }'}, 'attendance'], 'result': '16104', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; location ; st pete times forum } ; game ; 1 } ; attendance }'}, '16104'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; location ; st pete times forum } ; game ; 1 } ; attendance } ; 16104 } = true', 'tointer': 'select the rows whose location record fuzzily matches to st pete times forum . select the row whose game record of these rows is 1st minimum . the attendance record of this row is 16104 .'} | eq { hop { nth_argmin { filter_eq { all_rows ; location ; st pete times forum } ; game ; 1 } ; attendance } ; 16104 } = true | select the rows whose location record fuzzily matches to st pete times forum . select the row whose game record of these rows is 1st minimum . the attendance record of this row is 16104 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'num_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location_6': 6, 'st pete times forum_7': 7, 'game_8': 8, '1_9': 9, 'attendance_10': 10, '16104_11': 11} | {'eq_3': 'eq', 'result_4': 'true', 'num_hop_2': 'num_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location_6': 'location', 'st pete times forum_7': 'st pete times forum', 'game_8': 'game', '1_9': '1', 'attendance_10': 'attendance', '16104_11': '16104'} | {'eq_3': [4], 'result_4': [], 'num_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location_6': [0], 'st pete times forum_7': [0], 'game_8': [1], '1_9': [1], 'attendance_10': [2], '16104_11': [3]} | ['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points'] | [['10', 'november 1', 'ottawa senators', '3 - 2', 'st pete times forum', '16104', '4 - 3 - 3', '11'], ['11', 'november 5', 'new jersey devils', '3 - 4 so', 'prudential center', '11619', '4 - 3 - 4', '12'], ['12', 'november 6', 'new york rangers', '2 - 5', 'madison square garden', '18200', '4 - 4 - 4', '12'], ['13', 'november 8', 'philadelphia flyers', '2 - 1', 'wachovia center', '19412', '5 - 4 - 4', '14'], ['14', 'november 10', 'washington capitals', '2 - 4', 'verizon center', '17932', '5 - 5 - 4', '14'], ['15', 'november 12', 'florida panthers', '0 - 4', 'bankatlantic center', '12104', '5 - 6 - 4', '14'], ['16', 'november 13', 'detroit red wings', '3 - 4', 'st pete times forum', '20544', '5 - 7 - 4', '14'], ['17', 'november 16', 'carolina hurricanes', '2 - 3 so', 'rbc center', '13781', '5 - 7 - 5', '15'], ['18', 'november 18', 'florida panthers', '3 - 4 so', 'st pete times forum', '16176', '5 - 7 - 6', '16'], ['19', 'november 21', 'nashville predators', '4 - 1', 'st pete times forum', '16444', '6 - 7 - 6', '18'], ['20', 'november 23', 'new jersey devils', '3 - 7', 'st pete times forum', '14222', '6 - 8 - 6', '18'], ['21', 'november 26', 'new york rangers', '2 - 3 so', 'st pete times forum', '16991', '6 - 8 - 7', '19'], ['22', 'november 28', 'minnesota wild', '2 - 4', 'xcel energy center', '18568', '6 - 9 - 7', '19']] |
list of highest - grossing bollywood films | https://en.wikipedia.org/wiki/List_of_highest-grossing_Bollywood_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11872185-1.html.csv | aggregation | the ten highest-grossing bollywood films earned a total of 2632 crore worldwide . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '2632', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'worldwide gross'], 'result': '2632', 'ind': 0, 'tostr': 'sum { all_rows ; worldwide gross }'}, '2632'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; worldwide gross } ; 2632 } = true', 'tointer': 'the sum of the worldwide gross record of all rows is 2632 .'} | round_eq { sum { all_rows ; worldwide gross } ; 2632 } = true | the sum of the worldwide gross record of all rows is 2632 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'worldwide gross_4': 4, '2632_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'worldwide gross_4': 'worldwide gross', '2632_5': '2632'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'worldwide gross_4': [0], '2632_5': [1]} | ['rank', 'movie', 'year', 'worldwide gross', 'director', 'verdict'] | [['1', '3 idiots', '2009', '392 crore', 'rajkumar hirani', 'all time blockbuster'], ['2', 'chennai express', '2013', '314 crore', 'rohit shetty', 'blockbuster'], ['3', 'ek tha tiger', '2012', '310 crore', 'kabir khan', 'blockbuster'], ['4', 'yeh jawaani hai deewani', '2013', '301 crore', 'ayan mukerji', 'blockbuster'], ['5', 'dabangg 2', '2012', '251 crore', 'arbaaz khan', 'blockbuster'], ['6', 'bodyguard', '2011', '230 crore', 'siddique', 'blockbuster'], ['7', 'dabangg', '2010', '215 crore', 'abhinav singh kashyap', 'all time blockbuster'], ['8', 'jab tak hai jaan', '2012', '211 crore', 'yash chopra', 'super hit'], ['9', 'don 2', '2011', '206 crore', 'farhan akhtar', 'super hit'], ['10', 'raone', '2011', '202 crore', 'anubhav sinha', 'super hit']] |
csi : crime scene investigation ( season 5 ) | https://en.wikipedia.org/wiki/CSI%3A_Crime_Scene_Investigation_%28season_5%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10718631-2.html.csv | ordinal | the weeping willows episode of the crime scene investigation ( season 5 ) series has the latest original air date . | {'row': '19', 'col': '6', 'order': '1', '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', 'original air date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; original air date ; 1 }'}, 'title'], 'result': 'weeping willows', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; original air date ; 1 } ; title }'}, 'weeping willows'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; original air date ; 1 } ; title } ; weeping willows } = true', 'tointer': 'select the row whose original air date record of all rows is 1st maximum . the title record of this row is weeping willows .'} | eq { hop { nth_argmax { all_rows ; original air date ; 1 } ; title } ; weeping willows } = true | select the row whose original air date record of all rows is 1st maximum . the title record of this row is weeping willows . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '1_6': 6, 'title_7': 7, 'weeping willows_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', 'original air date_5': 'original air date', '1_6': '1', 'title_7': 'title', 'weeping willows_8': 'weeping willows'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '1_6': [0], 'title_7': [1], 'weeping willows_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['93', '1', 'viva las vegas', 'danny cannon', 'danny cannon & carol mendelsohn', 'september 23 , 2004', '30.57'], ['94', '2', 'down the drain', 'kenneth fink', 'naren shankar', 'october 7 , 2004', '28.43'], ['95', '3', 'harvest', 'david grossman', 'judith mccreary', 'october 14 , 2004', '28.89'], ['96', '4', "crow 's feet", 'richard j lewis', 'josh berman', 'october 21 , 2004', '26.54'], ['97', '5', 'swap meet', 'danny cannon', 'carol mendelsohn & david rambo & naren shankar', 'october 28 , 2004', '29.60'], ['98', '6', "what 's eating gilbert grissom", 'kenneth fink', 'sarah goldfinger', 'november 4 , 2004', '30.58'], ['99', '7', 'formalities', 'bill eagles', 'dustin lee abraham & naren shankar', 'november 11 , 2004', '29.64'], ['100', '8', 'ch - ch - changes', 'richard j lewis', 'jerry stahl', 'november 18 , 2004', '31.46'], ['102', '10', 'no humans involved', 'rob bailey', 'judith mccreary', 'december 9 , 2004', '29.83'], ['103', '11', 'who shot sherlock', 'kenneth fink', 'richard catalani & david rambo', 'january 6 , 2005', '28.86'], ['104', '12', 'snakes', 'richard j lewis', 'dustin lee abraham', 'january 13 , 2005', '27.55'], ['105', '13', 'nesting dolls', 'bill eagles', 'sarah goldfinger', 'february 3 , 2005', '24.95'], ['106', '14', 'unbearable', 'kenneth fink', 'josh berman & carol mendelsohn', 'february 10 , 2005', '27.85'], ['107', '15', 'king baby', 'richard j lewis', 'jerry stahl', 'february 17 , 2005', '30.72'], ['109', '17', 'compulsion', 'duane clark', 'josh berman & richard catalani', 'march 10 , 2005', '29.40'], ['110', '18', 'spark of life', 'kenneth fink', 'allen mcdonald', 'march 31 , 2005', '28.22'], ['112', '20', 'hollywood brass', 'bill eagles', 'sarah goldfinger & carol mendelsohn', 'april 21 , 2005', '27.02'], ['113', '21', 'committed', 'richard j lewis', 'sarah goldfinger & richard j lewis & uttam narsu', 'april 28 , 2005', '23.68'], ['114', '22', 'weeping willows', 'kenneth fink', 'areanne lloyd', 'may 5 , 2005', '26.65']] |
new england small college athletic conference | https://en.wikipedia.org/wiki/New_England_Small_College_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-261931-2.html.csv | aggregation | of schools in the new england small college athletic conference , average enrollment of those founded after 1850 was 2939 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '2939', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '1850'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'founded', '1850'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; founded ; 1850 }', 'tointer': 'select the rows whose founded record is greater than 1850 .'}, 'enrollment'], 'result': '2939', 'ind': 1, 'tostr': 'avg { filter_greater { all_rows ; founded ; 1850 } ; enrollment }'}, '2939'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_greater { all_rows ; founded ; 1850 } ; enrollment } ; 2939 } = true', 'tointer': 'select the rows whose founded record is greater than 1850 . the average of the enrollment record of these rows is 2939 .'} | round_eq { avg { filter_greater { all_rows ; founded ; 1850 } ; enrollment } ; 2939 } = true | select the rows whose founded record is greater than 1850 . the average of the enrollment record of these rows is 2939 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'founded_5': 5, '1850_6': 6, 'enrollment_7': 7, '2939_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'founded_5': 'founded', '1850_6': '1850', 'enrollment_7': 'enrollment', '2939_8': '2939'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'founded_5': [0], '1850_6': [0], 'enrollment_7': [1], '2939_8': [2]} | ['institution', 'location', 'nickname', 'founded', 'founding religious affiliation', 'enrollment', 'joined'] | [['amherst college', 'amherst , massachusetts', 'lord jeffs', '1821', 'congregationalist', '1817', '1971'], ['bates college', 'lewiston , maine', 'bobcats', '1855', 'free will baptist', '1769', '1971'], ['bowdoin college', 'brunswick , maine', 'polar bears', '1794', 'congregationalist', '1777', '1971'], ['colby college', 'waterville , maine', 'white mules', '1813', 'northern baptist', '1838', '1971'], ['connecticut college', 'new london , connecticut', 'camels', '1911', 'methodist', '1911', '1982'], ['hamilton college', 'clinton , new york', 'continentals', '1793', 'presbyterian', '1864', '1971'], ['middlebury college', 'middlebury , vermont', 'panthers', '1800', 'congregationalist', '2507', '1971'], ['trinity college', 'hartford , connecticut', 'bantams', '1823', 'episcopalian', '2344', '1971'], ['tufts university', 'medford , massachusetts', 'jumbos', '1852', 'universalist', '5138', '1971'], ['wesleyan university', 'middletown , connecticut', 'cardinals', '1831', 'methodist', '2870', '1971']] |
forces of satan records | https://en.wikipedia.org/wiki/Forces_of_Satan_Records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14728538-1.html.csv | count | two of the titles were released in the year 2008 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2008', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'release date', '2008'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose release date record fuzzily matches to 2008 .', 'tostr': 'filter_eq { all_rows ; release date ; 2008 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; release date ; 2008 } }', 'tointer': 'select the rows whose release date record fuzzily matches to 2008 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; release date ; 2008 } } ; 2 } = true', 'tointer': 'select the rows whose release date record fuzzily matches to 2008 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; release date ; 2008 } } ; 2 } = true | select the rows whose release date record fuzzily matches to 2008 . 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, 'release date_5': 5, '2008_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', 'release date_5': 'release date', '2008_6': '2008', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'release date_5': [0], '2008_6': [0], '2_7': [2]} | ['artist', 'title', 'release date', 'format', 'cat'] | [['gorgoroth', 'bergen 1996', 'november 2007', 'mcd / 7 pic disc', 'fsr001'], ['ophiolatry', 'transmutation', 'january 21 , 2008', 'full - length', 'fsr002'], ['ophiolatry', 'antievangelistical process ( re - release )', '2009', 'full - length', 'fsr003'], ['black flame', 'imperivm', 'june 23 , 2008', 'full - length', 'fsr004'], ['tangorodrim', 'unholy metal way ( re - release )', '2009', 'full - length', 'fsr005'], ['tangorodrim', 'those who unleashed ( re - release )', '2009', 'full - length', 'fsr006'], ['triumfall', 'antithesis of all flesh', 'june 15 , 2009', 'full - length', 'fsr007']] |
1949 vfl season | https://en.wikipedia.org/wiki/1949_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809351-8.html.csv | aggregation | the average crowd size of venues in the 1949 vfl season was 16667 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '16667', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '16667', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '16667'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 16667 } = true', 'tointer': 'the average of the crowd record of all rows is 16667 .'} | round_eq { avg { all_rows ; crowd } ; 16667 } = true | the average of the crowd record of all rows is 16667 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '16667_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '16667_5': '16667'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '16667_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '10.15 ( 75 )', 'richmond', '11.13 ( 79 )', 'kardinia park', '22500', '4 june 1949'], ['collingwood', '21.22 ( 148 )', 'st kilda', '4.12 ( 36 )', 'victoria park', '12000', '4 june 1949'], ['carlton', '14.13 ( 97 )', 'north melbourne', '10.7 ( 67 )', 'princes park', '29500', '4 june 1949'], ['melbourne', '10.17 ( 77 )', 'hawthorn', '10.6 ( 66 )', 'mcg', '11000', '4 june 1949'], ['south melbourne', '12.7 ( 79 )', 'fitzroy', '14.14 ( 98 )', 'lake oval', '12500', '4 june 1949'], ['footscray', '7.17 ( 59 )', 'essendon', '10.12 ( 72 )', 'western oval', '12500', '4 june 1949']] |
athletics at the 2008 summer olympics - men 's 400 metres | https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_400_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569105-7.html.csv | superlative | tyler christopher had the smallest reaction time of all athletes that competed in the the men 's 400 metres during the 2008 summer olympics . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'react'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; react }'}, 'athlete'], 'result': 'tyler christopher', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; react } ; athlete }'}, 'tyler christopher'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; react } ; athlete } ; tyler christopher } = true', 'tointer': 'select the row whose react record of all rows is minimum . the athlete record of this row is tyler christopher .'} | eq { hop { argmin { all_rows ; react } ; athlete } ; tyler christopher } = true | select the row whose react record of all rows is minimum . the athlete record of this row is tyler christopher . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'react_5': 5, 'athlete_6': 6, 'tyler christopher_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'react_5': 'react', 'athlete_6': 'athlete', 'tyler christopher_7': 'tyler christopher'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'react_5': [0], 'athlete_6': [1], 'tyler christopher_7': [2]} | ['rank', 'lane', 'athlete', 'nationality', 'time', 'react'] | [['1', '7', 'andrew steele', 'great britain', '44.94', '0.248'], ['2', '5', 'renny quow', 'trinidad and tobago', '45.13', '0.266'], ['3', '6', 'michael mathieu', 'bahamas', '45.17', '0.193'], ['4', '8', 'michael blackwood', 'jamaica', '45.56', '0.204'], ['5', '2', 'tyler christopher', 'canada', '45.67', '0.172'], ['6', '3', 'joel phillip', 'grenada', '46.30', '0.198'], ['7', '9', 'félix martinez', 'puerto rico', '46.46', '0.347'], ['8', '4', 'daniel dąbrowski', 'poland', '47.83', '0.260']] |
2005 - 06 u.s. citt \ xc3 \ xa0 di palermo season | https://en.wikipedia.org/wiki/2005%E2%80%9306_U.S._Citt%C3%A0_di_Palermo_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11361788-3.html.csv | count | anorthosis famagusta was the opponent 2 times during the 2005 - 06 u.s. città di palermo season . | {'scope': 'all', 'criterion': 'equal', 'value': 'anorthosis famagusta', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'anorthosis famagusta'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to anorthosis famagusta .', 'tostr': 'filter_eq { all_rows ; opponent ; anorthosis famagusta }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; anorthosis famagusta } }', 'tointer': 'select the rows whose opponent record fuzzily matches to anorthosis famagusta . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; anorthosis famagusta } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to anorthosis famagusta . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; anorthosis famagusta } } ; 2 } = true | select the rows whose opponent record fuzzily matches to anorthosis famagusta . 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, 'opponent_5': 5, 'anorthosis famagusta_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', 'opponent_5': 'opponent', 'anorthosis famagusta_6': 'anorthosis famagusta', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'anorthosis famagusta_6': [0], '2_7': [2]} | ['date and time', 'round', 'opponent', 'venue', 'result', 'attendance'] | [['september 15 , 2005 - 20.30', '1st round - 1st leg', 'anorthosis famagusta', 'home', 'won 2 - 1', '13047'], ['september 29 , 2005 - 17.00', '1st round - 2nd leg', 'anorthosis famagusta', 'away', 'won 4 - 0', '12000'], ['october 20 , 2005 - 17.00', 'group stage - group b', 'maccabi petah tikva', 'away', 'won 2 - 1', '2000'], ['november 3 , 2005 - 21.00', 'group stage - group b', 'lokomotiv moscow', 'home', 'drew 0 - 0', '15823'], ['november 24 , 2005 - 21.15', 'group stage - group b', 'espanyol', 'away', 'drew 1 - 1', '22000'], ['december 15 , 2005 - 20.45', 'group stage - group b', 'brøndby', 'home', 'won 3 - 0', '4521'], ['february 16 , 2006 - 20.45', 'round of 32 - 1st leg', 'slavia praha', 'away', 'lost 1 - 2', '6706'], ['february 23 , 2006 - 16.00', 'round of 32 - 2nd leg', 'slavia praha', 'home', 'won 1 - 0', '8063'], ['march 9 , 2006 - 18.00', 'round of 16 - 1st leg', 'schalke 04', 'home', 'won 1 - 0', '10581'], ['march 16 , 2006 - 20.30', 'round of 16 - 2nd leg', 'schalke 04', 'away', 'lost 0 - 3', '52151']] |
list of mountains in pakistan | https://en.wikipedia.org/wiki/List_of_mountains_in_Pakistan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1197311-1.html.csv | aggregation | an average height of pakistan mountains is 8181 m. | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '8181', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height ( m )'], 'result': '8181', 'ind': 0, 'tostr': 'avg { all_rows ; height ( m ) }'}, '8181'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height ( m ) } ; 8181 } = true', 'tointer': 'the average of the height ( m ) record of all rows is 8181 .'} | round_eq { avg { all_rows ; height ( m ) } ; 8181 } = true | the average of the height ( m ) record of all rows is 8181 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height (m)_4': 4, '8181_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height (m)_4': 'height ( m )', '8181_5': '8181'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height (m)_4': [0], '8181_5': [1]} | ['world rank', 'rank ( pakistan )', 'name', 'height ( m )', 'location'] | [['2', '1', 'k2 / godwin austen', '8611', 'karakoram'], ['9', '2', 'nanga parbat', '8126', 'himalaya'], ['11', '3', 'gasherbrum i / k5', '8080', 'baltoro karakoram'], ['12', '4', 'broad peak', '8051', 'baltoro karakoram'], ['13', '5', 'gasherbrum ii / k4', '8035', 'baltoro karakoram']] |
