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1948 vfl season | https://en.wikipedia.org/wiki/1948_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809529-12.html.csv | ordinal | victoria park venue recorded the 2nd highest crowd participation during the 1948 vfl season . | {'row': '3', 'col': '6', 'order': '2', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'venue'], 'result': 'victoria park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; venue }'}, 'victoria park'],... | eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; victoria park } = true | select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is victoria park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'venue_7': 7, 'victoria park_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '2_6': '2', 'venue_7': 'venue', 'victoria park_8': 'victoria park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'venue_7': [1], 'victoria park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '21.18 ( 144 )', 'south melbourne', '9.13 ( 67 )', 'punt road oval', '21000', '10 july 1948'], ['essendon', '13.13 ( 91 )', 'melbourne', '9.11 ( 65 )', 'windy hill', '17000', '10 july 1948'], ['collingwood', '19.13 ( 127 )', 'north melbourne', '10.11 ( 71 )', 'victoria park', '19500', '10 july 1948'], ['c... |
2007 - 08 commonwealth bank series statistics | https://en.wikipedia.org/wiki/2007%E2%80%9308_Commonwealth_Bank_Series_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15700367-5.html.csv | aggregation | the fourteen players that competed in the 2007-2008 commonwealth bank series scored a combined total of 1,097 runs . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '1,097', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'runs scored'], 'result': '1,097', 'ind': 0, 'tostr': 'sum { all_rows ; runs scored }'}, '1,097'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; runs scored } ; 1,097 } = true', 'tointer': 'the sum of the runs scored record of all rows... | round_eq { sum { all_rows ; runs scored } ; 1,097 } = true | the sum of the runs scored record of all rows is 1,097 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'runs scored_4': 4, '1,097_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'runs scored_4': 'runs scored', '1,097_5': '1,097'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'runs scored_4': [0], '1,097_5': [1]} | ['name', 'innings', 'runs scored', 'balls faced', 'average', 'sr'] | [['upul tharanga', '1', '10', '18', '10.00', '55.56'], ['sanath jayasuriya', '7', '103', '116', '14.71', '88.79'], ['kumar sangakkara ( wk )', '7', '326', '448', '46.57', '72.77'], ['mahela jayawardene ( c )', '7', '214', '297', '35.67', '72.05'], ['chamara silva', '6', '80', '171', '16.00', '46.78'], ['tillakaratne di... |
fundraising for the 2008 united states presidential election | https://en.wikipedia.org/wiki/Fundraising_for_the_2008_United_States_presidential_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12030247-2.html.csv | majority | most of the candidates of the 2008 united states presidential election received loans . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '0', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'loans received', '0'], 'result': True, 'ind': 0, 'tointer': 'for the loans received records of all rows , most of them are greater than 0 .', 'tostr': 'most_greater { all_rows ; loans received ; 0 } = true'} | most_greater { all_rows ; loans received ; 0 } = true | for the loans received records of all rows , most of them are greater than 0 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'loans received_3': 3, '0_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'loans received_3': 'loans received', '0_4': '0'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'loans received_3': [0], '0_4': [0]} | ['candidate', 'contributions', 'loans received', 'all receipts', 'operating expenditures', 'all disbursements'] | [['hillary clinton', '107056586', '0', '118301659', '77804197', '106000000'], ['barack obama', '102092819', '0', '103802537', '84497445', '85176289'], ['john edwards', '34986088', '8974714', '44259386', '33513005', '36468929'], ['bill richardson', '22421742', '1000000', '23671031', '21401414', '21857565'], ['chris dodd... |
1987 pittsburgh gladiators season | https://en.wikipedia.org/wiki/1987_Pittsburgh_Gladiators_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11938731-7.html.csv | aggregation | the players on the pittsburgh gladiators recorded a total of 153 solo tackles during the 1987 season . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '153', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'solo'], 'result': '153', 'ind': 0, 'tostr': 'sum { all_rows ; solo }'}, '153'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; solo } ; 153 } = true', 'tointer': 'the sum of the solo record of all rows is 153 .'} | round_eq { sum { all_rows ; solo } ; 153 } = true | the sum of the solo record of all rows is 153 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'solo_4': 4, '153_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'solo_4': 'solo', '153_5': '153'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'solo_4': [0], '153_5': [1]} | ['player', 'tackles', 'solo', 'assisted', 'sack', 'yards', "td 's"] | [['joel gueli', '31', '29', '4', '3', '31', '1'], ['craig walls', '19', '15', '8', '13', '0', '0'], ['russell hairston', '17.5', '16', '0', '0', '50', '1'], ['creig federico', '17', '12', '10', '3', '0', '0'], ['scott dmitrenko', '15', '13', '4', '3', '0', '0'], ['mike stoops', '14.5', '11', '7', '0', '0', '0'], ['john... |
1965 vfl season | https://en.wikipedia.org/wiki/1965_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10788451-14.html.csv | comparative | the south melbourne club scored more points than the north melbourne club . | {'row_1': '3', 'row_2': '1', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'south melbourne'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away team record fuzzily matches to south melbourne .', 'tostr': 'filter_eq { all_rows ; away team ; south melbourne }'}, ... | greater { hop { filter_eq { all_rows ; away team ; south melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; north melbourne } ; away team score } } = true | select the rows whose away team record fuzzily matches to south melbourne . take the away team score record of this row . select the rows whose away team record fuzzily matches to north melbourne . take the away team score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'away team_7': 7, 'south melbourne_8': 8, 'away team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'away team_11': 11, 'north melbourne_12': 12, 'away team score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'away team_7': 'away team', 'south melbourne_8': 'south melbourne', 'away team score_9': 'away team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_r... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'away team_7': [0], 'south melbourne_8': [0], 'away team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'away team_11': [1], 'north melbourne_12': [1], 'away team score_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '10.17 ( 77 )', 'north melbourne', '5.4 ( 34 )', 'kardinia park', '19658', '31 july 1965'], ['essendon', '13.18 ( 96 )', 'footscray', '6.11 ( 47 )', 'windy hill', '16800', '31 july 1965'], ['carlton', '9.19 ( 73 )', 'south melbourne', '13.12 ( 90 )', 'princes park', '20744', '31 july 1965'], ['st kilda', '... |