united states house of representatives elections , 1926 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1926 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342379-10.html.csv | majority | all of the georgia incumbents in the 1926 united states house of representatives elections were democratic . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'} | all_eq { all_rows ; party ; democratic } = true | for the party records of all rows , all of them fuzzily match to democratic . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['georgia 1', 'charles gordon edwards', 'democratic', '1924', 're - elected', 'charles gordon edwards ( d ) unopposed'], ['georgia 2', 'edward e cox', 'democratic', '1924', 're - elected', 'edward e cox ( d ) unopposed'], ['georgia 3', 'charles r crisp', 'democratic', '1912', 're - elected', 'charles r crisp ( d ) unopposed'], ['georgia 4', 'william c wright', 'democratic', '1918', 're - elected', 'william c wright ( d ) unopposed'], ['georgia 5', 'william d upshaw', 'democratic', '1918', 'lost renomination democratic hold', 'leslie jasper steele ( d ) unopposed'], ['georgia 6', 'samuel rutherford', 'democratic', '1924', 're - elected', 'samuel rutherford ( d ) unopposed'], ['georgia 7', 'gordon lee', 'democratic', '1904', 'retired democratic hold', 'malcolm c tarver ( d ) unopposed'], ['georgia 8', 'charles h brand', 'democratic', '1916', 're - elected', 'charles h brand ( d ) unopposed'], ['georgia 9', 'thomas montgomery bell', 'democratic', '1904', 're - elected', 'thomas montgomery bell ( d ) unopposed'], ['georgia 10', 'carl vinson', 'democratic', '1914', 're - elected', 'carl vinson ( d ) unopposed'], ['georgia 11', 'william c lankford', 'democratic', '1918', 're - elected', 'william c lankford ( d ) unopposed']] |
2008 - 09 real madrid c.f. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Real_Madrid_C.F._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17505751-2.html.csv | unique | garcía is the only player transferred to real madrid c.f. in the 2008 - 09 season that was from uruguay . | {'scope': 'all', 'row': '6', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'ury', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nat', 'ury'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nat record fuzzily matches to ury .', 'tostr': 'filter_eq { all_rows ; nat ; ury }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nat ; ury } }', 'tointer': 'select the rows whose nat record fuzzily matches to ury . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nat', 'ury'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nat record fuzzily matches to ury .', 'tostr': 'filter_eq { all_rows ; nat ; ury }'}, 'name'], 'result': 'garcía', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nat ; ury } ; name }'}, 'garcía'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nat ; ury } ; name } ; garcía }', 'tointer': 'the name record of this unqiue row is garcía .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nat ; ury } } ; eq { hop { filter_eq { all_rows ; nat ; ury } ; name } ; garcía } } = true', 'tointer': 'select the rows whose nat record fuzzily matches to ury . there is only one such row in the table . the name record of this unqiue row is garcía .'} | and { only { filter_eq { all_rows ; nat ; ury } } ; eq { hop { filter_eq { all_rows ; nat ; ury } ; name } ; garcía } } = true | select the rows whose nat record fuzzily matches to ury . there is only one such row in the table . the name record of this unqiue row is garcía . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nat_7': 7, 'ury_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'garcía_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nat_7': 'nat', 'ury_8': 'ury', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'garcía_10': 'garcía'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nat_7': [0], 'ury_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'garcía_10': [3]} | ['nat', 'name', 'moving from', 'type', 'transfer window', 'ends'] | [['ned', 'van der vaart', 'hamburger sv', 'transfer', 'summer', '2013'], ['esp', 'javi garcía', 'osasuna', 'transfer', 'summer', '2012'], ['esp', 'de la red', 'getafe', 'transfer', 'summer', '2011'], ['arg', 'garay', 'racingsantander', 'transfer', 'summer', '2014'], ['esp', 'gonzález', 'gimnàstic', 'loan return', 'summer', 'undisclosed'], ['ury', 'garcía', 'murcia', 'loan return', 'summer', 'undisclosed'], ['esp', 'agus', 'celta de vigo', 'loan return', 'summer', 'undisclosed'], ['esp', 'granero', 'getafe', 'loan return', 'summer', 'undisclosed'], ['ned', 'huntelaar', 'ajax', 'transfer', 'winter', '2013'], ['fra', 'lass', 'portsmouth', 'transfer', 'winter', '2013'], ['esp', 'parejo', 'queens park rangers', 'loan return', 'winter', '2017'], ['fra', 'faubert', 'west ham united', 'loan', 'winter', '2009']] |
list of auto racing tracks in the united states | https://en.wikipedia.org/wiki/List_of_auto_racing_tracks_in_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14688681-4.html.csv | count | three of the figure eight race tracks in the united states which are holland speedway , little valley speedway , and riverhead raceway are all located in new york . | {'scope': 'all', 'criterion': 'equal', 'value': 'new york', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'state', 'new york'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose state record fuzzily matches to new york .', 'tostr': 'filter_eq { all_rows ; state ; new york }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; state ; new york } }', 'tointer': 'select the rows whose state record fuzzily matches to new york . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; state ; new york } } ; 3 } = true', 'tointer': 'select the rows whose state record fuzzily matches to new york . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; state ; new york } } ; 3 } = true | select the rows whose state record fuzzily matches to new york . 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, 'state_5': 5, 'new york_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', 'state_5': 'state', 'new york_6': 'new york', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'state_5': [0], 'new york_6': [0], '3_7': [2]} | ['track', 'city', 'state', 'opened ( closing date if defunct )', 'surface', 'length'] | [['altamont motorsports park', 'tracy', 'california', '1966 - 2008', 'asphalt', 'miles ( km )'], ['evergreen speedway', 'monroe', 'washington', '1954', 'asphalt', 'miles ( km )'], ['holland speedway', 'holland', 'new york', '1960', 'concrete', 'miles ( km )'], ['indianapolis speedrome', 'indianapolis', 'indiana', '1945', 'asphalt', 'miles ( km )'], ['little valley speedway', 'little valley', 'new york', '1932 - 2011 ( figure 8 track )', 'clay', 'miles ( km )'], ['manzanita speedway', 'phoenix', 'arizona', '1951 - 2010', 'asphalt', 'miles ( km )'], ['riverhead raceway', 'riverhead', 'new york', '1951', 'asphalt', 'miles ( km )'], ['slinger speedway', 'slinger', 'wisconsin', '1974', 'asphalt', 'miles ( km )']] |
katrina adams | https://en.wikipedia.org/wiki/Katrina_Adams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18622227-5.html.csv | unique | 1989 was the only year that katrina adams made it to the 3rd round of wimbledon . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '3r', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1989', '3r'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1989 record fuzzily matches to 3r .', 'tostr': 'filter_eq { all_rows ; 1989 ; 3r }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 1989 ; 3r } }', 'tointer': 'select the rows whose 1989 record fuzzily matches to 3r . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1989', '3r'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1989 record fuzzily matches to 3r .', 'tostr': 'filter_eq { all_rows ; 1989 ; 3r }'}, 'tournament'], 'result': 'wimbledon', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 1989 ; 3r } ; tournament }'}, 'wimbledon'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 1989 ; 3r } ; tournament } ; wimbledon }', 'tointer': 'the tournament record of this unqiue row is wimbledon .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 1989 ; 3r } } ; eq { hop { filter_eq { all_rows ; 1989 ; 3r } ; tournament } ; wimbledon } } = true', 'tointer': 'select the rows whose 1989 record fuzzily matches to 3r . there is only one such row in the table . the tournament record of this unqiue row is wimbledon .'} | and { only { filter_eq { all_rows ; 1989 ; 3r } } ; eq { hop { filter_eq { all_rows ; 1989 ; 3r } ; tournament } ; wimbledon } } = true | select the rows whose 1989 record fuzzily matches to 3r . there is only one such row in the table . the tournament record of this unqiue row is wimbledon . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, '1989_7': 7, '3r_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'wimbledon_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', '1989_7': '1989', '3r_8': '3r', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'wimbledon_10': 'wimbledon'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], '1989_7': [0], '3r_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'wimbledon_10': [3]} | ['tournament', '1987', '1988', '1989', '1990', '1991', '1992', '1993', '1994', '1995', '1996', '1997'] | [['grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments'], ['australian open', 'a', '1r', '2r', '1r', 'a', '3r', 'lq', 'lq', 'lq', 'a', '1r'], ['french open', 'a', '1r', '1r', 'lq', 'lq', '1r', 'lq', 'lq', 'a', '1r', 'lq'], ['wimbledon', 'a', '4r', '3r', '1r', 'lq', '2r', 'lq', '1r', '1r', '2r', 'lq'], ['us open', 'lq', '1r', '1r', '1r', 'lq', 'a', '1r', '1r', '3r', '1r', 'lq']] |
european orienteering championships | https://en.wikipedia.org/wiki/European_Orienteering_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17760670-5.html.csv | ordinal | the european orienteering championship that took place in 2004 had the third longest distance . | {'row': '2', 'col': '5', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'notes', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; notes ; 3 }'}, 'year'], 'result': '2004', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; notes ; 3 } ; year }'}, '2004'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; notes ; 3 } ; year } ; 2004 } = true', 'tointer': 'select the row whose notes record of all rows is 3rd maximum . the year record of this row is 2004 .'} | eq { hop { nth_argmax { all_rows ; notes ; 3 } ; year } ; 2004 } = true | select the row whose notes record of all rows is 3rd maximum . the year record of this row is 2004 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'notes_5': 5, '3_6': 6, 'year_7': 7, '2004_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'notes_5': 'notes', '3_6': '3', 'year_7': 'year', '2004_8': '2004'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'notes_5': [0], '3_6': [0], 'year_7': [1], '2004_8': [2]} | ['year', 'gold', 'silver', 'bronze', 'notes'] | [['2002', 'gunilla svärd', 'brigitte wolf', 'birgitte husebye', '4.5 km , 13controls'], ['2004', 'hanne staff', 'dainora alšauskaitė', 'tatiana ryabkina', '5.3 km , 21controls'], ['2006', 'minna kauppi', 'marianne andersen', 'heli jukkola', '5.679 km , 15controls'], ['2008', 'heli jukkola', 'merja rantanen', 'minna kauppi', '5.2 km , 16controls'], ['2010', 'simone niggli - luder', 'signe soes', 'lena eliasson', '5.4 km , 22controls'], ['2012', 'simone niggli - luder', 'minna kauppi', 'tatiana ryabkina', '5.19 km , 18controls']] |
1990 - 91 yugoslav cup | https://en.wikipedia.org/wiki/1990%E2%80%9391_Yugoslav_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19294812-2.html.csv | count | two of the ties in the 1990-91 yugoslav cup had an agg of 2-1 . | {'scope': 'all', 'criterion': 'equal', 'value': '2-1', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'agg', '2-1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose agg record fuzzily matches to 2-1 .', 'tostr': 'filter_eq { all_rows ; agg ; 2-1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; agg ; 2-1 } }', 'tointer': 'select the rows whose agg record fuzzily matches to 2-1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; agg ; 2-1 } } ; 2 } = true', 'tointer': 'select the rows whose agg record fuzzily matches to 2-1 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; agg ; 2-1 } } ; 2 } = true | select the rows whose agg record fuzzily matches to 2-1 . 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, 'agg_5': 5, '2-1_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', 'agg_5': 'agg', '2-1_6': '2-1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'agg_5': [0], '2-1_6': [0], '2_7': [2]} | ['tie no', 'team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['1', 'borac banja luka', '2 - 1', 'osijek', '2 - 0', '0 - 1'], ['2', 'budućnost titograd', '2 - 1', 'partizan', '2 - 0', '0 - 1'], ['3', 'dinamo zagreb', '5 - 1', 'sarajevo', '1 - 0', '4 - 1'], ['4', 'hajduk split', '3 - 3 ( a )', 'pelister bitola', '1 - 1', '2 - 2'], ['5', 'ofk belgrade', '3 - 2', 'željezničar sarajevo', '2 - 1', '1 - 1'], ['6', 'proleter zrenjanin', '2 - 0', 'koper', '2 - 0', '0 - 0'], ['7', 'sloboda tuzla', '3 - 4', 'rijeka', '2 - 0', '1 - 4']] |
swimming at the 2000 summer olympics - women 's 200 metre freestyle | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Women%27s_200_metre_freestyle | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12383012-4.html.csv | count | for swimming at the 2000 summer olympics , in the women 's 200 metre freestyle , of those with times under 2:01 , two of the swimmers were from australia . | {'scope': 'subset', 'criterion': 'equal', 'value': 'australia', 'result': '2', 'col': '4', 'subset': {'col': '5', 'criterion': 'less_than', 'value': '2:01'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'time', '2:01'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; time ; 2:01 }', 'tointer': 'select the rows whose time record is less than 2:01 .'}, 'nationality', 'australia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose time record is less than 2:01 . among these rows , select the rows whose nationality record fuzzily matches to australia .', 'tostr': 'filter_eq { filter_less { all_rows ; time ; 2:01 } ; nationality ; australia }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_less { all_rows ; time ; 2:01 } ; nationality ; australia } }', 'tointer': 'select the rows whose time record is less than 2:01 . among these rows , select the rows whose nationality record fuzzily matches to australia . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_less { all_rows ; time ; 2:01 } ; nationality ; australia } } ; 2 } = true', 'tointer': 'select the rows whose time record is less than 2:01 . among these rows , select the rows whose nationality record fuzzily matches to australia . the number of such rows is 2 .'} | eq { count { filter_eq { filter_less { all_rows ; time ; 2:01 } ; nationality ; australia } } ; 2 } = true | select the rows whose time record is less than 2:01 . among these rows , select the rows whose nationality record fuzzily matches to australia . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'time_6': 6, '2:01_7': 7, 'nationality_8': 8, 'australia_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'time_6': 'time', '2:01_7': '2:01', 'nationality_8': 'nationality', 'australia_9': 'australia', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'time_6': [0], '2:01_7': [0], 'nationality_8': [1], 'australia_9': [1], '2_10': [3]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', "susie o'neill", 'australia', '1:59.37'], ['2', '3', 'camelia potec', 'romania', '1:59.54'], ['3', '5', 'claudia poll', 'costa rica', '1:59.63'], ['4', '2', 'nadezhda chemezova', 'russia', '1:59.69'], ['5', '6', 'franziska van almsick', 'germany', '2:00.26'], ['6', '1', 'giaan rooney', 'australia', '2:00.84'], ['7', '7', 'carla geurts', 'netherlands', '2:00.88'], ['8', '8', 'rada owen', 'united states', '2:03.34']] |
2009 - 10 3 . liga | https://en.wikipedia.org/wiki/2009%E2%80%9310_3._Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17593350-2.html.csv | majority | all of the managers of the 2009-10 3 . liga were replaced . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'not_equal', 'value': '-', 'subset': None} | {'func': 'all_not_eq', 'args': ['all_rows', 'replaced by', '-'], 'result': True, 'ind': 0, 'tointer': 'for the replaced by records of all rows , none of them is equal to - .', 'tostr': 'all_not_eq { all_rows ; replaced by ; - } = true'} | all_not_eq { all_rows ; replaced by ; - } = true | for the replaced by records of all rows , none of them is equal to - . | 1 | 1 | {'all_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'replaced by_3': 3, '-_4': 4} | {'all_not_eq_0': 'all_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'replaced by_3': 'replaced by', '-_4': '-'} | {'all_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'replaced by_3': [0], '-_4': [0]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['vfl osnabrück', 'claus - dieter wollitz', 'fc energie cottbus purchased rights', '30 june 2009', 'karsten baumann', '1 july 2009', 'pre - season'], ['fc carl zeiss jena', 'marc fascher', 'end of contract', '30 june 2009', 'rené van eck', '1 july 2009', 'pre - season'], ['fc rot - weiß erfurt', 'henri fuchs', 'end of tenure as caretaker', '30 june 2009', 'rainer hörgl', '1 july 2009', 'pre - season'], ['vfb stuttgart ii', 'rainer adrion', 'new coach of germany u - 21', '30 june 2009', 'reiner geyer', '1 july 2009', 'pre - season'], ['sv wacker burghausen', 'ralf santelli', 'end of contract', '30 june 2009', 'jürgen press', '1 july 2009', 'pre - season']] |
somerset county cricket club in 2010 | https://en.wikipedia.org/wiki/Somerset_County_Cricket_Club_in_2010 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28846752-5.html.csv | aggregation | the average wickets of the players in 2010 somerset county cricket club was 33 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '33', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'wickets'], 'result': '33', 'ind': 0, 'tostr': 'avg { all_rows ; wickets }'}, '33'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; wickets } ; 33 } = true', 'tointer': 'the average of the wickets record of all rows is 33 .'} | round_eq { avg { all_rows ; wickets } ; 33 } = true | the average of the wickets record of all rows is 33 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'wickets_4': 4, '33_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'wickets_4': 'wickets', '33_5': '33'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'wickets_4': [0], '33_5': [1]} | ['player', 'matches', 'innings', 'wickets', 'average', 'bbi', 'bbm', '5wi', '10wi'] | [['murali kartik', '11', '20', '45', '19.60', '6 / 42', '11 / 72', '5', '2'], ['ben phillips', '11', '19', '29', '22.79', '5 / 72', '5 / 72', '1', '0'], ['alfonso thomas', '15', '26', '49', '24.53', '5 / 40', '7 / 117', '2', '0'], ['damien wright', '5', '9', '14', '26.92', '5 / 41', '6 / 89', '1', '0'], ['charl willoughby', '16', '29', '58', '27.27', '6 / 101', '7 / 97', '1', '0'], ['zander de bruyn', '14', '17', '12', '32.16', '4 / 23', '4 / 23', '0', '0'], ['peter trego', '16', '25', '22', '33.13', '4 / 26', '6 / 121', '0', '0']] |
list of ngc objects ( 2001 - 3000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%282001%E2%80%933000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11097664-10.html.csv | ordinal | the ngc object in the constellation chamaeleon is the object that has the second lowest ngc number . | {'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', 'ngc number', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; ngc number ; 2 }'}, 'constellation'], 'result': 'chamaeleon', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; ngc number ; 2 } ; constellation }'}, 'chamaeleon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; ngc number ; 2 } ; constellation } ; chamaeleon } = true', 'tointer': 'select the row whose ngc number record of all rows is 2nd minimum . the constellation record of this row is chamaeleon .'} | eq { hop { nth_argmin { all_rows ; ngc number ; 2 } ; constellation } ; chamaeleon } = true | select the row whose ngc number record of all rows is 2nd minimum . the constellation record of this row is chamaeleon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'ngc number_5': 5, '2_6': 6, 'constellation_7': 7, 'chamaeleon_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', 'ngc number_5': 'ngc number', '2_6': '2', 'constellation_7': 'constellation', 'chamaeleon_8': 'chamaeleon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'ngc number_5': [0], '2_6': [0], 'constellation_7': [1], 'chamaeleon_8': [2]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )'] | [['2903', 'spiral galaxy', 'leo', '09h32 m09 .7 s', 'degree30 ′ 03 ″'], ['2915', 'irregular galaxy', 'chamaeleon', '09h26 m11 .5 s', 'degree37 ′ 35 ″'], ['2935', 'spiral galaxy', 'hydra', '09h36 m44 .6 s', 'degree07 ′ 41 ″'], ['2964', 'spiral galaxy', 'leo', '09h42 m54 .2 s', 'degree50 ′ 49 ″'], ['2968', 'irregular galaxy', 'leo', '09h43 m12 .1 s', 'degree55 ′ 42 ″'], ['2972', 'open cluster', 'vela', '09h40 m28 .5 s', 'degree20 ′ 10 ″'], ['2976', 'spiral galaxy', 'ursa major', '09h47 m15 .5 s', 'degree55 ′ 03 ″'], ['2997', 'spiral galaxy', 'antlia', '09h45 m38 .7 s', 'degree11 ′ 25 ″'], ['2998', 'spiral galaxy', 'ursa major', '09h48 m43 .6 s', 'degree04 ′ 51 ″'], ['2999', 'open cluster', 'vela', '09h40 m28 .5 s', 'degree20 ′ 10 ″'], ['3000', 'double star', 'ursa major', '09h49 m', 'degree08 ′']] |
list of glamorgan first - class cricket records | https://en.wikipedia.org/wiki/List_of_Glamorgan_first-class_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11377094-4.html.csv | aggregation | a total of 2617 runs were completed across the top ten wicket partnerships for glamorgan first-class cricket . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '2617', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'runs'], 'result': '2617', 'ind': 0, 'tostr': 'sum { all_rows ; runs }'}, '2617'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; runs } ; 2617 } = true', 'tointer': 'the sum of the runs record of all rows is 2617 .'} | round_eq { sum { all_rows ; runs } ; 2617 } = true | the sum of the runs record of all rows is 2617 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'runs_4': 4, '2617_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'runs_4': 'runs', '2617_5': '2617'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'runs_4': [0], '2617_5': [1]} | ['wicket partnership', 'runs', 'batsmen', 'opponents', 'venue', 'season'] | [['1st', '374', 'matthew elliott steve james', 'v sussex', 'colwyn bay', '2000'], ['2nd', '252', 'matthew maynard david hemp', 'v northamptonshire', 'cardiff', '2002'], ['3rd', '313', 'emrys davies willie jones', 'v essex', 'brentwood', '1948'], ['4th', '425', 'adrian dale viv richards', 'v middlesex', 'cardiff', '1993'], ['5th', '264', 'maurice robinson stan montgomery', 'v hampshire', 'bournemouth', '1949'], ['6th', '230', 'willie jones len muncer', 'v worcestershire', 'worcester', '1953'], ['7th', '211', 'tony cottey ottis gibson', 'v leicestershire', 'swansea', '1996'], ['8th', '202', 'dai davies joe hills', 'v sussex', 'eastbourne', '1928'], ['9th', '203', 'joe hills johnnie clay', 'v worcestershire', 'swansea', '1929'], ['10th', '143', 'terry davies simon daniels', 'v gloucestershire', 'swansea', '1982']] |
2009 - 10 washington capitals season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Washington_Capitals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23308178-9.html.csv | unique | the march 14th game had the highest attendance . | {'scope': 'all', 'row': '7', 'col': '6', 'col_other': '2', 'criterion': 'greater_than', 'value': '22288', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '22288'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is greater than 22288 .', 'tostr': 'filter_greater { all_rows ; attendance ; 22288 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; attendance ; 22288 } }', 'tointer': 'select the rows whose attendance record is greater than 22288 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '22288'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is greater than 22288 .', 'tostr': 'filter_greater { all_rows ; attendance ; 22288 }'}, 'date'], 'result': 'march 14', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; attendance ; 22288 } ; date }'}, 'march 14'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; attendance ; 22288 } ; date } ; march 14 }', 'tointer': 'the date record of this unqiue row is march 14 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; attendance ; 22288 } } ; eq { hop { filter_greater { all_rows ; attendance ; 22288 } ; date } ; march 14 } } = true', 'tointer': 'select the rows whose attendance record is greater than 22288 . there is only one such row in the table . the date record of this unqiue row is march 14 .'} | and { only { filter_greater { all_rows ; attendance ; 22288 } } ; eq { hop { filter_greater { all_rows ; attendance ; 22288 } ; date } ; march 14 } } = true | select the rows whose attendance record is greater than 22288 . there is only one such row in the table . the date record of this unqiue row is march 14 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'attendance_7': 7, '22288_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'march 14_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'attendance_7': 'attendance', '22288_8': '22288', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'march 14_10': 'march 14'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'attendance_7': [0], '22288_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'march 14_10': [3]} | ['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points'] | [['63', 'march 3', 'buffalo sabres', '3 - 1', 'hsbc arena', '18690', '42 - 13 - 8', '92'], ['64', 'march 4', 'tampa bay lightning', '5 - 4', 'verizon center', '18277', '43 - 13 - 8', '94'], ['65', 'march 6', 'new york rangers', '2 - 0', 'verizon center', '18277', '44 - 13 - 8', '96'], ['66', 'march 8', 'dallas stars', '4 - 3 so', 'verizon center', '18277', '44 - 13 - 9', '97'], ['67', 'march 10', 'carolina hurricanes', '4 - 3 ot', 'verizon center', '18277', '45 - 13 - 9', '99'], ['68', 'march 12', 'tampa bay lightning', '2 - 3', 'verizon center', '18277', '45 - 14 - 9', '99'], ['69', 'march 14', 'chicago blackhawks', '4 - 3 ot', 'united center', '22289', '46 - 14 - 9', '101'], ['70', 'march 16', 'florida panthers', '7 - 3', 'bankatlantic center', '15123', '47 - 14 - 9', '103'], ['71', 'march 18', 'carolina hurricanes', '3 - 4 ot', 'rbc center', '18144', '47 - 14 - 10', '104'], ['72', 'march 20', 'tampa bay lightning', '3 - 1', 'st pete times forum', '19844', '48 - 14 - 10', '106'], ['73', 'march 24', 'pittsburgh penguins', '4 - 3 so', 'verizon center', '18277', '49 - 14 - 10', '108'], ['74', 'march 25', 'carolina hurricanes', '3 - 2 so', 'rbc center', '18046', '49 - 14 - 11', '109'], ['75', 'march 28', 'calgary flames', '5 - 3', 'verizon center', '18277', '49 - 15 - 11', '109']] |
1988 open championship | https://en.wikipedia.org/wiki/1988_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18139254-4.html.csv | majority | the majority of players scored over 70 points in the 1988 open championship . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '70', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'score', '70'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them are greater than or equal to 70 .', 'tostr': 'most_greater_eq { all_rows ; score ; 70 } = true'} | most_greater_eq { all_rows ; score ; 70 } = true | for the score records of all rows , most of them are greater than or equal to 70 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '70_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '70_4': '70'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '70_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'seve ballesteros', 'spain', '67', '4'], ['t2', 'brad faxon', 'united states', '69', '2'], ['t2', 'wayne grady', 'australia', '69', '2'], ['t4', 'don pooley', 'united states', '70', '1'], ['t4', 'nick price', 'zimbabwe', '70', '1'], ['t4', 'noel ratcliffe', 'australia', '70', '1'], ['t4', 'peter senior', 'australia', '70', '1'], ['t8', 'andy bean', 'united states', '71', 'e'], ['t8', 'bob charles', 'new zealand', '71', 'e'], ['t8', 'howard clark', 'england', '71', 'e'], ['t8', 'nick faldo', 'england', '71', 'e'], ['t8', 'david frost', 'south africa', '71', 'e'], ['t8', 'jay haas', 'united states', '71', 'e'], ['t8', 'mark james', 'england', '71', 'e'], ['t8', 'gary koch', 'united states', '71', 'e'], ['t8', 'david j russell', 'england', '71', 'e'], ['t8', 'andrew sherborne', 'england', '71', 'e'], ['t8', 'bob tway', 'united states', '71', 'e']] |
grid energy storage | https://en.wikipedia.org/wiki/Grid_energy_storage | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1646838-1.html.csv | count | four types of grid energy storage technology utilize toxic materials . | {'scope': 'all', 'criterion': 'equal', 'value': 'yes', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'toxic materials', 'yes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose toxic materials record fuzzily matches to yes .', 'tostr': 'filter_eq { all_rows ; toxic materials ; yes }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; toxic materials ; yes } }', 'tointer': 'select the rows whose toxic materials record fuzzily matches to yes . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; toxic materials ; yes } } ; 4 } = true', 'tointer': 'select the rows whose toxic materials record fuzzily matches to yes . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; toxic materials ; yes } } ; 4 } = true | select the rows whose toxic materials record fuzzily matches to yes . 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, 'toxic materials_5': 5, 'yes_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', 'toxic materials_5': 'toxic materials', 'yes_6': 'yes', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'toxic materials_5': [0], 'yes_6': [0], '4_7': [2]} | ['technology', 'moving parts', 'room temperature', 'flammable', 'toxic materials', 'in production', 'rare metals'] | [['flow', 'yes', 'yes', 'no', 'yes', 'no', 'no'], ['liquid metal', 'no', 'no', 'yes', 'no', 'no', 'no'], ['sodium - ion', 'no', 'no', 'yes', 'no', 'no', 'no'], ['lead - acid', 'no', 'yes', 'no', 'yes', 'yes', 'no'], ['sodium - sulfur batteries', 'no', 'no', 'no', 'yes', 'yes', 'no'], ['ni - cd', 'no', 'yes', 'no', 'yes', 'yes', 'yes'], ['lithium - ion', 'no', 'yes', 'yes', 'no', 'yes', 'no']] |
korean tour | https://en.wikipedia.org/wiki/Korean_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11613207-1.html.csv | superlative | the ballantine 's championship tournament is worth the highest amount of points on the korean tour . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'owgr points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; owgr points }'}, 'tournament'], 'result': "ballantine 's championship", 'ind': 1, 'tostr': 'hop { argmax { all_rows ; owgr points } ; tournament }'}, "ballantine 's championship"], 'result': True, 'ind': 2, 'tostr': "eq { hop { argmax { all_rows ; owgr points } ; tournament } ; ballantine 's championship } = true", 'tointer': "select the row whose owgr points record of all rows is maximum . the tournament record of this row is ballantine 's championship ."} | eq { hop { argmax { all_rows ; owgr points } ; tournament } ; ballantine 's championship } = true | select the row whose owgr points record of all rows is maximum . the tournament record of this row is ballantine 's championship . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'owgr points_5': 5, 'tournament_6': 6, "ballantine 's championship_7": 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'owgr points_5': 'owgr points', 'tournament_6': 'tournament', "ballantine 's championship_7": "ballantine 's championship"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'owgr points_5': [0], 'tournament_6': [1], "ballantine 's championship_7": [2]} | ['dates', 'tournament', 'location', 'prize fund ( krw )', 'winner', 'owgr points'] | [['apr 25 - 28', "ballantine 's championship", 'icheon', '2205000', 'brett rumford', '34'], ['may 9 - 12', 'gs caltex maekyung open', 'seongnam', '1000000000', 'ryu hyun - woo', '8'], ['may 16 - 19', 'sk telecom open', 'seogwipo', '900000000', 'matthew griffin', '6'], ['may 23 - 26', 'happiness kwangju bank open', 'naju', '500000000', 'kang kyung - nam', '6'], ['may 30 - jun 2', 'gunsan cc open', 'gunsan', '300000000', 'lee soo - min ( a )', '6'], ['aug 1 - 4', 'bosung cc classic', 'boseong', '300000000', 'kim tae - hoon', '6'], ['aug 8 - 11', 'solaseado - pine beach open', 'haenam', '300000000', 'hong soon - sang', '6'], ['aug 15 - 18', 'kpga championship', 'chungju', '500000000', 'kim hyung - tae', '6'], ['sep 12 - 15', 'dongbu promi open', 'hoengseong', '400000000', 'lee chang - woo ( a )', '6'], ['sep 26 - 29', 'shinhan donghae open', 'incheon', '1000000000', 'bae sang - moon', '6'], ['oct 4 - 6', 'munsingwear match play championship', 'pyeongchang', '600000000', 'kim do - hoon', '6'], ['oct 10 - 13', 'cj invitational', 'yeoju', 'us 750000', 'kang sung - hoon', '14'], ['oct 17 - 20', 'kolon korea open', 'cheonan', '1000000000', 'kang sung - hoon', '14'], ['oct 29 - nov 1', 'hearld kyj tour championship', 'seogwipo', '300000000', 'hur in - hoi', '6']] |
wru division one east | https://en.wikipedia.org/wiki/WRU_Division_One_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12784856-4.html.csv | aggregation | there are 264 games played by all the teams in the wru division one east . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '264', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'played'], 'result': '264', 'ind': 0, 'tostr': 'sum { all_rows ; played }'}, '264'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; played } ; 264 } = true', 'tointer': 'the sum of the played record of all rows is 264 .'} | round_eq { sum { all_rows ; played } ; 264 } = true | the sum of the played record of all rows is 264 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'played_4': 4, '264_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'played_4': 'played', '264_5': '264'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'played_4': [0], '264_5': [1]} | ['club', 'played', 'drawn', 'lost', 'try bp', 'losing bp'] | [['club', 'played', 'drawn', 'lost', 'try bp', 'losing bp'], ['blackwood rfc', '22', '0', '1', '14', '0'], ['newbridge rfc', '22', '2', '4', '11', '1'], ['llanharan rfc', '22', '1', '7', '7', '1'], ['uwic rfc', '22', '1', '9', '9', '3'], ['bargoed rfc', '22', '1', '9', '9', '2'], ['caerphilly rfc', '22', '3', '8', '6', '4'], ['merthyr rfc', '22', '1', '9', '6', '2'], ['ystrad rhondda rfc', '22', '1', '12', '6', '4'], ['rumney rfc', '22', '0', '14', '3', '3'], ['beddau rfc', '22', '0', '16', '3', '1'], ['penallta rfc', '22', '0', '19', '2', '8'], ['newport saracens rfc', '22', '0', '19', '2', '5']] |
2009 supersport world championship season | https://en.wikipedia.org/wiki/2009_Supersport_World_Championship_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21191496-1.html.csv | unique | in the 2009 supersport world championship season , when cal crutchlow had the pole position , the only race in spain was on april 5th . | {'scope': 'subset', 'row': '3', 'col': '2', 'col_other': '4', 'criterion': 'equal', 'value': 'spain', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'cal crutchlow'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pole position', 'cal crutchlow'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; pole position ; cal crutchlow }', 'tointer': 'select the rows whose pole position record fuzzily matches to cal crutchlow .'}, 'country', 'spain'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose pole position record fuzzily matches to cal crutchlow . among these rows , select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain } }', 'tointer': 'select the rows whose pole position record fuzzily matches to cal crutchlow . among these rows , select the rows whose country record fuzzily matches to spain . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pole position', 'cal crutchlow'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; pole position ; cal crutchlow }', 'tointer': 'select the rows whose pole position record fuzzily matches to cal crutchlow .'}, 'country', 'spain'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose pole position record fuzzily matches to cal crutchlow . among these rows , select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain }'}, 'date'], 'result': '5 april', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain } ; date }'}, '5 april'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain } ; date } ; 5 april }', 'tointer': 'the date record of this unqiue row is 5 april .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain } } ; eq { hop { filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain } ; date } ; 5 april } } = true', 'tointer': 'select the rows whose pole position record fuzzily matches to cal crutchlow . among these rows , select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the date record of this unqiue row is 5 april .'} | and { only { filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain } } ; eq { hop { filter_eq { filter_eq { all_rows ; pole position ; cal crutchlow } ; country ; spain } ; date } ; 5 april } } = true | select the rows whose pole position record fuzzily matches to cal crutchlow . among these rows , select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the date record of this unqiue row is 5 april . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'pole position_8': 8, 'cal crutchlow_9': 9, 'country_10': 10, 'spain_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'date_12': 12, '5 april_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'pole position_8': 'pole position', 'cal crutchlow_9': 'cal crutchlow', 'country_10': 'country', 'spain_11': 'spain', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'date_12': 'date', '5 april_13': '5 april'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'pole position_8': [0], 'cal crutchlow_9': [0], 'country_10': [1], 'spain_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'date_12': [3], '5 april_13': [4]} | ['round', 'country', 'circuit', 'date', 'pole position', 'fastest lap', 'winning rider', 'winning team', 'report'] | [['1', 'australia', 'phillip island grand prix circuit', '1 march', 'kenan sofuoğlu', 'andrew pitt', 'kenan sofuoğlu', 'ten kate honda', 'report'], ['2', 'qatar', 'losail international circuit', '14 march', 'cal crutchlow', 'andrew pitt', 'eugene laverty', 'parkalgar honda', 'report'], ['3', 'spain', 'circuit ricardo tormo', '5 april', 'cal crutchlow', 'cal crutchlow', 'cal crutchlow', 'yamaha world supersport', 'report'], ['4', 'netherlands', 'tt circuit assen', '26 april', 'cal crutchlow', 'cal crutchlow', 'eugene laverty', 'parkalgar honda', 'report'], ['5', 'italy', 'autodromo nazionale monza', '10 may', 'cal crutchlow', 'cal crutchlow', 'cal crutchlow', 'yamaha world supersport', 'report'], ['6', 'south africa', 'kyalami', '17 may', 'cal crutchlow', 'eugene laverty', 'eugene laverty', 'parkalgar honda', 'report'], ['7', 'united states', 'miller motorsports park', '31 may', 'joan lascorz', 'kenan sofuoğlu', 'kenan sofuoğlu', 'ten kate honda', 'report'], ['8', 'san marino', 'misano world circuit', '21 june', 'michele pirro', 'cal crutchlow', 'cal crutchlow', 'yamaha world supersport', 'report'], ['9', 'great britain', 'donington park', '28 june', 'cal crutchlow', 'cal crutchlow', 'cal crutchlow', 'yamaha world supersport', 'report'], ['10', 'czech republic', 'masaryk circuit', '26 july', 'cal crutchlow', 'cal crutchlow', 'fabien foret', 'yamaha world supersport', 'report'], ['11', 'germany', 'nürburgring', '6 september', 'cal crutchlow', 'cal crutchlow', 'cal crutchlow', 'yamaha world supersport', 'report'], ['12', 'italy', 'autodromo enzo e dino ferrari', '27 september', 'cal crutchlow', 'cal crutchlow', 'kenan sofuoğlu', 'ten kate honda', 'report'], ['13', 'france', 'circuit de nevers magny - cours', '4 october', 'cal crutchlow', 'cal crutchlow', 'joan lascorz', 'provec kawasaki', 'report']] |