list of earthquakes in iran | https://en.wikipedia.org/wiki/List_of_earthquakes_in_Iran | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10677198-2.html.csv | count | there are 2 recorded earthquakes that occurred in iran for the year 1997 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '1997', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1997'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 1997 .', 'tostr': 'filter_eq { all_rows ; date ; 1997 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq {... | eq { count { filter_eq { all_rows ; date ; 1997 } } ; 2 } = true | select the rows whose date record fuzzily matches to 1997 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '1997_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '1997_6': '1997', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '1997_6': [0], '2_7': [2]} | ['date', 'epicenter', 'magnitude', 'fatalities', 'name'] | [['march 14 , 1998', 'golbaf', '6.6', '5', '1998 golbaf earthquake'], ['may 10 , 1997', 'birjand - qaen', '7.3', '1567', '1997 qayen earthquake'], ['february 28 , 1997', 'ardabil', '6.0', '1100', '1997 ardabil earthquake'], ['june 20 , 1990', 'manjil ( - rudbar )', '7.4', 'least 40000', '1990 manjil - rudbar earthquake... |
atlanta falcons draft history | https://en.wikipedia.org/wiki/Atlanta_Falcons_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-45.html.csv | count | three of these players were the 19th pick for their team . | {'scope': 'all', 'criterion': 'equal', 'value': '19', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'pick', '19'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pick record is equal to 19 .', 'tostr': 'filter_eq { all_rows ; pick ; 19 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; pick ... | eq { count { filter_eq { all_rows ; pick ; 19 } } ; 3 } = true | select the rows whose pick record is equal to 19 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'pick_5': 5, '19_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'pick_5': 'pick', '19_6': '19', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'pick_5': [0], '19_6': [0], '3_7': [2]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '19', '19', 'sean weatherspoon', 'linebacker', 'missouri'], ['3', '19', '83', 'corey peters', 'defensive tackle', 'kentucky'], ['3', '34', '98', 'mike johnson', 'guard', 'alabama'], ['4', '19', '117', 'joe hawley', 'guard', 'unlv'], ['5', '4', '135', 'dominique franks', 'cornerback', 'oklahoma'], ['5', '34', '16... |
european poker tour | https://en.wikipedia.org/wiki/European_Poker_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1296513-5.html.csv | ordinal | the 2008 european poker championships was the second earliest event . | {'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', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'event'], 'result': '2008 european poker championships', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; event }'}, ... | eq { hop { nth_argmin { all_rows ; date ; 2 } ; event } ; 2008 european poker championships } = true | select the row whose date record of all rows is 2nd minimum . the event record of this row is 2008 european poker championships . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'event_7': 7, '2008 european poker championships_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'event_7': 'event', '2008 european poker championships_8': '2008 european poker championships'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'event_7': [1], '2008 european poker championships_8': [2]} | ['date', 'city', 'event', 'winner', 'prize'] | [['10 - 14 september 2008', 'barcelona', 'ept barcelona open', 'sebastian ruthenberg', '1361000'], ['1 - 5 october 2008', 'london', '2008 european poker championships', 'michael martin', '1000000'], ['5 - 6 october 2008', 'london', 'ept london 1 million showdown', 'jason mercier', '516000'], ['28 oct - 1 nov 2008', 'bu... |
1979 - 80 philadelphia flyers season | https://en.wikipedia.org/wiki/1979%E2%80%9380_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208862-4.html.csv | unique | in the 1979 - 80 philadelphia flyers season , the only game with attendance under 10,000 was on december 26th . | {'scope': 'all', 'row': '12', 'col': '6', 'col_other': '1', 'criterion': 'less_than', 'value': '10000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 10000 .', 'tostr': 'filter_less { all_rows ; attendance ; 10000 }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_less { all_rows ; attendance ; 10000 } } ; eq { hop { filter_less { all_rows ; attendance ; 10000 } ; date } ; december 26 } } = true | select the rows whose attendance record is less than 10000 . there is only one such row in the table . the date record of this unqiue row is december 26 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'attendance_7': 7, '10000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'december 26_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'attendance_7': 'attendance', '10000_8': '10000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'december 26_10': 'december 26'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'attendance_7': [0], '10000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'december 26_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 1', 'philadelphia', '4 - 4', 'toronto', 'myre', '16485', '17 - 1 - 4'], ['december 2', 'detroit', '4 - 4', 'philadelphia', 'peeters', '17077', '17 - 1 - 5'], ['december 4', 'boston', '2 - 2', 'philadelphia', 'myre', '17077', '17 - 1 - 6'], ['december 6', 'los angeles', '4 - 9', 'philadelphia', 'peeters', '1... |
miami valley conference | https://en.wikipedia.org/wiki/Miami_Valley_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13456202-1.html.csv | count | two of the schools in the miami valley conference have a private christian affiliation . | {'scope': 'all', 'criterion': 'equal', 'value': 'private christian', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'affiliation', 'private christian'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose affiliation record fuzzily matches to private christian .', 'tostr': 'filter_eq { all_rows ; affiliation ; private christian ... | eq { count { filter_eq { all_rows ; affiliation ; private christian } } ; 2 } = true | select the rows whose affiliation record fuzzily matches to private christian . 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, 'affiliation_5': 5, 'private christian_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', 'affiliation_5': 'affiliation', 'private christian_6': 'private christian', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'affiliation_5': [0], 'private christian_6': [0], '2_7': [2]} | ['school', 'location', 'founded', 'affiliation', 'mascot', 'division'] | [['cincinnati country day school', 'cincinnati , ohio', '1926', 'private', 'indians', 'gray'], ['cincinnati christian schools', 'fairfield , ohio', '1989', 'private christian', 'cougars', 'gray'], ['cincinnati hills christian academy', 'cincinnati , ohio', '1989', 'private christian', 'eagles', 'scarlet'], ['lockland h... |