1998 australian super touring championship | https://en.wikipedia.org/wiki/1998_Australian_Super_Touring_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15394512-2.html.csv | superlative | in the 1998 australian super touring championship , the race won by brad jones on the earliest day of the year was held on 26-27 apr . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '6', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'brad jones'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'brad jones'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winner ; brad jones }', 'tointer': 'select the rows whose winner record fuzzily matches to brad jones .'}, 'date'], 'result': '26 - 27 apr', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; winner ; brad jones } ; date }', 'tointer': 'select the rows whose winner record fuzzily matches to brad jones . the minimum date record of these rows is 26 - 27 apr .'}, '26 - 27 apr'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; winner ; brad jones } ; date } ; 26 - 27 apr } = true', 'tointer': 'select the rows whose winner record fuzzily matches to brad jones . the minimum date record of these rows is 26 - 27 apr .'} | eq { min { filter_eq { all_rows ; winner ; brad jones } ; date } ; 26 - 27 apr } = true | select the rows whose winner record fuzzily matches to brad jones . the minimum date record of these rows is 26 - 27 apr . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'winner_5': 5, 'brad jones_6': 6, 'date_7': 7, '26 - 27 apr_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'winner_5': 'winner', 'brad jones_6': 'brad jones', 'date_7': 'date', '26 - 27 apr_8': '26 - 27 apr'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winner_5': [0], 'brad jones_6': [0], 'date_7': [1], '26 - 27 apr_8': [2]} | ['rd / race', 'race title', 'circuit', 'city / state', 'date', 'winner', 'team'] | [['1 / 1', 'calder', 'calder park raceway', 'melbourne , victoria', '4 - 5 apr', 'cameron mcconville', 'brad jones racing'], ['1 / 2', 'calder', 'calder park raceway', 'melbourne , victoria', '4 - 5 apr', 'cameron mcconville', 'brad jones racing'], ['2 / 1', 'oran park', 'oran park raceway', 'sydney , new south wales', '26 - 27 apr', 'brad jones', 'brad jones racing'], ['2 / 2', 'oran park', 'oran park raceway', 'sydney , new south wales', '26 - 27 apr', 'brad jones', 'brad jones racing'], ['3 / 1', 'phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '16 - 17 may', 'cameron mcconville', 'brad jones racing'], ['3 / 2', 'phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '16 - 17 may', 'jim richards', 'volvo racing'], ['4 / 1', 'eastern creek', 'eastern creek raceway', 'sydney , new south wales', '6 - 7 jun', 'jim richards', 'volvo racing'], ['4 / 2', 'eastern creek', 'eastern creek raceway', 'sydney , new south wales', '6 - 7 jun', 'brad jones', 'brad jones racing'], ['5 / 1', 'lakeside', 'lakeside international raceway', 'brisbane , queensland', '27 - 28 jun', 'brad jones', 'brad jones racing'], ['5 / 2', 'lakeside', 'lakeside international raceway', 'brisbane , queensland', '27 - 28 jun', 'brad jones', 'brad jones racing'], ['6 / 1', 'mallala', 'mallala motorsport park', 'adelaide , south australia', '18 - 19 jul', 'brad jones', 'brad jones racing'], ['6 / 2', 'mallala', 'mallala motorsport park', 'adelaide , south australia', '18 - 19 jul', 'cameron mcconville', 'brad jones racing'], ['7 / 1', 'winton', 'winton motor raceway', 'benalla , victoria', '8 - 9 aug', 'cameron mcconville', 'brad jones racing'], ['7 / 2', 'winton', 'winton motor raceway', 'benalla , victoria', '8 - 9 aug', 'cameron mcconville', 'brad jones racing'], ['8 / 1', 'oran park', 'oran park raceway', 'sydney , new south wales', '29 - 30 aug', 'cameron mcconville', 'brad jones racing'], ['8 / 2', 'oran park', 'oran park raceway', 'sydney , new south wales', '29 - 30 aug', 'brad jones', 'brad jones racing']] |
2009 copa sudamericana first stage | https://en.wikipedia.org/wiki/2009_Copa_Sudamericana_first_stage | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23812628-1.html.csv | unique | the only team to score 1 - 1 in the 2nd leg of the 2009 copa sudamericana first stage after score 1 - 1 in the 1st leg was atlético mineiro . | {'scope': 'subset', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '1 - 1', 'subset': {'col': '4', 'criterion': 'equal', 'value': '1 - 1'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st leg', '1 - 1'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; 1st leg ; 1 - 1 }', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 .'}, '2nd leg', '1 - 1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 . among these rows , select the rows whose 2nd leg record fuzzily matches to 1 - 1 .', 'tostr': 'filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 } }', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 . among these rows , select the rows whose 2nd leg record fuzzily matches to 1 - 1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st leg', '1 - 1'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; 1st leg ; 1 - 1 }', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 .'}, '2nd leg', '1 - 1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 . among these rows , select the rows whose 2nd leg record fuzzily matches to 1 - 1 .', 'tostr': 'filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 }'}, 'team 1'], 'result': 'atlético mineiro', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 } ; team 1 }'}, 'atlético mineiro'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 } ; team 1 } ; atlético mineiro }', 'tointer': 'the team 1 record of this unqiue row is atlético mineiro .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 } } ; eq { hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 } ; team 1 } ; atlético mineiro } } = true', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 . among these rows , select the rows whose 2nd leg record fuzzily matches to 1 - 1 . there is only one such row in the table . the team 1 record of this unqiue row is atlético mineiro .'} | and { only { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 } } ; eq { hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 1 } ; 2nd leg ; 1 - 1 } ; team 1 } ; atlético mineiro } } = true | select the rows whose 1st leg record fuzzily matches to 1 - 1 . among these rows , select the rows whose 2nd leg record fuzzily matches to 1 - 1 . there is only one such row in the table . the team 1 record of this unqiue row is atlético mineiro . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, '1st leg_8': 8, '1 - 1_9': 9, '2nd leg_10': 10, '1 - 1_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'team 1_12': 12, 'atlético mineiro_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', '1st leg_8': '1st leg', '1 - 1_9': '1 - 1', '2nd leg_10': '2nd leg', '1 - 1_11': '1 - 1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'team 1_12': 'team 1', 'atlético mineiro_13': 'atlético mineiro'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], '1st leg_8': [0], '1 - 1_9': [0], '2nd leg_10': [1], '1 - 1_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'team 1_12': [3], 'atlético mineiro_13': [4]} | ['team 1', 'points', 'team 2', '1st leg', '2nd leg'] | [['atlético mineiro', '2 - 2 ( 5 - 6 pk )', 'goiás', '1 - 1', '1 - 1'], ['la equidad', '1 - 4', 'unión española', '2 - 2', '0 - 1'], ['vitória', '3 - 3 ( 5 - 3 pk )', 'coritiba', '2 - 0', '0 - 2'], ['universidad de chile', '6 - 0', 'deportivo cali', '2 - 1', '1 - 0'], ['fluminense', '( a ) 2 - 2', 'flamengo', '0 - 0', '1 - 1'], ['liverpool', '1 - 4', 'cienciano', '0 - 0', '0 - 2'], ['river plate', '0 - 6', 'lanús', '1 - 2', '0 - 1'], ['zamora', '0 - 6', 'emelec', '0 - 1', '1 - 2'], ['atlético paranaense', '1 - 4', 'botafogo', '0 - 0', '2 - 3'], ['ldu quito', '4 - 1', 'libertad', '1 - 0', '1 - 1'], ['tigre', '3 - 3 ( a )', 'san lorenzo', '2 - 1', '0 - 1'], ['alianza atlético', '4 - 1', 'deportivo anzoátegui', '0 - 0', '2 - 1'], ['blooming', '0 - 6', 'river plate', '0 - 3', '1 - 2'], ['boca juniors', '1 - 4', 'vélez sársfield', '1 - 1', '0 - 1']] |
spain in the eurovision song contest 2009 | https://en.wikipedia.org/wiki/Spain_in_the_Eurovision_Song_Contest_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19763199-4.html.csv | ordinal | virginia received the second highest number of votes for spain in the 2008 eurovision song contest . | {'row': '5', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total votes', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total votes ; 2 }'}, 'artist'], 'result': 'virginia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total votes ; 2 } ; artist }'}, 'virginia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total votes ; 2 } ; artist } ; virginia } = true', 'tointer': 'select the row whose total votes record of all rows is 2nd maximum . the artist record of this row is virginia .'} | eq { hop { nth_argmax { all_rows ; total votes ; 2 } ; artist } ; virginia } = true | select the row whose total votes record of all rows is 2nd maximum . the artist record of this row is virginia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total votes_5': 5, '2_6': 6, 'artist_7': 7, 'virginia_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', 'total votes_5': 'total votes', '2_6': '2', 'artist_7': 'artist', 'virginia_8': 'virginia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total votes_5': [0], '2_6': [0], 'artist_7': [1], 'virginia_8': [2]} | ['draw', 'artist', 'song', 'jury votes', 'televotes', 'total votes', 'result'] | [['1', 'diqesi', 'subiré', '5', '4', '9', 'out'], ['2', 'roel', 'y ahora dices', '6', '3', '9', 'out'], ['3', 'salva ortega', 'lujuria', '7', '7', '14', 'second chance > final'], ['4', 'soraya', 'la noche es para mí', '12', '12', '24', 'final'], ['5', 'virginia', 'true love', '10', '10', '20', 'final'], ['6', 'calipop', 'burbuja', '2', '2', '4', 'out'], ['7', 'ángeles vela', 'vístete de primavera', '4', '5', '9', 'out'], ['8', 'jorge gonzález', 'si yo vengo a enamorarte', '8', '8', '16', 'final'], ['9', 'electronikboy', 'mon petit oiseau', '1', '1', '2', 'out']] |
snowy mountains scheme | https://en.wikipedia.org/wiki/Snowy_Mountains_Scheme | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-177948-2.html.csv | comparative | in the dams of the snowy mountains scheme listed , the tooma dam was completed before the talbingo dam . | {'row_1': '14', 'row_2': '12', 'col': '2', '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', 'dam constructed', 'tooma dam'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose dam constructed record fuzzily matches to tooma dam .', 'tostr': 'filter_eq { all_rows ; dam constructed ; tooma dam }'}, 'year completed'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; dam constructed ; tooma dam } ; year completed }', 'tointer': 'select the rows whose dam constructed record fuzzily matches to tooma dam . take the year completed record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'dam constructed', 'talbingo dam'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose dam constructed record fuzzily matches to talbingo dam .', 'tostr': 'filter_eq { all_rows ; dam constructed ; talbingo dam }'}, 'year completed'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; dam constructed ; talbingo dam } ; year completed }', 'tointer': 'select the rows whose dam constructed record fuzzily matches to talbingo dam . take the year completed record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; dam constructed ; tooma dam } ; year completed } ; hop { filter_eq { all_rows ; dam constructed ; talbingo dam } ; year completed } } = true', 'tointer': 'select the rows whose dam constructed record fuzzily matches to tooma dam . take the year completed record of this row . select the rows whose dam constructed record fuzzily matches to talbingo dam . take the year completed record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; dam constructed ; tooma dam } ; year completed } ; hop { filter_eq { all_rows ; dam constructed ; talbingo dam } ; year completed } } = true | select the rows whose dam constructed record fuzzily matches to tooma dam . take the year completed record of this row . select the rows whose dam constructed record fuzzily matches to talbingo dam . take the year completed 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, 'dam constructed_7': 7, 'tooma dam_8': 8, 'year completed_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'dam constructed_11': 11, 'talbingo dam_12': 12, 'year completed_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', 'dam constructed_7': 'dam constructed', 'tooma dam_8': 'tooma dam', 'year completed_9': 'year completed', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'dam constructed_11': 'dam constructed', 'talbingo dam_12': 'talbingo dam', 'year completed_13': 'year completed'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'dam constructed_7': [0], 'tooma dam_8': [0], 'year completed_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'dam constructed_11': [1], 'talbingo dam_12': [1], 'year completed_13': [3]} | ['dam constructed', 'year completed', 'impounded body of water', 'reservoir capacity', 'dam wall height', 'dam type'] | [['blowering dam', '1968', 'blowering reservoir', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['deep creek dam', '1961', 'deep creek reservoir', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['eucumbene dam', '1958', 'lake eucumbene', 'ml ( 10 6cuft )', '-', 'earthfill embankment'], ['geehi dam', '1966', 'geehi reservoir', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['guthega dam', '1955', 'guthega reservoir', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['happy jacks dam', '1959', 'happy jacks pondage', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['island bend dam', '1965', 'island bend pondage', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['jindabyne dam', '1967', 'lake jindabyne', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['jounama dam', '1968', 'jounama pondage', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['khancoban dam', '1966', 'khancoban reservoir', 'ml ( 10 6cuft )', '-', 'earthfill embankment'], ['murray two dam', '1968', 'murray two pondage', 'ml ( 10 6cuft )', '-', 'concrete arch'], ['talbingo dam', '1970', 'talbingo reservoir', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['tantangara dam', '1960', 'tantangara reservoir', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['tooma dam', '1961', 'tooma reservoir', 'ml ( 10 6cuft )', '-', 'concrete embankment'], ['tumut pond dam', '1959', 'tumut pond reservoir', 'ml ( 10 6cuft )', '-', 'concrete arch'], ['tumut two dam', '1961', 'tumut two pondage', 'ml ( 10 6cuft )', '-', 'concrete gravity']] |
katie o'brien | https://en.wikipedia.org/wiki/Katie_O%27Brien | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11961200-6.html.csv | majority | katie o'brien played most of her matches in 25000 tournaments . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '25000', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'tournament', '25000'], 'result': True, 'ind': 0, 'tointer': 'for the tournament records of all rows , most of them fuzzily match to 25000 .', 'tostr': 'most_eq { all_rows ; tournament ; 25000 } = true'} | most_eq { all_rows ; tournament ; 25000 } = true | for the tournament records of all rows , most of them fuzzily match to 25000 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tournament_3': 3, '25000_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tournament_3': 'tournament', '25000_4': '25000'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tournament_3': [0], '25000_4': [0]} | ['outcome', 'tournament', 'surface', 'partnering', 'score in the final'] | [['runner - up', '10000 tipton , great britain', 'hard ( i )', 'melanie south', '4 - 6 , 2 - 6'], ['runner - up', '10000 hull , great britain', 'hard ( i )', 'melanie south', '6 - 4 , 3 - 6 , 5 - 7'], ['runner - up', '25000 jersey , great britain', 'hard ( i )', 'melanie south', '3 - 6 , 1 - 6'], ['winner', '25000 madrid , spain', 'hard', 'sorana cîrstea', '6 - 4 , 6 - 4'], ['runner - up', '25000 nottingham , great britain', 'hard', 'margit rüütel', '2 - 6 , 6 - 2 , 6 - 7 ( 1 - 7 )'], ['winner', '25000 jersey , great britain', 'hard ( i )', 'margit rüütel', '7 - 5 , 6 - 4'], ['runner - up', '25000 glasgow , great britain', 'hard ( i )', 'margit rüütel', '4 - 6 , 3 - 6'], ['runner - up', '25000 istanbul , turkey', 'hard ( i )', 'sorana cîrstea', 'w / o'], ['runner - up', '25000 jersey , great britain', 'hard ( i )', 'georgie stoop', '0 - 6 , 4 - 6'], ['runner - up', '25000 sutton , great britain', 'hard ( i )', 'rebecca marino', '3 - 6 , 3 - 6'], ['runner - up', '50000 nottingham , great britain', 'grass', 'naomi broady', '3 - 6 , 6 - 2 ,']] |
1973 nhl amateur draft | https://en.wikipedia.org/wiki/1973_NHL_Amateur_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1965650-4.html.csv | unique | only one player from the united kingdom was selected in picks 49-64 of the 1973 nhl amateur draft . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'united kingdom', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united kingdom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to united kingdom .', 'tostr': 'filter_eq { all_rows ; nationality ; united kingdom }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; united kingdom } }', 'tointer': 'select the rows whose nationality record fuzzily matches to united kingdom . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united kingdom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to united kingdom .', 'tostr': 'filter_eq { all_rows ; nationality ; united kingdom }'}, 'pick'], 'result': '51', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; united kingdom } ; pick }'}, '51'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; united kingdom } ; pick } ; 51 }', 'tointer': 'the pick record of this unqiue row is 51 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; united kingdom } } ; eq { hop { filter_eq { all_rows ; nationality ; united kingdom } ; pick } ; 51 } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to united kingdom . there is only one such row in the table . the pick record of this unqiue row is 51 .'} | and { only { filter_eq { all_rows ; nationality ; united kingdom } } ; eq { hop { filter_eq { all_rows ; nationality ; united kingdom } ; pick } ; 51 } } = true | select the rows whose nationality record fuzzily matches to united kingdom . there is only one such row in the table . the pick record of this unqiue row is 51 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'united kingdom_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'pick_9': 9, '51_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'united kingdom_8': 'united kingdom', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'pick_9': 'pick', '51_10': '51'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'united kingdom_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'pick_9': [2], '51_10': [3]} | ['pick', 'player', 'position', 'nationality', 'nhl team', 'college / junior / club team'] | [['49', 'andre st laurent', 'centre', 'canada', 'new york islanders', 'montreal junior canadiens ( qmjhl )'], ['50', 'ron serafini', 'defence', 'united states', 'california golden seals', 'st catharines black hawks ( oha )'], ['51', 'keith mackie', 'defence', 'united kingdom canada', 'vancouver canucks', 'edmonton oil kings ( wchl )'], ['52', 'frank rochon', 'left wing', 'canada', 'toronto maple leafs', 'sherbrooke castors ( qmjhl )'], ['53', 'dean talafous', 'centre', 'united states', 'atlanta flames', 'university of wisconsin ( ncaa )'], ['54', 'jim mccrimmon', 'defence', 'canada', 'los angeles kings', 'medicine hat tigers ( wchl )'], ['55', 'dennis owchar', 'defence', 'canada', 'pittsburgh penguins', 'toronto marlboros ( oha )'], ['56', 'alan hangsleben', 'defence', 'united states', 'montreal canadiens', 'university of north dakota ( ncaa )'], ['57', 'tom colley', 'centre', 'canada', 'minnesota north stars', 'sudbury wolves ( oha )'], ['58', 'dale cook', 'left wing', 'canada', 'philadelphia flyers', 'victoria cougars ( wchl )'], ['59', 'mike korney', 'defence', 'canada', 'detroit red wings', 'winnipeg jets ( wchl )'], ['60', 'yvon dupuis', 'right wing', 'canada', 'buffalo sabres', 'quebec remparts ( qmjhl )'], ['61', 'dave elliott', 'left wing', 'canada', 'chicago black hawks', 'winnipeg jets ( wchl )'], ['62', 'brian molvik', 'defence', 'canada', 'new york rangers', 'calgary centennials ( wchl )'], ['63', 'steve langdon', 'left wing', 'canada', 'boston bruins', 'london knights ( oha )'], ['64', 'richard latulippe', 'centre', 'canada', 'montreal canadiens', 'quebec remparts ( qmjhl )']] |