list of formula one driver records | https://en.wikipedia.org/wiki/List_of_Formula_One_driver_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13599687-60.html.csv | aggregation | the drivers combined earned a total of 1,357 points . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '1,357', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '1,357', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '1,357'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 1,357 } = true', 'tointer': 'the sum of the points record of all rows is 1,357 .'} | round_eq { sum { all_rows ; points } ; 1,357 } = true | the sum of the points record of all rows is 1,357 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '1,357_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '1,357_5': '1,357'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '1,357_5': [1]} | ['driver', 'points', 'season', 'races', 'percentage of possible points'] | [['michael schumacher', '148', '2004', '18', '82.22 %'], ['michael schumacher', '144', '2002', '17', '84.71 %'], ['fernando alonso', '134', '2006', '18', '74.44 %'], ['fernando alonso', '133', '2005', '19', '70.00 %'], ['michael schumacher', '123', '2001', '17', '72.36 %'], ['michael schumacher', '121', '2006', '18', '... |
list of state leaders in 860s bc | https://en.wikipedia.org/wiki/List_of_state_leaders_in_860s_BC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17337639-10.html.csv | unique | the state of qi is the only one belonging to the royal house of jiang . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'jiang', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'royal house', 'jiang'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose royal house record fuzzily matches to jiang .', 'tostr': 'filter_eq { all_rows ; royal house ; jiang }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; royal house ; jiang } } ; eq { hop { filter_eq { all_rows ; royal house ; jiang } ; state } ; qi } } = true | select the rows whose royal house record fuzzily matches to jiang . there is only one such row in the table . the state record of this unqiue row is qi . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'royal house_7': 7, 'jiang_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'state_9': 9, 'qi_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'royal house_7': 'royal house', 'jiang_8': 'jiang', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'state_9': 'state', 'qi_10': 'qi'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'royal house_7': [0], 'jiang_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'state_9': [2], 'qi_10': [3]} | ['state', 'type', 'name', 'title', 'royal house'] | [['cai', 'sovereign', 'li', 'marquis', 'ji'], ['cai', 'sovereign', 'wu', 'marquis', 'ji'], ['cao', 'sovereign', 'xiao', 'count', '-'], ['cao', 'sovereign', 'yi', 'count', '-'], ['lu', 'sovereign', 'xian', 'duke', 'ji'], ['qi', 'sovereign', 'ai', 'duke', 'jiang'], ['qin', 'sovereign', 'feizi', 'ruler', 'ying'], ['wey', ... |
1953 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1953_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17290169-1.html.csv | aggregation | the players have a score aggregation of 71 points in 1953 u.s golf opens . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '71', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '71', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '71'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 71 } = true', 'tointer': 'the average of the score record of all rows is 71 .'} | round_eq { avg { all_rows ; score } ; 71 } = true | the average of the score record of all rows is 71 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '71_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '71_5': '71'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '71_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'ben hogan', 'united states', '67', '- 5'], ['t2', 'walter burkemo', 'united states', '70', '- 2'], ['t2', 'george fazio', 'united states', '70', '- 2'], ['t2', 'frank souchak ( a )', 'united states', '70', '- 2'], ['t5', 'jimmy demaret', 'united states', '71', '- 1'], ['t5', 'bill ogden', 'united states', '71',... |
2008 - 09 fa cup | https://en.wikipedia.org/wiki/2008%E2%80%9309_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17814838-1.html.csv | aggregation | the prize money of the september rounds of the 2008-09 fa cup was 7500 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '7500', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'september'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'main date', 'september'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; main date ; september }', 'tointer': 'select the rows whose main date record fuzzily matches to september .'}, 'prize money'], 'resu... | round_eq { sum { filter_eq { all_rows ; main date ; september } ; prize money } ; 7500 } = true | select the rows whose main date record fuzzily matches to september . the sum of the prize money record of these rows is 7500 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'main date_5': 5, 'september_6': 6, 'prize money_7': 7, '7500_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'main date_5': 'main date', 'september_6': 'september', 'prize money_7': 'prize money', '7500_8': '7500'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'main date_5': [0], 'september_6': [0], 'prize money_7': [1], '7500_8': [2]} | ['round', 'main date', 'number of fixtures', 'clubs', 'new entries this round', 'prize money', 'player of the round'] | [['extra preliminary round', '16 august 2008', '203', '761 → 558', '406 : 356th - 761st', '750', 'n / a'], ['preliminary round', '30 august 2008', '166', '558 → 392', '129 : 227th - 355th', '1500', 'n / a'], ['first round qualifying', '13 september 2008', '116', '392 → 276', '66 : 161st - 226th', '3000', 'derren ibrahi... |
pete sampras career statistics | https://en.wikipedia.org/wiki/Pete_Sampras_career_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22834834-2.html.csv | count | pete samparas was winner four out of five times from 1991-1997 . | {'scope': 'all', 'criterion': 'equal', 'value': 'winner', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose outcome record fuzzily matches to winner .', 'tostr': 'filter_eq { all_rows ; outcome ; winner }'}], 'result': '4', 'ind': 1, 'tostr': 'coun... | eq { count { filter_eq { all_rows ; outcome ; winner } } ; 4 } = true | select the rows whose outcome record fuzzily matches to winner . 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, 'outcome_5': 5, 'winner_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', 'outcome_5': 'outcome', 'winner_6': 'winner', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'outcome_5': [0], 'winner_6': [0], '4_7': [2]} | ['outcome', 'year', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['winner', '1991', 'frankfurt', 'carpet ( i )', 'jim courier', '3 - 6 , 7 - 6 ( 7 - 5 ) , 6 - 3 , 6 - 4'], ['runner - up', '1993', 'frankfurt', 'carpet ( i )', 'michael stich', '6 - 7 ( 3 - 7 ) , 6 - 2 , 6 - 7 ( 7 - 9 ) , 2 - 6'], ['winner', '1994', 'frankfurt', 'carpet ( i )', 'boris becker', '4 - 6 , 6 - 3 , 7 - 5 ,... |
the sunday night project | https://en.wikipedia.org/wiki/The_Sunday_Night_Project | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1590967-3.html.csv | superlative | in the sunday night project , the episode with the most recent air date was the episode where cheryl cole , kimberley walsh and sarah harding hosted . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '11', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'air date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; air date }'}, 'guest host'], 'result': 'cheryl cole , kimberley walsh and sarah harding', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; air date } ; guest... | eq { hop { argmax { all_rows ; air date } ; guest host } ; cheryl cole , kimberley walsh and sarah harding } = true | select the row whose air date record of all rows is maximum . the guest host record of this row is cheryl cole , kimberley walsh and sarah harding . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'air date_5': 5, 'guest host_6': 6, 'cheryl cole , kimberley walsh and sarah harding_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'air date_5': 'air date', 'guest host_6': 'guest host', 'cheryl cole , kimberley walsh and sarah harding_7': 'cheryl cole , kimberley walsh and sarah harding'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'air date_5': [0], 'guest host_6': [1], 'cheryl cole , kimberley walsh and sarah harding_7': [2]} | ['episode number', 'air date', 'guest host', 'musical guest ( song performed )', 'who knows the most about the guest host panelists'] | [['1', '16 june 2006', 'jerry springer', 'orson ( bright idea )', 'zãe lucker and sam brodie'], ['2', '23 june 2006', 'patsy kensit', 'placebo ( infra - red )', 'jeremy edwards and grace adams - short'], ['3', '30 june 2006', 'rob lowe', 'the zutons ( valerie )', 'jennifer ellison and kirsty gallacher'], ['4', '7 july ... |