list of schools in the waikato region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Waikato_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12146269-10.html.csv | aggregation | the average school in the waikato region has a roll of 99.61 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '99.61', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'roll'], 'result': '99.61', 'ind': 0, 'tostr': 'avg { all_rows ; roll }'}, '99.61'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; roll } ; 99.61 } = true', 'tointer': 'the average of the roll record of all rows is 99.61 .'} | round_eq { avg { all_rows ; roll } ; 99.61 } = true | the average of the roll record of all rows is 99.61 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'roll_4': 4, '99.61_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'roll_4': 'roll', '99.61_5': '99.61'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'roll_4': [0], '99.61_5': [1]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['aria school', '1 - 6', 'coed', 'aria', 'state', '5', '55'], ['benneydale school', '1 - 8', 'coed', 'benneydale', 'state', '1', '14'], ['centennial park school', '1 - 8', 'coed', 'te kuiti', 'state', '1', '113'], ['kinohaku school', '1 - 8', 'coed', 'te kuiti', 'state', '4', '32'], ['mapiu school', '1 - 8', 'coed', 'mapiu', 'state', '4', '9'], ['mokau school', '1 - 8', 'coed', 'mokau', 'state', '3', '24'], ['piopio college', '7 - 15', 'coed', 'piopio', 'state', '4', '202'], ['piopio primary school', '1 - 6', 'coed', 'piopio', 'state', '5', '129'], ['piri piri school', '1 - 8', 'coed', 'te kuiti', 'state', '4', '22'], ['pukenui school', '1 - 8', 'coed', 'te kuiti', 'state', '2', '186'], ['rangitoto school', '1 - 8', 'coed', 'rangitoto', 'state', '6', '40'], ["st joseph 's catholic school", '1 - 8', 'coed', 'te kuiti', 'state integrated', '4', '102'], ['te kuiti high school', '9 - 15', 'coed', 'te kuiti', 'state', '3', '321'], ['te kuiti primary school', '1 - 8', 'coed', 'te kuiti', 'state', '2', '356'], ['te kura o tahaaroa', '1 - 8', 'coed', 'te kuiti', 'state', '3', '38'], ['te wharekura o maniapoto', '1 - 15', 'coed', 'te kuiti', 'state', '2', '96'], ['waitomo caves school', '1 - 8', 'coed', 'waitomo caves', 'state', '5', '44'], ['whareorino school', '1 - 8', 'coed', 'mokau', 'state', '5', '10']] |
2001 - 02 boston celtics season | https://en.wikipedia.org/wiki/2001%E2%80%9302_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17622423-8.html.csv | superlative | in the 2001 - 02 boston celtics season , the earliest game to be played at the fleet center was on friday march 1 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'fleetcenter'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'fleetcenter'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; fleetcenter }', 'tointer': 'select the rows whose location record fuzzily matches to fleetcenter .'}, 'date'], 'result': 'fri mar 1', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; location ; fleetcenter } ; date }', 'tointer': 'select the rows whose location record fuzzily matches to fleetcenter . the minimum date record of these rows is fri mar 1 .'}, 'fri mar 1'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; location ; fleetcenter } ; date } ; fri mar 1 } = true', 'tointer': 'select the rows whose location record fuzzily matches to fleetcenter . the minimum date record of these rows is fri mar 1 .'} | eq { min { filter_eq { all_rows ; location ; fleetcenter } ; date } ; fri mar 1 } = true | select the rows whose location record fuzzily matches to fleetcenter . the minimum date record of these rows is fri mar 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'fleetcenter_6': 6, 'date_7': 7, 'fri mar 1_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'fleetcenter_6': 'fleetcenter', 'date_7': 'date', 'fri mar 1_8': 'fri mar 1'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'fleetcenter_6': [0], 'date_7': [1], 'fri mar 1_8': [2]} | ['game', 'date', 'opponent', 'score', 'location', 'record'] | [['58', 'fri mar 1', 'charlotte hornets', '87 - 100', 'fleetcenter', '31 - 27'], ['59', 'mon mar 4', 'philadelphia 76ers', '100 - 94', 'first union center', '32 - 27'], ['60', 'wed mar 6', 'orlando magic', '130 - 110', 'fleetcenter', '33 - 27'], ['61', 'fri mar 8', 'detroit pistons', '117 - 92', 'fleetcenter', '34 - 27'], ['62', 'sun mar 10', 'washington wizards', '98 - 91', 'fleetcenter', '35 - 27'], ['63', 'mon mar 11', 'washington wizards', '104 - 99', 'mci center', '36 - 27'], ['64', 'wed mar 13', 'new jersey nets', '97 - 89', 'fleetcenter', '37 - 27'], ['65', 'fri mar 15', 'memphis grizzlies', '103 - 97', 'the pyramid', '38 - 27'], ['66', 'sat mar 16', 'san antonio spurs', '104 - 111', 'alamodome', '38 - 28'], ['67', 'mon mar 18', 'portland trail blazers', '91 - 100', 'fleetcenter', '38 - 29'], ['68', 'wed mar 20', 'cleveland cavaliers', '96 - 70', 'fleetcenter', '39 - 29'], ['69', 'fri mar 22', 'philadelphia 76ers', '91 - 96', 'fleetcenter', '39 - 30'], ['70', 'sun mar 24', 'detroit pistons', '101 - 109', 'the palace of auburn hills', '39 - 31'], ['71', 'mon mar 25', 'miami heat', '87 - 82', 'american airlines arena', '40 - 31'], ['72', 'wed mar 27', 'golden state warriors', '102 - 99', 'fleetcenter', '41 - 31'], ['73', 'fri mar 29', 'dallas mavericks', '82 - 108', 'fleetcenter', '41 - 32'], ['74', 'sun mar 31', 'milwaukee bucks', '110 - 80', 'fleetcenter', '42 - 32']] |
united states house of representatives elections , 1974 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1974 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341690-18.html.csv | count | all incumbents are member of the democratic party . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; party ; democratic } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; democratic } } ; 5 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; party ; democratic } } ; 5 } = true | select the rows whose party record fuzzily matches to democratic . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'democratic_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'democratic_6': 'democratic', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '5_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', 'f edward hebert', 'democratic', '1940', 're - elected', 'f edward hebert ( d ) unopposed'], ['louisiana 4', 'joe waggonner', 'democratic', '1961', 're - elected', 'joe waggonner ( d ) unopposed'], ['louisiana 5', 'otto passman', 'democratic', '1946', 're - elected', 'otto passman ( d ) unopposed'], ['louisiana 6', 'john rarick', 'democratic', '1966', 'lost renomination republican gain', 'henson moore ( r ) 54.1 % jeff la caze ( d ) 45.9 %'], ['louisiana 7', 'john breaux', 'democratic', '1972', 're - elected', 'john breaux ( d ) 89.3 % jeremy j millett ( i ) 10.7 %']] |
lewis black 's root of all evil | https://en.wikipedia.org/wiki/Lewis_Black%27s_Root_of_All_Evil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15781170-1.html.csv | superlative | in lewis black 's root of all evil , andrew daly is the advocate with the great number of poll losses . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'poll losses'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; poll losses }'}, 'advocate'], 'result': 'andrew daly', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; poll losses } ; advocate }'}, 'andrew daly'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; poll losses } ; advocate } ; andrew daly } = true', 'tointer': 'select the row whose poll losses record of all rows is maximum . the advocate record of this row is andrew daly .'} | eq { hop { argmax { all_rows ; poll losses } ; advocate } ; andrew daly } = true | select the row whose poll losses record of all rows is maximum . the advocate record of this row is andrew daly . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'poll losses_5': 5, 'advocate_6': 6, 'andrew daly_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'poll losses_5': 'poll losses', 'advocate_6': 'advocate', 'andrew daly_7': 'andrew daly'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'poll losses_5': [0], 'advocate_6': [1], 'andrew daly_7': [2]} | ['advocate', 'wins', 'losses', 'ties', 'poll wins', 'poll losses'] | [['andrew daly', '4', '2', '0', '2', '4'], ['andy kindler', '3', '1', '0', '1', '3'], ['patton oswalt', '3', '2', '1', '3', '3'], ['kathleen madigan', '2', '1', '0', '1', '2'], ['greg giraldo', '2', '7', '0', '6', '3'], ['paul f tompkins', '1', '4', '1', '3', '3'], ['jerry minor', '1', '0', '0', '1', '0'], ['andrea savage', '1', '0', '0', '1', '0']] |
1998 cfl draft | https://en.wikipedia.org/wiki/1998_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16441561-1.html.csv | comparative | the hamilton tiger-cats had their pick before the british columbia lions . | {'row_1': '1', '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', 'cfl team', 'hamilton tiger - cats'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cfl team record fuzzily matches to hamilton tiger - cats .', 'tostr': 'filter_eq { all_rows ; cfl team ; hamilton tiger - cats }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; cfl team ; hamilton tiger - cats } ; pick }', 'tointer': 'select the rows whose cfl team record fuzzily matches to hamilton tiger - cats . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cfl team', 'british columbia lions'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose cfl team record fuzzily matches to british columbia lions .', 'tostr': 'filter_eq { all_rows ; cfl team ; british columbia lions }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; cfl team ; british columbia lions } ; pick }', 'tointer': 'select the rows whose cfl team record fuzzily matches to british columbia lions . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; cfl team ; hamilton tiger - cats } ; pick } ; hop { filter_eq { all_rows ; cfl team ; british columbia lions } ; pick } } = true', 'tointer': 'select the rows whose cfl team record fuzzily matches to hamilton tiger - cats . take the pick record of this row . select the rows whose cfl team record fuzzily matches to british columbia lions . take the pick record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; cfl team ; hamilton tiger - cats } ; pick } ; hop { filter_eq { all_rows ; cfl team ; british columbia lions } ; pick } } = true | select the rows whose cfl team record fuzzily matches to hamilton tiger - cats . take the pick record of this row . select the rows whose cfl team record fuzzily matches to british columbia lions . take the pick 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, 'cfl team_7': 7, 'hamilton tiger - cats_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'cfl team_11': 11, 'british columbia lions_12': 12, 'pick_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', 'cfl team_7': 'cfl team', 'hamilton tiger - cats_8': 'hamilton tiger - cats', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'cfl team_11': 'cfl team', 'british columbia lions_12': 'british columbia lions', 'pick_13': 'pick'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'cfl team_7': [0], 'hamilton tiger - cats_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'cfl team_11': [1], 'british columbia lions_12': [1], 'pick_13': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['1', 'hamilton tiger - cats', 'tim fleiszer', 'dl', 'harvard'], ['2', 'toronto argonauts', 'dave miller - johnston', 'p / k', 'concordia'], ['3', 'british columbia lions', 'steve hardin', 't', 'oregon'], ['4', 'calgary stampeders', 'marc pilon', 'lb', 'syracuse'], ['5', 'edmonton eskimos', 'phillippe girard', 'db', 'mount allison'], ['6', 'montreal alouettes', 'ben cahoon', 'wr', 'brigham young'], ['7', 'saskatchewan roughriders', 'curtis galick', 'db', 'british columbia']] |
sigurd rushfeldt | https://en.wikipedia.org/wiki/Sigurd_Rushfeldt | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1207980-1.html.csv | aggregation | the average number of scores that sigurd rushfeldt has had is 1.17 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1.17', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'scored'], 'result': '1.17', 'ind': 0, 'tostr': 'avg { all_rows ; scored }'}, '1.17'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; scored } ; 1.17 } = true', 'tointer': 'the average of the scored record of all rows is 1.17 .'} | round_eq { avg { all_rows ; scored } ; 1.17 } = true | the average of the scored record of all rows is 1.17 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'scored_4': 4, '1.17_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'scored_4': 'scored', '1.17_5': '1.17'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'scored_4': [0], '1.17_5': [1]} | ['date', 'venue', 'result', 'competition', 'scored'] | [['2002 - 05 - 14', 'ullevaal stadion , oslo', '3 - 0', 'friendly match', '1'], ['2003 - 01 - 28', 'bausher , muscat', '2 - 0', 'friendly match', '1'], ['2003 - 02 - 04', 'stade josy barthel , luxembourg city', '2 - 0', 'uefa euro 2004 qualifying', '1'], ['2004 - 04 - 28', 'ullevaal stadion , oslo', '3 - 2', 'friendly match', '1'], ['2005 - 02 - 09', "ta ' qali stadium , attard", '3 - 0', 'friendly match', '2'], ['2005 - 10 - 08', 'ullevaal stadion , oslo', '1 - 0', '2006 fifa world cup qualification', '1']] |
religion in eritrea | https://en.wikipedia.org/wiki/Religion_in_Eritrea | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16806446-2.html.csv | ordinal | the saho ethic group has the 3rd largest population in eritrea . | {'row': '3', 'col': '3', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'population', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ; 3 }'}, 'ethnic group'], 'result': 'saho', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population ; 3 } ; ethnic group }'}, 'saho'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; population ; 3 } ; ethnic group } ; saho } = true', 'tointer': 'select the row whose population record of all rows is 3rd maximum . the ethnic group record of this row is saho .'} | eq { hop { nth_argmax { all_rows ; population ; 3 } ; ethnic group } ; saho } = true | select the row whose population record of all rows is 3rd maximum . the ethnic group record of this row is saho . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population_5': 5, '3_6': 6, 'ethnic group_7': 7, 'saho_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', 'population_5': 'population', '3_6': '3', 'ethnic group_7': 'ethnic group', 'saho_8': 'saho'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population_5': [0], '3_6': [0], 'ethnic group_7': [1], 'saho_8': [2]} | ['ethnic group', 'main regions', 'population', 'percentage of total population', 'christians', 'muslims', 'other'] | [['tigrigna', 'maekel region , debub region', '3319680', '57 %', '53 %', '44 %', '1 %'], ['tigre', 'gash - barka region , anseba region , maekel region', '1630720', '28 %', '6 %', '90 %', '4 %'], ['saho', 'northern red sea region , debub region', '232960', '4 %', '7 %', '93 %', 'n / a'], ['kunama', 'gash - barka region', '174720', '3 %', '41 %', '23 %', '36 %'], ['afar', 'southern red sea region', '174720', '3 %', '2 %', '98 %', 'n / a'], ['bilen', 'anseba region', '116480', '2 %', '48 %', '47 %', '5 %'], ['nara', 'gash - barka region', '58240', '1 %', '14 %', '85 %', '1 %'], ['beja', 'gash - barka region , anseba region', '58240', '1 %', '1 %', '98 %', '1 %'], ['rashaida', 'northern red sea region', '58.240', '1 %', 'n / a', '99 %', 'na']] |
cultural interest fraternities and sororities | https://en.wikipedia.org/wiki/Cultural_interest_fraternities_and_sororities | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2538117-7.html.csv | comparative | omicron epsilon pi was founded six years before alpha lambda zeta . | {'row_1': '3', 'row_2': '5', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '6 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'organization', 'omicron epsilon pi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose organization record fuzzily matches to omicron epsilon pi .', 'tostr': 'filter_eq { all_rows ; organization ; omicron epsilon pi }'}, 'founding date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; organization ; omicron epsilon pi } ; founding date }', 'tointer': 'select the rows whose organization record fuzzily matches to omicron epsilon pi . take the founding date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'organization', 'alpha lambda zeta'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose organization record fuzzily matches to alpha lambda zeta .', 'tostr': 'filter_eq { all_rows ; organization ; alpha lambda zeta }'}, 'founding date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; organization ; alpha lambda zeta } ; founding date }', 'tointer': 'select the rows whose organization record fuzzily matches to alpha lambda zeta . take the founding date record of this row .'}], 'result': '-6 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; organization ; omicron epsilon pi } ; founding date } ; hop { filter_eq { all_rows ; organization ; alpha lambda zeta } ; founding date } }'}, '-6 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; organization ; omicron epsilon pi } ; founding date } ; hop { filter_eq { all_rows ; organization ; alpha lambda zeta } ; founding date } } ; -6 years } = true', 'tointer': 'select the rows whose organization record fuzzily matches to omicron epsilon pi . take the founding date record of this row . select the rows whose organization record fuzzily matches to alpha lambda zeta . take the founding date record of this row . the second record is 6 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; organization ; omicron epsilon pi } ; founding date } ; hop { filter_eq { all_rows ; organization ; alpha lambda zeta } ; founding date } } ; -6 years } = true | select the rows whose organization record fuzzily matches to omicron epsilon pi . take the founding date record of this row . select the rows whose organization record fuzzily matches to alpha lambda zeta . take the founding date record of this row . the second record is 6 years larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'organization_8': 8, 'omicron epsilon pi_9': 9, 'founding date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'organization_12': 12, 'alpha lambda zeta_13': 13, 'founding date_14': 14, '-6 years_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'organization_8': 'organization', 'omicron epsilon pi_9': 'omicron epsilon pi', 'founding date_10': 'founding date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'organization_12': 'organization', 'alpha lambda zeta_13': 'alpha lambda zeta', 'founding date_14': 'founding date', '-6 years_15': '-6 years'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'organization_8': [0], 'omicron epsilon pi_9': [0], 'founding date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'organization_12': [1], 'alpha lambda zeta_13': [1], 'founding date_14': [3], '-6 years_15': [5]} | ['letters', 'organization', 'nickname', 'founding date', 'founding university', 'type'] | [['δλφ', 'delta lambda phi', "dlp , deltas ' , or lambda men", '1986 - 10 - 15', 'washington , dc', 'fraternity'], ['κψκ', 'kappa psi kappa', 'canes , k - psis , diamonds , or angels', '2001 - 08 - 17', 'tallahassee , florida', 'fraternity'], ['οεπ', 'omicron epsilon pi', 'the epps', '2000 - 12 - 07', 'tallahassee , florida', 'sorority'], ['γρλ', 'gamma rho lambda 1', 'grl', '2003 - 08 - 25', 'tempe , arizona', 'sorority'], ['αλζ', 'alpha lambda zeta', 'the regal alphas', '2006 - 01 - 09', 'houston , texas and atlanta , georgia', 'fraternity'], ['καλ', 'kappa alpha lambda', 'the kappas', '2003 - 10 - 19', 'clark atlanta university', 'sorority'], ['φαν', 'phi alpha nu', 'phi - nomenal gentlewomen', '2006 - 07 - 30', 'charlotte , nc', 'fraternity']] |
gastão elias | https://en.wikipedia.org/wiki/Gast%C3%A3o_Elias | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16741821-8.html.csv | majority | most of the tennis matches for gastão elias ended in losses for him . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'loss', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'w / l', 'loss'], 'result': True, 'ind': 0, 'tointer': 'for the w / l records of all rows , most of them fuzzily match to loss .', 'tostr': 'most_eq { all_rows ; w / l ; loss } = true'} | most_eq { all_rows ; w / l ; loss } = true | for the w / l records of all rows , most of them fuzzily match to loss . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'w / l_3': 3, 'loss_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'w / l_3': 'w / l', 'loss_4': 'loss'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'w / l_3': [0], 'loss_4': [0]} | ['edition', 'round', 'date', 'against', 'surface', 'opponent', 'w / l', 'result'] | [['2007 davis cup europe / africa group i', '1r', '9 - 11 february 2007', 'georgia', 'carpet', 'george khrikadze', 'win', '6 - 3 , 7 - 6 ( 7 - 5 )'], ['2007 davis cup europe / africa group i', 'gi po', '21 - 23 september 2007', 'netherlands', 'hard', 'robin haase', 'loss', '1 - 6 , 1 - 6 , 6 - 2 , 7 - 5 , 2 - 6'], ['2008 davis cup europe / africa group ii', '1r', '11 - 13 april 2008', 'tunisia', 'clay', 'walid jallali', 'loss', '5 - 7 , 2 - 6'], ['2008 davis cup europe / africa group ii', 'sf', '19 - 21 september 2008', 'ukraine', 'hard', 'sergiy stakhovsky', 'loss', '4 - 6 , 6 - 7 ( 5 - 7 ) , 4 - 6'], ['2012 davis cup europe / africa group i', 'gi po', '14 - 16 september 2012', 'slovakia', 'hard', 'martin kližan', 'loss', '6 - 3 , 2 - 6 , 6 - 7 ( 4 - 7 ) , 2 - 6'], ['2013 davis cup europe / africa group ii', '2r', '5 - 7 april 2013', 'lithuania', 'clay', 'lukas mugevicius', 'win', '6 - 0 , 6 - 1 , 6 - 2']] |
united states house of representatives elections , 2012 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2012 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25030512-36.html.csv | count | 6 incumbents were re - elected during the 2012 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '6', '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': '6', '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 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re - elected } } ; 6 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 6 } = true | select the rows whose result record fuzzily matches to re - elected . 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, 'result_5': 5, 're - elected_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', 'result_5': 'result', 're - elected_6': 're - elected', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '6_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 3', 'walter jones jr', 'republican', '1994', 're - elected', 'walter jones jr ( r ) 63.2 % erik anderson ( d ) 36.8 %'], ['north carolina 4', 'david price', 'democratic', '1996', 're - elected', "david price ( d ) 74.4 % tim d'annunzio ( r ) 25.6 %"], ['north carolina 6', 'howard coble', 'republican', '1984', 're - elected', 'howard coble ( r ) 60.9 % tony foriest ( d ) 39.1 %'], ['north carolina 7', 'mike mcintyre', 'democratic', '1996', 're - elected', 'mike mcintyre ( d ) 50.1 % david rouzer ( r ) 49.9 %'], ['north carolina 8', 'larry kissell', 'democratic', '2008', 'lost re - election republican gain', 'richard hudson ( r ) 54.1 % larry kissell ( d ) 45.9 %'], ['north carolina 10', 'patrick mchenry', 'republican', '2004', 're - elected', 'patrick mchenry ( r ) 57.0 % patsy keever ( d ) 43.0 %'], ['north carolina 11', 'heath shuler', 'democratic', '2006', 'retired republican gain', 'mark meadows ( r ) 57.4 % hayden rogers ( d ) 42.6 %'], ['north carolina 12', 'mel watt', 'democratic', '1992', 're - elected', 'mel watt ( d ) 79.7 % jack brosch ( r ) 20.3 %']] |
2005 japanese television dramas | https://en.wikipedia.org/wiki/2005_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18540104-2.html.csv | superlative | the highest rating percentage for 2005 japanese television dramas was for the one titled densha otoko . | {'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', 'average ratings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; average ratings }'}, 'romaji title'], 'result': 'densha otoko', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; average ratings } ; romaji title }'}, 'densha otoko'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; average ratings } ; romaji title } ; densha otoko } = true', 'tointer': 'select the row whose average ratings record of all rows is maximum . the romaji title record of this row is densha otoko .'} | eq { hop { argmax { all_rows ; average ratings } ; romaji title } ; densha otoko } = true | select the row whose average ratings record of all rows is maximum . the romaji title record of this row is densha otoko . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'average ratings_5': 5, 'romaji title_6': 6, 'densha otoko_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'average ratings_5': 'average ratings', 'romaji title_6': 'romaji title', 'densha otoko_7': 'densha otoko'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'average ratings_5': [0], 'romaji title_6': [1], 'densha otoko_7': [2]} | ['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings'] | [['電車男', 'densha otoko', 'fuji tv', '11', '21.0 %'], ['海猿 umizaru evolution', 'umizaru evolution', 'fuji tv', '11', '13.2 %'], ['スローダンス', 'slow dance', 'fuji tv', '11', '16.8 %'], ['がんばっていきまっしょい', 'ganbatte ikimasshoi', 'fuji tv', '10', '12.4 %'], ['幸せになりたい !', 'shiawase ni naritai !', 'tbs', '10', '11.8 %'], ['女系家族', 'nyokei kazoku', 'tbs', '11', '13.85 %'], ['いま 、 会いにゆきます', 'ima , ai ni yukimasu', 'tbs', '10', '11 %'], ['ドラゴン桜', 'dragon zakura', 'tbs', '11', '16.4 %'], ['はるか17', 'haruka seventeen', 'tv asahi', '10', '8.9 %'], ['菊次郎とさき 2', 'kikujirou to saki 2', 'ntv', '9', '14.9 %'], ['女王の教室', 'joou no kyoushitsu', 'ntv', '11', '15.7 %']] |
the firebird | https://en.wikipedia.org/wiki/The_Firebird | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1060482-1.html.csv | majority | most of the releases of the firebird have been done so on cd . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'cd', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'format', 'cd'], 'result': True, 'ind': 0, 'tointer': 'for the format records of all rows , most of them fuzzily match to cd .', 'tostr': 'most_eq { all_rows ; format ; cd } = true'} | most_eq { all_rows ; format ; cd } = true | for the format records of all rows , most of them fuzzily match to cd . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'format_3': 3, 'cd_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'format_3': 'format', 'cd_4': 'cd'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'format_3': [0], 'cd_4': [0]} | ['orchestra', 'conductor', 'record company', 'year of recording', 'format'] | [['london symphony orchestra', 'antal doráti', 'mercury records', '1959', 'cd'], ['columbia symphony orchestra', 'igor stravinsky', 'columbia masterworks', '1961', 'cd / lp'], ['royal concertgebouw orchestra', 'colin davis', 'philips', '1978', 'cd'], ['royal danish orchestra', 'paul jorgensen', 'kultur', '1982', 'dvd'], ['detroit symphony orchestra', 'antal doráti', 'decca records', '1982', 'cd'], ['montreal symphony orchestra', 'charles dutoit', 'decca records', '1984', 'cd'], ['seattle symphony orchestra', 'gerard schwarz', 'delos records', '1992', 'cd'], ['chicago symphony orchestra', 'pierre boulez', 'deutsche grammophon', '1993', 'cd'], ['kirov orchestra', 'valeri gergiev', 'philips classics records', '1998', 'cd'], ['philharmonia orchestra', 'robert craft', 'koch records / naxos records', '1996', 'cd'], ['orchestre de paris', 'seiji ozawa', 'emi', '1997', 'cd'], ['san francisco symphony orchestra', 'michael tilson thomas', 'rca', '1998', 'cd'], ['city of birmingham symphony orchestra', 'simon rattle', 'emi', '2008', 'cd'], ['los angeles philharmonic orchestra', 'esa - pekka salonen', 'deutsche grammophon', '2008', 'digital download']] |
2009 canadian olympic curling trials | https://en.wikipedia.org/wiki/2009_Canadian_Olympic_Curling_Trials | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17012578-2.html.csv | unique | bob ursel 's team is the only one to represent kelowna . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'kelowna', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'kelowna'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city record fuzzily matches to kelowna .', 'tostr': 'filter_eq { all_rows ; city ; kelowna }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; city ; kelowna } }', 'tointer': 'select the rows whose city record fuzzily matches to kelowna . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'kelowna'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city record fuzzily matches to kelowna .', 'tostr': 'filter_eq { all_rows ; city ; kelowna }'}, 'skip'], 'result': 'bob ursel', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; city ; kelowna } ; skip }'}, 'bob ursel'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; city ; kelowna } ; skip } ; bob ursel }', 'tointer': 'the skip record of this unqiue row is bob ursel .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; city ; kelowna } } ; eq { hop { filter_eq { all_rows ; city ; kelowna } ; skip } ; bob ursel } } = true', 'tointer': 'select the rows whose city record fuzzily matches to kelowna . there is only one such row in the table . the skip record of this unqiue row is bob ursel .'} | and { only { filter_eq { all_rows ; city ; kelowna } } ; eq { hop { filter_eq { all_rows ; city ; kelowna } ; skip } ; bob ursel } } = true | select the rows whose city record fuzzily matches to kelowna . there is only one such row in the table . the skip record of this unqiue row is bob ursel . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'city_7': 7, 'kelowna_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'skip_9': 9, 'bob ursel_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'city_7': 'city', 'kelowna_8': 'kelowna', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'skip_9': 'skip', 'bob ursel_10': 'bob ursel'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'city_7': [0], 'kelowna_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'skip_9': [2], 'bob ursel_10': [3]} | ['skip', 'third / vice skip', 'second', 'lead', 'city'] | [['kerry burtnyk', 'don walchuk', 'richard daneault', 'garth smith', 'winnipeg'], ['pat simmons', 'gerry adam', 'jeff sharp', 'steve laycock', 'davidson'], ['jeff stoughton', 'kevin park', 'rob fowler', 'steve gould', 'winnipeg'], ['wayne middaugh', 'jon mead', 'john epping', 'scott bailey', 'islington'], ['brad gushue', 'mark nichols', 'ryan fry', 'jamie korab', "st john 's"], ['mike mcewen', 'b j neufeld', 'matt wozniak', 'denni neufeld', 'winnipeg'], ['joel jordison', 'scott bitz', 'aryn schmidt', 'dean hicke', 'moose jaw'], ['bob ursel', 'jim cotter', 'kevin folk', 'rick sawatsky', 'kelowna'], ['jean - michel ménard', 'martin crête', 'éric sylvain', 'jean gagnon', 'lévis'], ['ted appelman', 'tom appelman', 'bradon klassen', 'brendan melnyk', 'edmonton'], ['greg mcaulay', 'ken maskiewich', 'deane horning', 'aaron watson', 'richmond'], ['jason gunnlaugson', 'justin richter', 'braden zawada', 'tyler forrest', 'beausejour']] |
2002 pga championship | https://en.wikipedia.org/wiki/2002_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18009787-7.html.csv | aggregation | the total score amongst all players in the 2002 pga championship is 4,577 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '4577', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '4577', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '4577'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 4577 } = true', 'tointer': 'the sum of the score record of all rows is 4577 .'} | round_eq { sum { all_rows ; score } ; 4577 } = true | the sum of the score record of all rows is 4577 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '4577_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '4577_5': '4577'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '4577_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'rich beem', 'united states', '72 + 66 + 72 + 68 = 278', '- 10', '990000'], ['2', 'tiger woods', 'united states', '71 + 69 + 72 + 67 = 279', '- 9', '594000'], ['3', 'chris riley', 'united states', '71 + 70 + 72 + 70 = 283', '- 5', '374000'], ['t4', 'fred funk', 'united states', '68 + 70 + 73 + 73 = 284', '- 4', '235000'], ['t4', 'justin leonard', 'united states', '72 + 66 + 69 + 77 = 284', '- 4', '235000'], ['6', 'rocco mediate', 'united states', '72 + 73 + 70 + 70 = 285', '- 3', '185000'], ['7', 'mark calcavecchia', 'united states', '70 + 68 + 74 + 74 = 286', '- 2', '172000'], ['8', 'vijay singh', 'fiji', '71 + 74 + 74 + 68 = 287', '- 1', '159000'], ['9', 'jim furyk', 'united states', '68 + 73 + 76 + 71 = 288', 'e', '149000'], ['t10', 'robert allenby', 'australia', '76 + 66 + 77 + 70 = 289', '+ 1', '110714'], ['t10', 'stewart cink', 'united states', '74 + 74 + 72 + 69 = 289', '+ 1', '110714'], ['t10', 'josé cóceres', 'argentina', '72 + 71 + 72 + 74 = 289', '+ 1', '110714'], ['t10', 'pierre fulke', 'sweden', '72 + 68 + 78 + 71 = 289', '+ 1', '110714'], ['t10', 'sergio garcía', 'spain', '75 + 73 + 73 + 68 = 289', '+ 1', '110714'], ['t10', 'ricardo gonzález', 'argentina', '74 + 73 + 71 + 71 = 289', '+ 1', '110714'], ['t10', 'steve lowery', 'united states', '71 + 71 + 73 + 74 = 289', '+ 1', '110714']] |
malayalam calendar | https://en.wikipedia.org/wiki/Malayalam_calendar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-169955-1.html.csv | unique | only the month of chingam is associated with the zodiac sign of leo . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'leo', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sign of zodiac', 'leo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sign of zodiac record fuzzily matches to leo .', 'tostr': 'filter_eq { all_rows ; sign of zodiac ; leo }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; sign of zodiac ; leo } }', 'tointer': 'select the rows whose sign of zodiac record fuzzily matches to leo . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sign of zodiac', 'leo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sign of zodiac record fuzzily matches to leo .', 'tostr': 'filter_eq { all_rows ; sign of zodiac ; leo }'}, 'months in malayalam era'], 'result': 'chingam', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; sign of zodiac ; leo } ; months in malayalam era }'}, 'chingam'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; sign of zodiac ; leo } ; months in malayalam era } ; chingam }', 'tointer': 'the months in malayalam era record of this unqiue row is chingam .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; sign of zodiac ; leo } } ; eq { hop { filter_eq { all_rows ; sign of zodiac ; leo } ; months in malayalam era } ; chingam } } = true', 'tointer': 'select the rows whose sign of zodiac record fuzzily matches to leo . there is only one such row in the table . the months in malayalam era record of this unqiue row is chingam .'} | and { only { filter_eq { all_rows ; sign of zodiac ; leo } } ; eq { hop { filter_eq { all_rows ; sign of zodiac ; leo } ; months in malayalam era } ; chingam } } = true | select the rows whose sign of zodiac record fuzzily matches to leo . there is only one such row in the table . the months in malayalam era record of this unqiue row is chingam . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'sign of zodiac_7': 7, 'leo_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'months in malayalam era_9': 9, 'chingam_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'sign of zodiac_7': 'sign of zodiac', 'leo_8': 'leo', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'months in malayalam era_9': 'months in malayalam era', 'chingam_10': 'chingam'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'sign of zodiac_7': [0], 'leo_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'months in malayalam era_9': [2], 'chingam_10': [3]} | ['months in malayalam era', 'in malayalam', 'gregorian calendar', 'tamil calendar', 'saka era', 'sign of zodiac'] | [['chingam', 'ചിങ ങ', 'august - september', 'aavani', 'sravan - bhadrapada', 'leo'], ['kanni', 'കന നി', 'september - october', 'purattasi', 'bhadrapada - asvina', 'virgo'], ['tulam', 'തുലാ', 'october - november', 'aippasi', 'asvina - kartika', 'libra'], ['vrscikam', 'വൃശ ചിക', 'november - december', 'karthigai', 'kartika - agrahayana', 'scorpio'], ['dhanu', 'ധനു', 'december - january', 'margazhi', 'agrahayana - pausa', 'sagittarius'], ['makaram', 'മകര', 'january - february', 'thai', 'pausa - magha', 'capricon'], ['kumbham', 'കു ഭ', 'february - march', 'maasi', 'magha - phalguna', 'aquarius'], ['minam', 'മീന', 'march - april', 'panguni', 'phalguna - chaitra', 'pisces'], ['medam', 'മേട', 'april - may', 'chithirai', 'chaitra - vaisakha', 'aries'], ['edavam ( idavam )', 'ഇടവ', 'may - june', 'vaikasi', 'vaisakha - jyaistha', 'taurus'], ['mithunam', 'മിഥുന', 'june - july', 'aani', 'jyaistha - asada', 'gemini'], ['karkadakam', 'കര ക കടക', 'july - august', 'aadi', 'asada - sravana', 'cancer']] |
united states house of representatives elections in connecticut , 2008 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Connecticut%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18722787-1.html.csv | ordinal | for the united states house of representatives election in 2008 in connecticut , the 2nd highest numbered district had christopher shays as the incumbent . | {'row': '4', 'col': '1', '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', 'district', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; district ; 2 }'}, 'incumbent'], 'result': 'christopher shays', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; district ; 2 } ; incumbent }'}, 'christopher shays'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; district ; 2 } ; incumbent } ; christopher shays } = true', 'tointer': 'select the row whose district record of all rows is 2nd maximum . the incumbent record of this row is christopher shays .'} | eq { hop { nth_argmax { all_rows ; district ; 2 } ; incumbent } ; christopher shays } = true | select the row whose district record of all rows is 2nd maximum . the incumbent record of this row is christopher shays . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'district_5': 5, '2_6': 6, 'incumbent_7': 7, 'christopher shays_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', 'district_5': 'district', '2_6': '2', 'incumbent_7': 'incumbent', 'christopher shays_8': 'christopher shays'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'district_5': [0], '2_6': [0], 'incumbent_7': [1], 'christopher shays_8': [2]} | ['district', 'incumbent', '2008 status', 'democratic', 'republican', 'green'] | [['1', 'john b larson', 're - election', 'john b larson', 'joe visconti', 'stephen e d fournier'], ['2', 'joe courtney', 're - election', 'joe courtney', 'sean sullivan', 'g scott deshefy'], ['3', 'rosa delauro', 're - election', 'rosa delauro', 'bo itshaky', 'ralph ferrucci'], ['4', 'christopher shays', 're - election', 'jim himes', 'christopher shays', 'richard duffee'], ['5', 'chris murphy', 're - election', 'chris murphy', 'david cappiello', 'harold burbank']] |
1994 group | https://en.wikipedia.org/wiki/1994_Group | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-142950-1.html.csv | aggregation | there are a total of 123,950 students enrolled in the 1994 group 's member institutions . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '123950', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total number of students'], 'result': '123950', 'ind': 0, 'tostr': 'sum { all_rows ; total number of students }'}, '123950'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total number of students } ; 123950 } = true', 'tointer': 'the sum of the total number of students record of all rows is 123950 .'} | round_eq { sum { all_rows ; total number of students } ; 123950 } = true | the sum of the total number of students record of all rows is 123950 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total number of students_4': 4, '123950_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total number of students_4': 'total number of students', '123950_5': '123950'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total number of students_4': [0], '123950_5': [1]} | ['institution', 'location', 'established', 'gained university status', 'vice - chancellor', 'total number of students', 'research funding ( 000 )'] | [['birkbeck , university of london', 'london', '1823', '1920', 'professor david latchman', '19020', '9985'], ['university of east anglia', 'norwich', '1963', '1963', 'professor edward acton', '19585', '16482'], ['university of essex', 'colchester', '1964', '1964', 'professor anthony forster', '11690', '9967'], ['goldsmiths , university of london', 'london', '1891', '1904', 'dr pat loughrey', '7615', '8539'], ['institute of education , university of london', 'london', '1902', '1932', 'professor chris husbands', '7215', '7734'], ['university of lancaster', 'lancaster', '1964', '1964', 'professor mark smith', '12695', '18640'], ['university of leicester', 'leicester', '1921', '1957', 'professor robert burgess', '16160', '22225'], ['loughborough university', 'loughborough', '1909', '1966', 'professor robert allison', '17825', '22398'], ['royal holloway , university of london', 'egham', '1849', '1900', 'professor paul layzell ( principal )', '7620', '13699'], ['soas , university of london', 'london', '1916', '1916', 'professor paul webley', '4525', '7238']] |