united states house of representatives elections , 1964 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1964 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341865-37.html.csv | count | in the united states house of representatives election in 1964 , for those that were re-elected , two of the incumbents were first elected in 1960 . | {'scope': 'subset', 'criterion': 'equal', 'value': '1960', 'result': '2', 'col': '4', 'subset': {'col': '5', 'criterion': 'equal', 'value': 're - elected'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; re - elected }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected... | eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; first elected ; 1960 } } ; 2 } = true | select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose first elected record is equal to 1960 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'result_6': 6, 're - elected_7': 7, 'first elected_8': 8, '1960_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'result_6': 'result', 're - elected_7': 're - elected', 'first elected_8': 'first elected', '1960_9': '1960', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'result_6': [0], 're - elected_7': [0], 'first elected_8': [1], '1960_9': [1], '2_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['ohio 1', 'carl w rich', 'republican', '1962', 'lost re - election democratic gain', 'john j gilligan ( d ) 51.9 % carl w rich ( r ) 48.1 %'], ['ohio 2', 'donald d clancy', 'republican', '1960', 're - elected', 'donald d clancy ( r ) 60.5 % h a sand ( d ) 39.5 %'], ['ohio 3', 'paul f schenck', 'republican', '1951', '... |
united states house of representatives elections , 1942 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1942 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342256-5.html.csv | majority | all of the arkansas incumbents in the 1942 united states house of representatives elections were with the democratic party . | {'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'] | [['arkansas 1', 'ezekiel c gathings', 'democratic', '1938', 're - elected', 'ezekiel c gathings ( d ) unopposed'], ['arkansas 2', 'wilbur mills', 'democratic', '1938', 're - elected', 'wilbur mills ( d ) unopposed'], ['arkansas 3', 'clyde t ellis', 'democratic', '1938', 'retired to run for u s senate democratic hold', ... |
naia independent football schools | https://en.wikipedia.org/wiki/NAIA_independent_football_schools | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15617076-1.html.csv | unique | haskell indian nations university is the only tribal institution among the naia independent football schools . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '4', 'criterion': 'equal', 'value': 'tribal', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'tribal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose type record fuzzily matches to tribal .', 'tostr': 'filter_eq { all_rows ; type ; tribal }'}], 'result': True, 'ind': 1, 'tostr': 'only { filte... | and { only { filter_eq { all_rows ; type ; tribal } } ; eq { hop { filter_eq { all_rows ; type ; tribal } ; type } ; tribal } } = true | select the rows whose type record fuzzily matches to tribal . there is only one such row in the table . the type record of this unqiue row is tribal . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'type_7': 7, 'tribal_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'type_9': 9, 'tribal_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'type_7': 'type', 'tribal_8': 'tribal', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'type_9': 'type', 'tribal_10': 'tribal'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'type_7': [0], 'tribal_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'type_9': [2], 'tribal_10': [3]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'team', 'primary conference'] | [['ave maria university', 'ave maria , florida', '1998', 'private', '1200', 'gyrenes', 'the sun'], ['dakota state university', 'madison , south dakota', '1881', 'public', '3102', 'trojans', 'none'], ['edward waters college', 'jacksonville , florida', '1866', 'private', '800', 'tigers', 'gulf coast ( gcac )'], ['haskell... |
ai sugiyama | https://en.wikipedia.org/wiki/Ai_Sugiyama | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1514559-1.html.csv | aggregation | ai sugiyama 's average score in the finals is six points . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score in the final'], 'result': '6', 'ind': 0, 'tostr': 'avg { all_rows ; score in the final }'}, '6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score in the final } ; 6 } = true', 'tointer': 'the average of the score in the fina... | round_eq { avg { all_rows ; score in the final } ; 6 } = true | the average of the score in the final record of all rows is 6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score in the final_4': 4, '6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score in the final_4': 'score in the final', '6_5': '6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score in the final_4': [0], '6_5': [1]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['runner - up', '2000', 'wimbledon', 'grass', 'julie halard', 'serena williams venus williams', '6 - 3 , 6 - 2'], ['winner', '2000', 'us open', 'hard', 'julie halard', 'cara black elena likhovtseva', '6 - 0 , 1 - 6 , 6 - 1'], ['runner - up', '2001', 'wimbledon ( 2 )', 'grass', 'kim clijsters', 'lisa raymond rennae stu... |
hubert hahne | https://en.wikipedia.org/wiki/Hubert_Hahne | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1233847-1.html.csv | unique | 1966 is the only year that hubert hahne drove for the tyrrell racing organisation . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'tyrrell racing organisation', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'entrant', 'tyrrell racing organisation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose entrant record fuzzily matches to tyrrell racing organisation .', 'tostr': 'filter_eq { all_rows ; entrant ; tyrrell ra... | and { only { filter_eq { all_rows ; entrant ; tyrrell racing organisation } } ; eq { hop { filter_eq { all_rows ; entrant ; tyrrell racing organisation } ; year } ; 1966 } } = true | select the rows whose entrant record fuzzily matches to tyrrell racing organisation . there is only one such row in the table . the year record of this unqiue row is 1966 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'entrant_7': 7, 'tyrrell racing organisation_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1966_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'entrant_7': 'entrant', 'tyrrell racing organisation_8': 'tyrrell racing organisation', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1966_10': '1966'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'entrant_7': [0], 'tyrrell racing organisation_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1966_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1966', 'tyrrell racing organisation', 'matra ms5 ( f2 )', 'brm straight - 4', '0'], ['1967', 'bayerische motoren werke', 'lola t100', 'bmw straight - 4', '0'], ['1968', 'bayerische motoren werke', 'lola t100', 'bmw straight - 4', '0'], ['1969', 'bayerische motoren werke', 'bmw t269 ( f2 )', 'bmw straight - 4', '0'],... |