cjbc ( am ) | https://en.wikipedia.org/wiki/CJBC_%28AM%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1873304-1.html.csv | unique | kingston is the only city of license than has a class a cjbc radio channel . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'a', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'a'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class record fuzzily matches to a .', 'tostr': 'filter_eq { all_rows ; class ; a }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; class ; a } }', 'tointer': 'select the rows whose class record fuzzily matches to a . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'a'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class record fuzzily matches to a .', 'tostr': 'filter_eq { all_rows ; class ; a }'}, 'city of license'], 'result': 'kingston', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; class ; a } ; city of license }'}, 'kingston'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; class ; a } ; city of license } ; kingston }', 'tointer': 'the city of license record of this unqiue row is kingston .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; class ; a } } ; eq { hop { filter_eq { all_rows ; class ; a } ; city of license } ; kingston } } = true', 'tointer': 'select the rows whose class record fuzzily matches to a . there is only one such row in the table . the city of license record of this unqiue row is kingston .'} | and { only { filter_eq { all_rows ; class ; a } } ; eq { hop { filter_eq { all_rows ; class ; a } ; city of license } ; kingston } } = true | select the rows whose class record fuzzily matches to a . there is only one such row in the table . the city of license record of this unqiue row is kingston . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'class_7': 7, 'a_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'city of license_9': 9, 'kingston_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'class_7': 'class', 'a_8': 'a', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'city of license_9': 'city of license', 'kingston_10': 'kingston'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'class_7': [0], 'a_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'city of license_9': [2], 'kingston_10': [3]} | ['city of license', 'identifier', 'frequency', 'power', 'class', 'recnet'] | [['belleville', 'cjbc - 1 - fm', '94.3 fm', '34950 s watt', 'b', 'query'], ['kingston', 'cjbc - 2 - fm', '99.5 fm', '1560 watts', 'a', 'query'], ['london', 'cjbc - 4 - fm', '99.3 fm', '22500 watts', 'b', 'query'], ['penetanguishene', 'cjbc - 3 - fm', '96.5 fm', '15300 watts', 'b', 'query'], ['peterborough', 'cjbc - 5 - fm', '106.3 fm', '13000 watts', 'b', 'query']] |
emanuele pirro | https://en.wikipedia.org/wiki/Emanuele_Pirro | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219777-5.html.csv | aggregation | emanuele pirro was ranked , on average around 20th from 1999 to 2010 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '10th', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'rank'], 'result': '10th', 'ind': 0, 'tostr': 'avg { all_rows ; rank }'}, '10th'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; rank } ; 10th } = true', 'tointer': 'the average of the rank record of all rows is 10th .'} | round_eq { avg { all_rows ; rank } ; 10th } = true | the average of the rank record of all rows is 10th . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'rank_4': 4, '10th_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'rank_4': 'rank', '10th_5': '10th'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'rank_4': [0], '10th_5': [1]} | ['year', 'entrant', 'class', 'chassis', 'engine', 'tyres', 'rank', 'points'] | [['1999', 'audi sport team joest', 'lmp', 'audi r8r', 'audi 3.6 l turbo v8', 'm', '52nd', '20'], ['2000', 'audi sport north america', 'lmp', 'audi r8', 'audi 3.6 l turbo v8', 'm', '3rd', '232'], ['2000', 'audi sport north america', 'lmp', 'audi r8r', 'audi 3.6 l turbo v8', 'm', '3rd', '232'], ['2001', 'audi sport north america', 'lmp900', 'audi r8', 'audi 3.6 l turbo v8', 'm', '1st', '202'], ['2002', 'audi sport north america', 'lmp900', 'audi r8', 'audi 3.6 l turbo v8', 'm', '4th', '206'], ['2003', 'adt champion racing', 'lmp900', 'audi r8', 'audi 3.6 l turbo v8', 'm', '18th', '22'], ['2004', 'adt champion racing', 'lmp1', 'audi r8', 'audi 3.6 l turbo v8', 'm', '13th', '22'], ['2005', 'adt champion racing', 'lmp1', 'audi r8', 'audi 3.6 l turbo v8', 'm', '1st', '182'], ['2006', 'audi sport north america', 'lmp1', 'audi r10 tdi', 'audi 5.5 l turbo v12 ( diesel )', 'm', '5th', '80'], ['2007', 'audi sport north america', 'lmp1', 'audi r10 tdi', 'audi 5.5 l turbo v12 ( diesel )', 'm', '4th', '175'], ['2008', 'audi sport north america', 'lmp1', 'audi r10 tdi', 'audi 5.5 l turbo v12 ( diesel )', 'm', '3rd', '156'], ['2010', 'drayson racing', 'lmp1', 'lola b09 / 60', 'judd gv5 .5 s2 5.5 l v10', 'm', '12th', '46']] |
vehicles & animals | https://en.wikipedia.org/wiki/Vehicles_%26_Animals | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1546629-3.html.csv | majority | most releases of the album vehicles & animals were from the label parlophone . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'parlophone', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'label', 'parlophone'], 'result': True, 'ind': 0, 'tointer': 'for the label records of all rows , most of them fuzzily match to parlophone .', 'tostr': 'most_eq { all_rows ; label ; parlophone } = true'} | most_eq { all_rows ; label ; parlophone } = true | for the label records of all rows , most of them fuzzily match to parlophone . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'label_3': 3, 'parlophone_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'label_3': 'label', 'parlophone_4': 'parlophone'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'label_3': [0], 'parlophone_4': [0]} | ['country', 'date', 'label', 'format', 'catalog'] | [['united kingdom', '7 april 2003', 'parlophone', 'lp', '582 2911'], ['united kingdom', '7 april 2003', 'parlophone', 'cd', '582 2912'], ['united kingdom', '7 april 2003', 'parlophone', 'cd digipak', '584 2112'], ['united states', '18 may 2004', 'astralwerks', 'cd', 'asw 82291'], ['australia', '14 march 2005', 'capitol records', 'cd', '582 3412']] |
ross bagdasarian , jr | https://en.wikipedia.org/wiki/Ross_Bagdasarian%2C_Jr. | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1543453-1.html.csv | aggregation | the chipmunk movies that ross bagdasarian jr. worked on have an average release date of 2002 . | {'scope': 'all', 'col': '1', 'type': 'average', 'result': '2002', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'year'], 'result': '2002', 'ind': 0, 'tostr': 'avg { all_rows ; year }'}, '2002'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; year } ; 2002 } = true', 'tointer': 'the average of the year record of all rows is 2002 .'} | round_eq { avg { all_rows ; year } ; 2002 } = true | the average of the year record of all rows is 2002 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'year_4': 4, '2002_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'year_4': 'year', '2002_5': '2002'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'year_4': [0], '2002_5': [1]} | ['year', 'title', 'producer', 'actor', 'role'] | [['1987', 'the chipmunk adventure', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['1999', 'alvin and the chipmunks meet frankenstein', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['2000', 'alvin and the chipmunks meet the wolfman', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['2005', 'little alvin and the mini - munks', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['2007', 'alvin and the chipmunks', 'yes', 'yes', 'alvin seville simon seville'], ['2009', 'alvin and the chipmunks : the squeakquel', 'yes', 'yes', 'alvin seville simon seville'], ['2011', 'alvin and the chipmunks : chipwrecked', 'yes', 'yes', 'alvin seville simon seville']] |
george hu | https://en.wikipedia.org/wiki/George_Hu | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18932977-1.html.csv | unique | george hu only played a guest role for one of his roles . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'guest', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'role', 'guest'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose role record fuzzily matches to guest .', 'tostr': 'filter_eq { all_rows ; role ; guest }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; role ; guest } } = true', 'tointer': 'select the rows whose role record fuzzily matches to guest . there is only one such row in the table .'} | only { filter_eq { all_rows ; role ; guest } } = true | select the rows whose role record fuzzily matches to guest . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'role_4': 4, 'guest_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'role_4': 'role', 'guest_5': 'guest'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'role_4': [0], 'guest_5': [0]} | ['year', 'chinese title', 'english', 'role', 'character'] | [['2006', '屋頂上的綠寶石', 'emerald on the roof', 'minor', 'nie kai ( 聶凱 )'], ['2007', '武十郎', 'love at first fight', 'main', 'lei sheng da ( 雷聲大 )'], ['2007', '終極一家', 'the x - family', 'guest', 'shen xing zhe ( 神行者 ) / qiang ling wang ( 槍靈王 )'], ['2007', '公主小妹', 'romantic princess', 'supporting', 'nan feng lin ( 南風璘 )'], ['2008', '籃球火', 'hot shot', 'supporting', 'wu ji wei ( 無極威 )'], ['2009', '愛就宅一起', 'together', 'main', 'wei jia sen ( 魏加森 )'], ['2009', '終極三國', 'ko3an guo', 'main', 'guan yu ( 關羽 )'], ['2010', '我和我的兄弟 ~ 恩', 'me & my brothers', 'main', 'dennis'], ['2011', '旋風管家', 'hayate the combat butler ( tv series )', 'lead role', 'ling qisa ( 凌奇颯 ) / hayate ayazaki'], ['2011', '新兵日記之特戰英雄', 'rookies diary season2', 'main', 'zheng qiang ( 鄭強 )'], ['2012', '戀夏38 ℃', 'summer fever', 'lead role', 'lin ming kuan ( 林明寬 )'], ['2012', '真愛趁現在', 'love , now', 'lead role', 'lan shi - de ( 藍仕德 )'], ['2013', '真愛黑白配', 'love around', 'lead role', 'zhou zhen ( 周震 )']] |
2006 toronto argonauts season | https://en.wikipedia.org/wiki/2006_Toronto_Argonauts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20649850-1.html.csv | unique | in the 2006 toronto argonauts season , the only player who went to college in new mexico was brian ramsay . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'new mexico', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'new mexico'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to new mexico .', 'tostr': 'filter_eq { all_rows ; college ; new mexico }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; new mexico } }', 'tointer': 'select the rows whose college record fuzzily matches to new mexico . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'new mexico'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to new mexico .', 'tostr': 'filter_eq { all_rows ; college ; new mexico }'}, 'player'], 'result': 'brian ramsay', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; new mexico } ; player }'}, 'brian ramsay'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; new mexico } ; player } ; brian ramsay }', 'tointer': 'the player record of this unqiue row is brian ramsay .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; new mexico } } ; eq { hop { filter_eq { all_rows ; college ; new mexico } ; player } ; brian ramsay } } = true', 'tointer': 'select the rows whose college record fuzzily matches to new mexico . there is only one such row in the table . the player record of this unqiue row is brian ramsay .'} | and { only { filter_eq { all_rows ; college ; new mexico } } ; eq { hop { filter_eq { all_rows ; college ; new mexico } ; player } ; brian ramsay } } = true | select the rows whose college record fuzzily matches to new mexico . there is only one such row in the table . the player record of this unqiue row is brian ramsay . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'new mexico_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'brian ramsay_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'new mexico_8': 'new mexico', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'brian ramsay_10': 'brian ramsay'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'new mexico_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'brian ramsay_10': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['5', 'toronto argonauts', 'daniel federkeil', 'dl', 'calgary'], ['10', 'toronto argonauts', 'leron mitchell', 'db', 'western ontario'], ['14', 'toronto argonauts', 'aaron wagner', 'lb', 'brigham young'], ['31', 'toronto argonauts', 'obed cetoute', 'wr', 'central florida'], ['39', 'toronto argonauts', 'brian ramsay', 'ol', 'new mexico']] |
2007 - 08 guildford flames season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Guildford_Flames_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15213262-10.html.csv | count | the flames played four home games during the 07-08 season . | {'scope': 'all', 'criterion': 'equal', 'value': 'home', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'home'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to home .', 'tostr': 'filter_eq { all_rows ; venue ; home }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; home } }', 'tointer': 'select the rows whose venue record fuzzily matches to home . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; home } } ; 4 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to home . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; venue ; home } } ; 4 } = true | select the rows whose venue record fuzzily matches to home . 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, 'venue_5': 5, 'home_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', 'venue_5': 'venue', 'home_6': 'home', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'home_6': [0], '4_7': [2]} | ['date', 'opponent', 'venue', 'result', 'attendance', 'competition'] | [['1', 'bracknell bees', 'home', 'won 4 - 0', '1467', 'league'], ['5', 'telford tigers', 'home', 'won 5 - 4', '1634', 'league'], ['6', 'swindon wildcats', 'away', 'won 4 - 3 ( so )', '670', 'league'], ['12', 'slough jets', 'away', 'lost 5 - 7', '702', 'league'], ['13', 'milton keynes lightning', 'home', 'lost 5 - 6 ( so )', '1443', 'league'], ['19', 'wightlink raiders', 'away', 'won 10 - 4', '506', 'league'], ['20', 'bracknell bees', 'away', 'lost 1 - 4', '1110', 'league'], ['26', 'chelmsford chieftains', 'home', 'won 10 - 5', '1619', 'league']] |
vladimir koman | https://en.wikipedia.org/wiki/Vladimir_Koman | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10521952-3.html.csv | comparative | the match in october of 2012 was closer than the one in october of 2010 . | {'row_1': '7', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '16 october 2012'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 16 october 2012 .', 'tostr': 'filter_eq { all_rows ; date ; 16 october 2012 }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 16 october 2012 } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to 16 october 2012 . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '8 october 2010'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 8 october 2010 .', 'tostr': 'filter_eq { all_rows ; date ; 8 october 2010 }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 8 october 2010 } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to 8 october 2010 . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; date ; 16 october 2012 } ; score } ; hop { filter_eq { all_rows ; date ; 8 october 2010 } ; score } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 16 october 2012 . take the score record of this row . select the rows whose date record fuzzily matches to 8 october 2010 . take the score record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; date ; 16 october 2012 } ; score } ; hop { filter_eq { all_rows ; date ; 8 october 2010 } ; score } } = true | select the rows whose date record fuzzily matches to 16 october 2012 . take the score record of this row . select the rows whose date record fuzzily matches to 8 october 2010 . 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, 'date_7': 7, '16 october 2012_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '8 october 2010_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', 'date_7': 'date', '16 october 2012_8': '16 october 2012', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '8 october 2010_12': '8 october 2010', 'score_13': 'score'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '16 october 2012_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '8 october 2010_12': [1], 'score_13': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['7 september 2010', 'szusza stadium , budapest', '2 - 0', '2 - 1', 'uefa euro 2012 qualifying'], ['8 october 2010', 'puskás stadium , budapest', '6 - 0', '8 - 0', 'uefa euro 2012 qualifying'], ['7 june 2011', 'stadio olimpico , serravalle', '3 - 0', '3 - 0', 'uefa euro 2012 qualifying'], ['10 august 2011', 'puskás stadium , budapest', '1 - 0', '4 - 0', 'international friendly'], ['11 september 2011', 'puskás stadium , budapest', '4 - 0', '5 - 0', 'international friendly'], ['7 september 2012', 'estadi comunal , andorra la vella', '5 - 0', '5 - 0', '2014 fifa world cup qualifying'], ['16 october 2012', 'puskás stadium , budapest', '1 - 1', '3 - 1', '2014 fifa world cup qualifying']] |
miller barber | https://en.wikipedia.org/wiki/Miller_Barber | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1552405-5.html.csv | majority | across the different types of tournaments he competed in , miller barber was mostly not in the top 5 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'top - 5', '0'], 'result': True, 'ind': 0, 'tointer': 'for the top - 5 records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; top - 5 ; 0 } = true'} | most_eq { all_rows ; top - 5 ; 0 } = true | for the top - 5 records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'top - 5_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'top - 5_3': 'top - 5', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'top - 5_3': [0], '0_4': [0]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '0', '1', '6', '11', '8'], ['us open', '0', '0', '2', '7', '19', '13'], ['the open championship', '0', '0', '1', '1', '4', '2'], ['pga championship', '0', '2', '3', '6', '15', '12'], ['totals', '0', '2', '7', '20', '49', '35']] |
uk film council completion fund | https://en.wikipedia.org/wiki/UK_Film_Council_Completion_Fund | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12181447-7.html.csv | superlative | the highest award for the uk film council completion fund went to the film hotel infinity . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '9', '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', 'award'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; award }'}, 'film'], 'result': 'hotel infinity', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; award } ; film }'}, 'hotel infinity'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; award } ; film } ; hotel infinity } = true', 'tointer': 'select the row whose award record of all rows is maximum . the film record of this row is hotel infinity .'} | eq { hop { argmax { all_rows ; award } ; film } ; hotel infinity } = true | select the row whose award record of all rows is maximum . the film record of this row is hotel infinity . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'award_5': 5, 'film_6': 6, 'hotel infinity_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'award_5': 'award', 'film_6': 'film', 'hotel infinity_7': 'hotel infinity'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'award_5': [0], 'film_6': [1], 'hotel infinity_7': [2]} | ['film', 'director ( s )', 'writer ( s )', 'recipient', 'date', 'award'] | [['mercy', 'candida scott knight', 'tina walker', 'maya vision international ltd', '3 / 3 / 04', '7800'], ['no deposit , no return', 'dallas campbell', 'dallas campbell , john edwards', 'rocliffe ltd', '3 / 3 / 04', '4360'], ['6.6.04', 'simon hook', 'simon hook , jayne kirkham', 'andrew wilson', '3 / 3 / 04', '1939'], ['bushido : the way of the warrior', 'susan jacobson', 'susan jacobson , anna reeves', 'pistachio pictures ltd', '3 / 3 / 04', '3386'], ['jamaica', 'martin scanlan', 'martin scanlan', 'prussia lane productions ltd', '3 / 3 / 04', '6947'], ['flowers and coins', 'joshua neale', 'neil henry , joshua neale', 'joshua neale', '3 / 3 / 04', '3740'], ['moving on', 'albert kodagolian', 'dusan tolmac', 'albert kodagolian', '3 / 3 / 04', '6504'], ['stalin , my neighbour', 'carol morley', 'carol morley', 'cannon and morley productions ltd', '3 / 3 / 04', '5750'], ['hotel infinity', 'amanda boyle', 'amanda boyle', 'picture farm ltd', '3 / 3 / 04', '9549'], ['traffic warden', 'donald rice', 'donald rice', 'clockwork pictures ltd', '3 / 3 / 04', '6947']] |