1988 - 89 argentine primera división | https://en.wikipedia.org/wiki/1988%E2%80%9389_Argentine_Primera_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17968265-1.html.csv | count | two of the teams finished with 130 points . | {'scope': 'all', 'criterion': 'equal', 'value': '130', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '130'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 130 .', 'tostr': 'filter_eq { all_rows ; points ; 130 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_row... | eq { count { filter_eq { all_rows ; points ; 130 } } ; 2 } = true | select the rows whose points record is equal to 130 . 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, 'points_5': 5, '130_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'points_5': 'points', '130_6': '130', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'points_5': [0], '130_6': [0], '2_7': [2]} | ['team', 'average', 'points', 'played', '1986 - 87', '1987 - 88', '1988 - 89'] | [['independiente', '1.219', '139', '114', '47', '37', '55'], ["newell 's old boys", '1.193', '136', '114', '48', '55', '33'], ['san lorenzo', '1.184', '135', '114', '44', '49', '42'], ['racing club', '1.158', '132', '114', '44', '48', '40'], ['boca juniors', '1.140', '130', '114', '46', '35', '49'], ['river plate', '1.... |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-10.html.csv | superlative | georgia district 1 had the highest number of competing candidates in the united states house of representatives elections of 1954 . | {'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', 'candidates'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; candidates }'}, 'district'], 'result': 'georgia 1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; candidates } ; district }'}, 'georgia 1'], 'result': T... | eq { hop { argmax { all_rows ; candidates } ; district } ; georgia 1 } = true | select the row whose candidates record of all rows is maximum . the district record of this row is georgia 1 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, 'district_6': 6, 'georgia 1_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', 'district_6': 'district', 'georgia 1_7': 'georgia 1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], 'district_6': [1], 'georgia 1_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['georgia 1', 'prince hulon preston , jr', 'democratic', '1946', 're - elected', 'prince hulon preston , jr ( d ) 83.7 % others 16.3 %'], ['georgia 2', 'j l pilcher', 'democratic', '1953', 're - elected', 'j l pilcher ( d ) unopposed'], ['georgia 3', 'tic forrester', 'democratic', '1950', 're - elected', 'tic forreste... |
tiffany joh | https://en.wikipedia.org/wiki/Tiffany_Joh | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15870501-2.html.csv | ordinal | from 2007 - 2012 , tiffany joh 's third lowest scoring average was in 2011 . | {'row': '4', 'col': '7', 'order': '3', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'scoring average', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; scoring average ; 3 }'}, 'year'], 'result': '2011', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; scoring average ; 3 } ; year }'}, '2... | eq { hop { nth_argmin { all_rows ; scoring average ; 3 } ; year } ; 2011 } = true | select the row whose scoring average record of all rows is 3rd minimum . the year record of this row is 2011 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'scoring average_5': 5, '3_6': 6, 'year_7': 7, '2011_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'scoring average_5': 'scoring average', '3_6': '3', 'year_7': 'year', '2011_8': '2011'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'scoring average_5': [0], '3_6': [0], 'year_7': [1], '2011_8': [2]} | ['year', 'tournaments played', 'cuts made', 'wins', 'best finish', 'earnings', 'scoring average'] | [['2007', '1', '1', '0', 't22', 'n / a', '71.66'], ['2009', '1', '1', '0', 't21', 'n / a', '72.50'], ['2010', '2', '0', '0', 'mc', '0', '79.00'], ['2011', '14', '12', '0', '2', '237365', '72.75'], ['2012', '20', '10', '0', 't33', '48695', '74.09']] |
list of european cup and uefa champions league winning managers | https://en.wikipedia.org/wiki/List_of_European_Cup_and_UEFA_Champions_League_winning_managers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15205941-2.html.csv | majority | the majority of european cup and uefa champions league winning managers have 0 runner-up positions . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'runner - up', '0'], 'result': True, 'ind': 0, 'tointer': 'for the runner - up records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; runner - up ; 0 } = true'} | most_eq { all_rows ; runner - up ; 0 } = true | for the runner - up records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'runner - up_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'runner - up_3': 'runner - up', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'runner - up_3': [0], '0_4': [0]} | ['rank', 'manager', 'runner - up', 'years won', 'clubs won'] | [['1', 'bob paisley', '0', '1977 , 1978 , 1981', 'liverpool'], ['2', 'alex ferguson', '2', '1999 , 2008', 'manchester united'], ['2', 'miguel muñoz', '2', '1960 , 1966', 'real madrid'], ['4', 'jupp heynckes', '1', '1998 , 2013', 'real madrid , bayern munich'], ['4', 'carlo ancelotti', '1', '2003 , 2007', 'milan'], ['4'... |
nick park | https://en.wikipedia.org/wiki/Nick_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-149052-1.html.csv | comparative | chicken run was released after creature comforts was released . | {'row_1': '5', 'row_2': '1', 'col': '1', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'chicken run'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to chicken run .', 'tostr': 'filter_eq { all_rows ; title ; chicken run }'}, 'year'], 'result': None,... | greater { hop { filter_eq { all_rows ; title ; chicken run } ; year } ; hop { filter_eq { all_rows ; title ; creature comforts } ; year } } = true | select the rows whose title record fuzzily matches to chicken run . take the year record of this row . select the rows whose title record fuzzily matches to creature comforts . take the year 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, 'title_7': 7, 'chicken run_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'creature comforts_12': 12, 'year_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', 'title_7': 'title', 'chicken run_8': 'chicken run', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'creature c... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'chicken run_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'creature comforts_12': [1], 'year_13': [3]} | ['year', 'title', 'director', 'writer', 'notes'] | [['1989', 'creature comforts', 'yes', 'yes', 'short film'], ['1989', 'wallace & gromit : a grand day out', 'yes', 'yes', 'short film'], ['1993', 'wallace & gromit : the wrong trousers', 'yes', 'yes', 'short film'], ['1995', 'wallace & gromit : a close shave', 'yes', 'yes', 'short film'], ['2000', 'chicken run', 'yes', ... |
1981 denver broncos season | https://en.wikipedia.org/wiki/1981_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17972136-1.html.csv | comparative | game attendance was higher on september 6 than on november 22 . | {'row_1': '1', 'row_2': '12', 'col': '7', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'september 6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to september 6 .', 'tostr': 'filter_eq { all_rows ; date ; september 6 }'}, 'attendance'], 'result': No... | greater { hop { filter_eq { all_rows ; date ; september 6 } ; attendance } ; hop { filter_eq { all_rows ; date ; november 22 } ; attendance } } = true | select the rows whose date record fuzzily matches to september 6 . take the attendance record of this row . select the rows whose date record fuzzily matches to november 22 . take the attendance 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, 'date_7': 7, 'september 6_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'november 22_12': 12, 'attendance_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', 'date_7': 'date', 'september 6_8': 'september 6', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'no... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'september 6_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'november 22_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 6', 'oakland raiders', 'w 9 - 7', 'mile high stadium', '1 - 0', '74796'], ['2', 'september 13', 'seattle seahawks', 'l 10 - 13', 'kingdome', '1 - 1', '58513'], ['3', 'september 20', 'baltimore colts', 'w 28 - 10', 'mile high stadium', '2 - 1', '74804'], ['4', 'september 27', 'san diego chargers', 'w 4... |
1975 england rugby union tour of australia | https://en.wikipedia.org/wiki/1975_England_rugby_union_tour_of_Australia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17004899-1.html.csv | aggregation | the opposing teams scored a total of 119 against england in the 1975 england rugby union tour of australia . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '119', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'against'], 'result': '119', 'ind': 0, 'tostr': 'sum { all_rows ; against }'}, '119'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; against } ; 119 } = true', 'tointer': 'the sum of the against record of all rows is 119 .'} | round_eq { sum { all_rows ; against } ; 119 } = true | the sum of the against record of all rows is 119 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'against_4': 4, '119_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'against_4': 'against', '119_5': '119'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'against_4': [0], '119_5': [1]} | ['opposing team', 'against', 'date', 'venue', 'status'] | [['western australia', '12', '10 / 05 / 1975', 'perry lakes stadium , perth', 'tour match'], ['sydney', '14', '13 / 05 / 1975', 'sydney cricket ground , sydney', 'tour match'], ['new south wales', '24', '17 / 05 / 1975', 'sydney sports ground , sydney', 'tour match'], ['new south wales country xv', '14', '20 / 05 / 197... |
paul caligiuri | https://en.wikipedia.org/wiki/Paul_Caligiuri | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1036039-1.html.csv | unique | of all of paul caligiuri 's competitions , the only one in italy was on june 10 , 1990 . | {'scope': 'all', 'row': '4', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'italy', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; venue ; italy }'}], 'result': True, 'ind': 1, 'tostr': 'only { filte... | and { only { filter_eq { all_rows ; venue ; italy } } ; eq { hop { filter_eq { all_rows ; venue ; italy } ; date } ; june 10 , 1990 } } = true | select the rows whose venue record fuzzily matches to italy . there is only one such row in the table . the date record of this unqiue row is june 10 , 1990 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'italy_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'june 10 , 1990_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'italy_8': 'italy', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'june 10 , 1990_10': 'june 10 , 1990'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'italy_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'june 10 , 1990_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['may 19 , 1985', 'torrance , california', '1 - 0', '1 - 0', '1986 world cup qualifying'], ['november 19 , 1989', 'port of spain , trinidad and tobago', '1 - 0', '1 - 0', '1990 world cup qualifying'], ['march 10 , 1990', 'tampa , florida', '1 - 0', '2 - 1', 'friendly'], ['june 10 , 1990', 'florence , italy', '1 - 3', ... |
2011 the dominion tankard | https://en.wikipedia.org/wiki/2011_The_Dominion_Tankard | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29565601-2.html.csv | unique | in the dominion tankard in 2011 , the only one with over 15 stolen ends was chris gardner . | {'scope': 'all', 'row': '6', 'col': '9', 'col_other': '1', 'criterion': 'greater_than', 'value': '15', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'stolen ends', '15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose stolen ends record is greater than 15 .', 'tostr': 'filter_greater { all_rows ; stolen ends ; 15 }'}], 'result': True, 'ind': 1, 'tostr': '... | and { only { filter_greater { all_rows ; stolen ends ; 15 } } ; eq { hop { filter_greater { all_rows ; stolen ends ; 15 } ; skip ( club ) } ; chris gardner ( renfrew ) } } = true | select the rows whose stolen ends record is greater than 15 . there is only one such row in the table . the skip ( club ) record of this unqiue row is chris gardner ( renfrew ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'stolen ends_7': 7, '15_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'skip (club)_9': 9, 'chris gardner (renfrew)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'stolen ends_7': 'stolen ends', '15_8': '15', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'skip (club)_9': 'skip ( club )', 'chris gardner (renfrew)_10': 'chris gardner ( renfrew )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'stolen ends_7': [0], '15_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'skip (club)_9': [2], 'chris gardner (renfrew)_10': [3]} | ['skip ( club )', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends'] | [['peter corner ( brampton )', '8', '2', '69', '54', '41', '36', '8', '11'], ['glenn howard ( coldwater )', '8', '2', '79', '35', '40', '22', '8', '11'], ['greg balsdon ( loonie )', '7', '3', '80', '57', '46', '37', '5', '12'], ['john epping ( donalda )', '7', '3', '76', '64', '43', '41', '5', '10'], ['mark bice ( sarn... |