2012 in film | https://en.wikipedia.org/wiki/2012_in_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16921964-1.html.csv | comparative | wreck - it ralph had a lower wordwide gross than the twilight saga : breaking dawn - part 2 . | {'row_1': '14', 'row_2': '6', 'col': '5', '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', 'title', 'wreck - it ralph'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to wreck - it ralph .', 'tostr': 'filter_eq { all_rows ; title ; wreck - it ralph }'}, 'worldwide gross'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; wreck - it ralph } ; worldwide gross }', 'tointer': 'select the rows whose title record fuzzily matches to wreck - it ralph . take the worldwide gross record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'the twilight saga : breaking dawn - part 2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to the twilight saga : breaking dawn - part 2 .', 'tostr': 'filter_eq { all_rows ; title ; the twilight saga : breaking dawn - part 2 }'}, 'worldwide gross'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; the twilight saga : breaking dawn - part 2 } ; worldwide gross }', 'tointer': 'select the rows whose title record fuzzily matches to the twilight saga : breaking dawn - part 2 . take the worldwide gross record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; title ; wreck - it ralph } ; worldwide gross } ; hop { filter_eq { all_rows ; title ; the twilight saga : breaking dawn - part 2 } ; worldwide gross } } = true', 'tointer': 'select the rows whose title record fuzzily matches to wreck - it ralph . take the worldwide gross record of this row . select the rows whose title record fuzzily matches to the twilight saga : breaking dawn - part 2 . take the worldwide gross record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; title ; wreck - it ralph } ; worldwide gross } ; hop { filter_eq { all_rows ; title ; the twilight saga : breaking dawn - part 2 } ; worldwide gross } } = true | select the rows whose title record fuzzily matches to wreck - it ralph . take the worldwide gross record of this row . select the rows whose title record fuzzily matches to the twilight saga : breaking dawn - part 2 . take the worldwide gross 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, 'title_7': 7, 'wreck - it ralph_8': 8, 'worldwide gross_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'the twilight saga : breaking dawn - part 2_12': 12, 'worldwide gross_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', 'title_7': 'title', 'wreck - it ralph_8': 'wreck - it ralph', 'worldwide gross_9': 'worldwide gross', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'the twilight saga : breaking dawn - part 2_12': 'the twilight saga : breaking dawn - part 2', 'worldwide gross_13': 'worldwide gross'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'wreck - it ralph_8': [0], 'worldwide gross_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'the twilight saga : breaking dawn - part 2_12': [1], 'worldwide gross_13': [3]} | ['rank', 'title', 'studio', 'director ( s )', 'worldwide gross'] | [['1', 'the avengers', 'marvel / disney', 'joss whedon', '1511757910'], ['2', 'skyfall', 'mgm / columbia pictures', 'sam mendes', '1108561013'], ['3', 'the dark knight rises', 'warner bros / legendary pictures', 'christopher nolan', '1084439099'], ['4', 'the hobbit : an unexpected journey', 'warner bros / mgm / new line', 'peter jackson', '1017003568'], ['5', 'ice age : continental drift', '20th century fox / blue sky', 'steve martino and mike thurmeier', '877244782'], ['6', 'the twilight saga : breaking dawn - part 2', 'lionsgate / summit', 'bill condon', '829224737'], ['7', 'the amazing spider - man', 'columbia pictures', 'marc webb', '752216557'], ['8', "madagascar 3 : europe 's most wanted", 'paramount / dreamworks', 'eric darnell , tom mcgrath and conrad vernon', '746921274'], ['9', 'the hunger games', 'lionsgate', 'gary ross', '691247768'], ['10', 'men in black 3', 'columbia pictures', 'barry sonnenfeld', '624026776'], ['11', 'life of pi', '20th century fox', 'ang lee', '609016565'], ['12', 'ted', 'universal pictures', 'seth macfarlane', '549368315'], ['13', 'brave', 'walt disney pictures / pixar animation studios', 'mark andrews and brenda chapman', '538983207'], ['14', 'wreck - it ralph', 'walt disney pictures', 'rich moore', '471222889'], ['15', 'les misérables', 'universal pictures', 'tom hooper', '441809770'], ['16', 'the intouchables', 'gaumont film company', 'olivier nakache and éric toledano', '426588510'], ['17', 'django unchained', 'the weinstein company / columbia pictures', 'quentin tarantino', '425368238'], ['18', 'prometheus', '20th century fox', 'ridley scott', '403354469'], ['19', 'snow white and the huntsman', 'universal pictures', 'rupert sanders', '396592829'], ['20', 'taken 2', '20th century fox', 'olivier megaton', '376141306']] |
1992 - 93 vancouver canucks season | https://en.wikipedia.org/wiki/1992%E2%80%9393_Vancouver_Canucks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11128774-6.html.csv | majority | mclean made the majority of decisions for the vancouver canucks in february 1993 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'mclean', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'decision', 'mclean'], 'result': True, 'ind': 0, 'tointer': 'for the decision records of all rows , most of them fuzzily match to mclean .', 'tostr': 'most_eq { all_rows ; decision ; mclean } = true'} | most_eq { all_rows ; decision ; mclean } = true | for the decision records of all rows , most of them fuzzily match to mclean . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'decision_3': 3, 'mclean_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'decision_3': 'decision', 'mclean_4': 'mclean'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'decision_3': [0], 'mclean_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['february 1', 'minnesota', '5 - 4', 'vancouver', 'mclean', '14830', '29 - 15 - 8'], ['february 3', 'tampa bay', '2 - 4', 'vancouver', 'whitmore', '14171', '30 - 15 - 8'], ['february 9', 'vancouver', '5 - 1', 'quebec', 'mclean', '14360', '31 - 15 - 8'], ['february 11', 'vancouver', '2 - 5', 'toronto', 'mclean', '15720', '31 - 16 - 8'], ['february 12', 'vancouver', '3 - 1', 'buffalo', 'whitmore', '16325', '32 - 16 - 8'], ['february 15', 'vancouver', '0 - 3', 'los angeles', 'mclean', '16005', '32 - 17 - 8'], ['february 18', 'philadelphia', '3 - 2', 'vancouver', 'whitmore', '16150', '32 - 18 - 8'], ['february 20', 'winnipeg', '2 - 4', 'vancouver', 'mclean', '16150', '33 - 18 - 8'], ['february 22', 'toronto', '8 - 1', 'vancouver', 'mclean', '16150', '33 - 19 - 8'], ['february 24', 'ny rangers', '4 - 5', 'vancouver', 'whitmore', '16150', '34 - 19 - 8'], ['february 26', 'vancouver', '7 - 4', 'winnipeg', 'mclean', '15398', '35 - 19 - 8']] |
hugo duarte | https://en.wikipedia.org/wiki/Hugo_Duarte | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17446996-2.html.csv | comparative | the fight that hugo duarte had against mark kerr had more rounds compared to the combat against dieusel berto . | {'row_1': '3', 'row_2': '8', 'col': '6', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'mark kerr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to mark kerr .', 'tostr': 'filter_eq { all_rows ; opponent ; mark kerr }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; mark kerr } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to mark kerr . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'dieusel berto'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to dieusel berto .', 'tostr': 'filter_eq { all_rows ; opponent ; dieusel berto }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; dieusel berto } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to dieusel berto . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; mark kerr } ; round } ; hop { filter_eq { all_rows ; opponent ; dieusel berto } ; round } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to mark kerr . take the round record of this row . select the rows whose opponent record fuzzily matches to dieusel berto . take the round record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; mark kerr } ; round } ; hop { filter_eq { all_rows ; opponent ; dieusel berto } ; round } } = true | select the rows whose opponent record fuzzily matches to mark kerr . take the round record of this row . select the rows whose opponent record fuzzily matches to dieusel berto . take the round 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, 'opponent_7': 7, 'mark kerr_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'dieusel berto_12': 12, 'round_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', 'opponent_7': 'opponent', 'mark kerr_8': 'mark kerr', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'dieusel berto_12': 'dieusel berto', 'round_13': 'round'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'mark kerr_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'dieusel berto_12': [1], 'round_13': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '6 - 3', 'bob schrijber', 'tko ( punches )', '2h2h 1 - 2 hot 2 handle', '1', '3:34', 'netherlands'], ['win', '6 - 2', 'mikhail avetisyan', 'dq ( eye gouging )', 'wvc 8 - world vale tudo championship 8', '1', '1:51', 'havana beach club , aruba'], ['loss', '5 - 2', 'mark kerr', 'tko', 'pride 4', '3', '2:32', 'tokyo , japan'], ['loss', '5 - 1', 'tank abbott', 'tko ( strikes )', 'ufc 17', '1', '0:43', 'alabama , united states'], ['win', '5 - 0', 'steve seddon', 'submission ( rear naked choke )', 'wff - world fighting federation', '1', '0:31', 'alabama , united states'], ['win', '4 - 0', 'harold howard', 'submission ( punches )', 'uvf 3 - universal vale tudo fighting 3', '1', '0:29', 'tokyo , japan'], ['win', '3 - 0', 'gerry harris', 'submission ( punches )', 'uvf 2 - universal vale tudo fighting 2', '1', '0:08', 'brazil'], ['win', '2 - 0', 'dieusel berto', 'submission ( kimura )', 'uvf 1 - universal vale tudo fighting 1', '1', '1:28', 'japan'], ['win', '1 - 0', 'marcelo raul', 'submission ( strikes )', 'gcvt 2 - gaisei challenge vale tudo 2', '1', '0:20', 'brazil']] |
1913 world wrestling championships | https://en.wikipedia.org/wiki/1913_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15980739-1.html.csv | aggregation | at the 1913 world wrestling championships , the average number of gold medals won was .8 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '.8', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; .8 } = true', 'tointer': 'the average of the gold record of all rows is .8 .'} | round_eq { avg { all_rows ; gold } ; .8 } = true | the average of the gold record of all rows is .8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '.8_5': '.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '.8_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'sweden', '2', '2', '0', '4'], ['2', 'germany', '1', '1', '3', '5'], ['3', 'russia', '1', '0', '0', '1'], ['4', 'austria', '0', '1', '0', '1'], ['5', 'bohemia', '0', '0', '1', '1'], ['total', 'total', '4', '4', '4', '12']] |
tuncay şanlı | https://en.wikipedia.org/wiki/Tuncay_%C5%9Eanl%C4%B1 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1765584-4.html.csv | count | for competitions that tuncay şanlı participated in , when the competition was uefa cup , the result was a draw two times . | {'scope': 'subset', 'criterion': 'equal', 'value': 'draw', 'result': '2', 'col': '4', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'uefa cup'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'uefa cup'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competition ; uefa cup }', 'tointer': 'select the rows whose competition record fuzzily matches to uefa cup .'}, 'result', 'draw'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose competition record fuzzily matches to uefa cup . among these rows , select the rows whose result record fuzzily matches to draw .', 'tostr': 'filter_eq { filter_eq { all_rows ; competition ; uefa cup } ; result ; draw }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; competition ; uefa cup } ; result ; draw } }', 'tointer': 'select the rows whose competition record fuzzily matches to uefa cup . among these rows , select the rows whose result record fuzzily matches to draw . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; competition ; uefa cup } ; result ; draw } } ; 2 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to uefa cup . among these rows , select the rows whose result record fuzzily matches to draw . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; competition ; uefa cup } ; result ; draw } } ; 2 } = true | select the rows whose competition record fuzzily matches to uefa cup . among these rows , select the rows whose result record fuzzily matches to draw . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'competition_6': 6, 'uefa cup_7': 7, 'result_8': 8, 'draw_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'competition_6': 'competition', 'uefa cup_7': 'uefa cup', 'result_8': 'result', 'draw_9': 'draw', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'competition_6': [0], 'uefa cup_7': [0], 'result_8': [1], 'draw_9': [1], '2_10': [3]} | ['date', 'opponent', 'score', 'result', 'competition'] | [['14 november 2002', 'panathinaikos', '1 - 4', 'loss', 'uefa cup'], ['23 september 2004', 'manchester united', '6 - 2', 'loss', 'champions league'], ['3 november 2004', 'lyon', '4 - 2', 'loss', 'champions league'], ['8 december 2004', 'manchester united', '3 - 0', 'win', 'champions league'], ['28 september 2006', 'randers', '0 - 3', 'win', 'uefa cup'], ['23 november 2006', 'palermo', '3 - 0', 'win', 'uefa cup'], ['13 december 2006', 'eintracht frankfurt', '2 - 2', 'draw', 'uefa cup'], ['14 february 2007', 'az alkmaar', '3 - 3', 'draw', 'uefa cup']] |
balloon satellite | https://en.wikipedia.org/wiki/Balloon_satellite | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2150068-1.html.csv | aggregation | the listed balloon satellites have an average mass of 56.32 kg . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '56.32 kg', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'mass ( kg )'], 'result': '56.32 kg', 'ind': 0, 'tostr': 'avg { all_rows ; mass ( kg ) }'}, '56.32 kg'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; mass ( kg ) } ; 56.32 kg } = true', 'tointer': 'the average of the mass ( kg ) record of all rows is 56.32 kg .'} | round_eq { avg { all_rows ; mass ( kg ) } ; 56.32 kg } = true | the average of the mass ( kg ) record of all rows is 56.32 kg . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'mass (kg)_4': 4, '56.32 kg_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'mass (kg)_4': 'mass ( kg )', '56.32 kg_5': '56.32 kg'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'mass (kg)_4': [0], '56.32 kg_5': [1]} | ['satellite', 'launch date ( utc )', 'decay', 'mass ( kg )', 'diameter ( m )', 'nssdc id', 'nation', 'usage'] | [['echo 1', '1960 - 08 - 12 09:36:00', '1968 - 05 - 24', '180', '30.48', '1960 - 009a', 'us', 'pcr , ado , spc , tri'], ['explorer 9', '1961 - 02 - 16 13:12:00', '1964 - 04 - 09', '36', '3.66', '1961 - 004a', 'us', 'ado'], ['explorer 19 ( ad - a )', '1963 - 12 - 19 18:43:00', '1981 - 10 - 05', '7.7', '3.66', '1963 - 053a', 'us', 'ado'], ['echo 2', '1964 - 01 - 25 13:55:00', '1969 - 06 - 07', '256', '41', '1964 - 004a', 'us', 'pcr , tri'], ['explorer 24 ( ad - b )', '1964 - 11 - 21 17:17:00', '1968 - 10 - 18', '8.6', '3.6', '1964 - 076a', 'us', 'ado'], ['pageos 1', '1966 - 06 - 24 00:14:00', '1975 - 07 - 12', '56.7', '30.48', '1966 - 056a', 'us', 'tri'], ['explorer 39 ( ad - c )', '1968 - 08 - 08 20:12:00', '1981 - 06 - 22', '9.4', '3.6', '1968 - 066a', 'us', 'ado'], ['mylar balloon', '1971 - 08 - 07 00:11:00', '1981 - 09 - 01', '0.8', '2.13', '1971 - 067f', 'us', 'ado'], ['qi qiu weixing 1', '1990 - 09 - 03 00:53:00', '1991 - 03 - 11', '4', '3', '1990 - 081b', 'prc', 'ado'], ['qi qiu weixing 2', '1990 - 09 - 03 00:53:00', '1991 - 07 - 24', '4', '2.5', '1990 - 081c', 'prc', 'ado']] |
raleigh - durham skyhawks | https://en.wikipedia.org/wiki/Raleigh%E2%80%93Durham_Skyhawks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1639689-2.html.csv | unique | the only game that kicked off at 6 pm was on sunday , april 28th . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '6:00 pm', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'kickoff', '6:00 pm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose kickoff record fuzzily matches to 6:00 pm .', 'tostr': 'filter_eq { all_rows ; kickoff ; 6:00 pm }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; kickoff ; 6:00 pm } }', 'tointer': 'select the rows whose kickoff record fuzzily matches to 6:00 pm . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'kickoff', '6:00 pm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose kickoff record fuzzily matches to 6:00 pm .', 'tostr': 'filter_eq { all_rows ; kickoff ; 6:00 pm }'}, 'date'], 'result': 'sunday , april 28', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; kickoff ; 6:00 pm } ; date }'}, 'sunday , april 28'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; kickoff ; 6:00 pm } ; date } ; sunday , april 28 }', 'tointer': 'the date record of this unqiue row is sunday , april 28 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; kickoff ; 6:00 pm } } ; eq { hop { filter_eq { all_rows ; kickoff ; 6:00 pm } ; date } ; sunday , april 28 } } = true', 'tointer': 'select the rows whose kickoff record fuzzily matches to 6:00 pm . there is only one such row in the table . the date record of this unqiue row is sunday , april 28 .'} | and { only { filter_eq { all_rows ; kickoff ; 6:00 pm } } ; eq { hop { filter_eq { all_rows ; kickoff ; 6:00 pm } ; date } ; sunday , april 28 } } = true | select the rows whose kickoff record fuzzily matches to 6:00 pm . there is only one such row in the table . the date record of this unqiue row is sunday , april 28 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'kickoff_7': 7, '6:00 pm_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'sunday , april 28_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'kickoff_7': 'kickoff', '6:00 pm_8': '6:00 pm', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'sunday , april 28_10': 'sunday , april 28'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'kickoff_7': [0], '6:00 pm_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'sunday , april 28_10': [3]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , march 23', '4:00 pm', 'sacramento surge', 'l 3 - 9', '0 - 1', 'hughes stadium', '15126'], ['2', 'saturday , march 30', '8:00 pm', 'orlando thunder', 'l 20 - 58', '0 - 2', 'florida citrus bowl', '20811'], ['3', 'saturday , april 6', '8:00 pm', 'barcelona dragons', 'l 14 - 26', '0 - 3', 'carter - finley stadium', '17900'], ['4', 'monday , april 15', '8:00 pm', 'san antonio riders', 'l 15 - 37', '0 - 4', 'carter - finley stadium', '11818'], ['5', 'saturday , april 20', '8:00 pm', 'frankfurt galaxy', 'l 28 - 30', '0 - 5', 'waldstadion', '21065'], ['6', 'sunday , april 28', '6:00 pm', 'london monarchs', 'l 10 - 35', '0 - 6', 'wembley stadium', '33997'], ['7', 'sunday , may 5', '1:00 pm', 'new york / new jersey knights', 'l 6 - 42', '0 - 7', 'carter - finley stadium', '10069'], ['8', 'monday , may 13', '8:00 pm', 'montreal machine', 'l 6 - 15', '0 - 8', 'olympic stadium', '20123'], ['9', 'monday , may 20', '8:00 pm', 'orlando thunder', 'l 14 - 20', '0 - 9', 'carter - finley stadium', '4207']] |
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