wqln - fm | https://en.wikipedia.org/wiki/WQLN-FM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14163566-1.html.csv | comparative | w207af and w211ae both share the same fcc info , fcc . | {'row_1': '1', 'row_2': '2', 'col': '5', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'call sign', 'w207af'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose call sign record fuzzily matches to w207af .', 'tostr': 'filter_eq { all_rows ; call sign ; w207af }'}, 'fc... | and { eq { hop { filter_eq { all_rows ; call sign ; w207af } ; fcc info } ; hop { filter_eq { all_rows ; call sign ; w211ae } ; fcc info } } ; and { eq { hop { filter_eq { all_rows ; call sign ; w207af } ; fcc info } ; fcc } ; eq { hop { filter_eq { all_rows ; call sign ; w211ae } ; fcc info } ; fcc } } } = true | select the rows whose call sign record fuzzily matches to w207af . take the fcc info record of this row . select the rows whose call sign record fuzzily matches to w211ae . take the fcc info record of this row . the first record fuzzily matches to the second record . the fcc info record of the first row is fcc . the fc... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'call sign_11': 11, 'w207af_12': 12, 'fcc info_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'call sign_15': 15, 'w211ae_16': 16, 'fcc info_17': 17, 'and_7': 7, 'str_eq_5': 5, 'fcc_18': 18, 'str_eq_6'... | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'call sign_11': 'call sign', 'w207af_12': 'w207af', 'fcc info_13': 'fcc info', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'call si... | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'call sign_11': [0], 'w207af_12': [0], 'fcc info_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'call sign_15': [1], 'w211ae_16': [1], 'fcc info_17': [3], 'and_7': [8], 'str_eq_5'... | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'fcc info'] | [['w207af', '89.3 fm', 'meadville , pa', '4', 'fcc'], ['w211ae', '90.1 fm', 'mayville , ny', '3', 'fcc'], ['w218ap', '91.5 fm', 'titusville , pa', '13', 'fcc'], ['w220ba', '91.9 fm', 'oil city , pa', '10', 'fcc'], ['w255ae', '98.9 fm', 'warren , pa', '50', 'fcc']] |
henri leconte | https://en.wikipedia.org/wiki/Henri_Leconte | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1171445-6.html.csv | unique | the 1990 london / queen 's club , england tournament was the only one played against jeremy bates and kevin curren . | {'scope': 'all', 'row': '15', 'col': '6', 'col_other': '2,3', 'criterion': 'equal', 'value': 'jeremy bates kevin curren', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents in the final', 'jeremy bates kevin curren'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponents in the final record fuzzily matches to jeremy bates kevin curren .', 'tostr': 'filter_eq { all_r... | and { only { filter_eq { all_rows ; opponents in the final ; jeremy bates kevin curren } } ; and { eq { hop { filter_eq { all_rows ; opponents in the final ; jeremy bates kevin curren } ; date } ; 1990 } ; eq { hop { filter_eq { all_rows ; opponents in the final ; jeremy bates kevin curren } ; tournament } ; london / q... | select the rows whose opponents in the final record fuzzily matches to jeremy bates kevin curren . there is only one such row in the table . the date record of this unqiue row is 1990 . the tournament record of this unqiue row is london / queen 's club , england . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'opponents in the final_10': 10, 'jeremy bates kevin curren_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'date_12': 12, '1990_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'tournament_14': 14, "london / queen 's club , england_15": 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'opponents in the final_10': 'opponents in the final', 'jeremy bates kevin curren_11': 'jeremy bates kevin curren', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'date_12': 'date', '1990_13': '19... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'opponents in the final_10': [0], 'jeremy bates kevin curren_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'date_12': [2], '1990_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'tournament_14': [4], "london / queen 's c... | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['winner', '1981', 'bologna , italy', 'carpet', 'sammy giammalva jr', 'tomáš šmíd balázs taróczy', '7 - 6 , 6 - 4'], ['winner', '1982', 'nice , france', 'clay', 'yannick noah', 'paul mcnamee balázs taróczy', '5 - 7 , 6 - 4 , 6 - 3'], ['runner - up', '1982', 'bournemouth , england', 'clay', 'ilie năstase', 'paul mcname... |
2010 - 11 san antonio spurs season | https://en.wikipedia.org/wiki/2010%E2%80%9311_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27715173-12.html.csv | aggregation | in the 2010-11 san antonio spurs season , for games where tim duncan had the high rebounds , his average number of rebounds was 11.5 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '11.5', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'tim duncan'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'tim duncan'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high rebounds ; tim duncan }', 'tointer': 'select the rows whose high rebounds record fuzzily matches to tim duncan .'}, 'high ... | round_eq { avg { filter_eq { all_rows ; high rebounds ; tim duncan } ; high rebounds } ; 11.5 } = true | select the rows whose high rebounds record fuzzily matches to tim duncan . the average of the high rebounds record of these rows is 11.5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high rebounds_5': 5, 'tim duncan_6': 6, 'high rebounds_7': 7, '11.5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high rebounds_5': 'high rebounds', 'tim duncan_6': 'tim duncan', 'high rebounds_7': 'high rebounds', '11.5_8': '11.5'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'tim duncan_6': [0], 'high rebounds_7': [1], '11.5_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 17', 'memphis', 'l 98 - 101 ( ot )', 'tony parker ( 20 )', 'tim duncan ( 13 )', 'tony parker ( 5 )', 'at & t center 18581', '0 - 1'], ['2', 'april 20', 'memphis', 'w 93 - 87 ( ot )', 'manu ginóbili ( 17 )', 'tim duncan ( 10 )', 'tony parker ( 7 )', 'at & t center 18760', '1 - 1'], ['3', 'april 23', 'memph... |
list of supernanny episodes | https://en.wikipedia.org/wiki/List_of_Supernanny_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-10.html.csv | ordinal | the orm family was the 3rd family to be featured . | {'row': '3', 'col': '2', 'order': '3', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'no in season', '3'], 'result': '3', 'ind': 0, 'tostr': 'nth_min { all_rows ; no in season ; 3 }', 'tointer': 'the 3rd minimum no in season record of all rows is 3 .'}, '3'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_... | and { eq { nth_min { all_rows ; no in season ; 3 } ; 3 } ; eq { hop { nth_argmin { all_rows ; no in season ; 3 } ; family / families } ; the orm family } } = true | the 3rd minimum no in season record of all rows is 3 . the family / families record of the row with 3rd minimum no in season record is the orm family . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'no in season_8': 8, '3_9': 9, '3_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'no in season_12': 12, '3_13': 13, 'family / families_14': 14, 'the orm family_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'no in season_8': 'no in season', '3_9': '3', '3_10': '3', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'no in season_12': 'no in season', '3_13': '3', 'family /... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'no in season_8': [0], '3_9': [0], '3_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'no in season_12': [2], '3_13': [2], 'family / families_14': [3], 'the orm family_15': [4]} | ['no in series', 'no in season', 'family / families', 'location ( s )', 'original air date'] | [['us1', '1', 'the jeans family', 'denver , co', '1 january 2005'], ['us2', '2', 'the bullard family', 'aurora , co', '24 january 2005'], ['us3', '3', 'the orm family', 'santa clarita , ca', '31 january 2005'], ['us4', '4', 'the wischmeyer family', 'colorado', '7 february 2005'], ['us5', '5', 'the weston family', 'flor... |
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/1-15187735-12.html.csv | comparative | of the how it 's made episodes , the episode where segment a was metal detectors was one episode before the episode where segment a was riding mowers . | {'row_1': '8', 'row_2': '9', 'col': '2', 'col_other': '4', 'relation': 'diff', 'record_mentioned': 'yes', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment a', 'metal detectors'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment a record fuzzily matches to metal detectors .', 'tostr': 'filter_eq ... | and { eq { diff { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } } ; -1 } ; and { eq { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; 151 } ; eq { hop { filter_eq { all_rows ; segment a ; riding mowe... | select the rows whose segment a record fuzzily matches to metal detectors . take the episode record of this row . select the rows whose segment a record fuzzily matches to riding mowers . take the episode record of this row . the second record is 1 larger than the first record . the episode record of the first row is 1... | 14 | 10 | {'and_9': 9, 'result_10': 10, 'eq_5': 5, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_11': 11, 'segment a_12': 12, 'metal detectors_13': 13, 'episode_14': 14, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_15': 15, 'segment a_16': 16, 'riding mowers_17': 17, 'episode_18': 18, '-1_19': 19, 'and_8': 8, '... | {'and_9': 'and', 'result_10': 'true', 'eq_5': 'eq', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_11': 'all_rows', 'segment a_12': 'segment a', 'metal detectors_13': 'metal detectors', 'episode_14': 'episode', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_row... | {'and_9': [10], 'result_10': [], 'eq_5': [9], 'diff_4': [5], 'num_hop_2': [4, 6], 'filter_str_eq_0': [2], 'all_rows_11': [0], 'segment a_12': [0], 'metal detectors_13': [0], 'episode_14': [2], 'num_hop_3': [4, 7], 'filter_str_eq_1': [3], 'all_rows_15': [1], 'segment a_16': [1], 'riding mowers_17': [1], 'episode_18': [3... | ['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d'] | [['12 - 01', '144', 's06e14', 'pneumatic impact wrenches', 'cultured marble sinks', 'plantain chips', 'nascar stock cars'], ['12 - 02', '145', 's06e15', 'jaws of life', 'artificial christmas trees', 'soda crackers', 'ratchets'], ['12 - 03', '146', 's06e16', 's thermometer', 'produce scales', 'aircraft painting', 'luxur... |
fringe ( season 1 ) | https://en.wikipedia.org/wiki/Fringe_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24648983-1.html.csv | majority | the majority of the episodes aired in 2008 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '2008', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'original air date', '2008'], 'result': True, 'ind': 0, 'tointer': 'for the original air date records of all rows , most of them fuzzily match to 2008 .', 'tostr': 'most_eq { all_rows ; original air date ; 2008 } = true'} | most_eq { all_rows ; original air date ; 2008 } = true | for the original air date records of all rows , most of them fuzzily match to 2008 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'original air date_3': 3, '2008_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'original air date_3': 'original air date', '2008_4': '2008'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'original air date_3': [0], '2008_4': [0]} | ['-', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['1', 'pilot', 'alex graves', 'j j abrams & alex kurtzman & roberto orci', 'september 9 , 2008', '276038', '9.13'], ['3', 'the ghost network', 'frederick e o toye', 'david h goodman & j r orci', 'september 23 , 2008', '3t7652', '9.42'], ['4', 'the arrival', 'paul edwards', 'j j abrams & jeff pinkner', 'september 30 , ... |
2008 - 09 detroit red wings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17371135-30.html.csv | comparative | red wings player had a higher number of pick points over julian cayer during the 2008-2009 season . | {'row_1': '4', 'row_2': '3', 'col': '2', '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', 'player', 'julien cayer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to julien cayer .', 'tostr': 'filter_eq { all_rows ; player ; julien cayer }'}, 'overall pick'], '... | greater { hop { filter_eq { all_rows ; player ; julien cayer } ; overall pick } ; hop { filter_eq { all_rows ; player ; gustav nyquist } ; overall pick } } = true | select the rows whose player record fuzzily matches to julien cayer . take the overall pick record of this row . select the rows whose player record fuzzily matches to gustav nyquist . take the overall pick record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'julien cayer_8': 8, 'overall pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'gustav nyquist_12': 12, 'overall pick_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'julien cayer_8': 'julien cayer', 'overall pick_9': 'overall pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11':... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'julien cayer_8': [0], 'overall pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'gustav nyquist_12': [1], 'overall pick_13': [3]} | ['round', 'overall pick', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', '30', 'thomas mccollum', 'goaltender', 'united states', 'guelph storm ( ohl )'], ['3', '91', 'max nicastro', 'defenseman', 'united states', 'chicago steel ( ushl )'], ['4', '121', 'gustav nyquist', 'center', 'sweden', 'malmã redhawks ( sweden jr )'], ['5', '151', 'julien cayer', 'center', 'canada', 'northwood sc... |
made ( tv series ) | https://en.wikipedia.org/wiki/Made_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2140071-13.html.csv | unique | chris is made into a celebrity assistant was the only episode where bj coleman was the coach . | {'scope': 'all', 'row': '9', 'col': '6', 'col_other': '3', 'criterion': 'equal', 'value': 'bj coleman', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'coach', 'bj coleman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose coach record fuzzily matches to bj coleman .', 'tostr': 'filter_eq { all_rows ; coach ; bj coleman }'}], 'result': True, 'ind': 1, 'tostr'... | and { only { filter_eq { all_rows ; coach ; bj coleman } } ; eq { hop { filter_eq { all_rows ; coach ; bj coleman } ; episode summary } ; chris is made into a celebrity assistant } } = true | select the rows whose coach record fuzzily matches to bj coleman . there is only one such row in the table . the episode summary record of this unqiue row is chris is made into a celebrity assistant . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'coach_7': 7, 'bj coleman_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'episode summary_9': 9, 'chris is made into a celebrity assistant_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'coach_7': 'coach', 'bj coleman_8': 'bj coleman', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'episode summary_9': 'episode summary', 'chris is made into a celebrity assistant_10': 'chris is made into ... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'coach_7': [0], 'bj coleman_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'episode summary_9': [2], 'chris is made into a celebrity assistant_10': [3]} | ['season', 'episode', 'episode summary', 'premier date', 'external link', 'coach'] | [['13', '1', 'cara is made into an actress', 'june 18 , 2012', 'full episode', 'nikki deloach'], ['13', '2', 'felicia is made into a rapper', 'june 19 , 2012', 'full episode', 'killer mike | - |'], ['13', '3', 'rachel is made into a makeup mogul', 'june 20 , 2012', 'full episode', 'nikki robinson'], ['13', '4', 'megan ... |
automobiles gonfaronnaises sportives | https://en.wikipedia.org/wiki/Automobiles_Gonfaronnaises_Sportives | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226665-1.html.csv | ordinal | ags jh22 was the second earliest chasis to be introduced in service among automobiles gonfaronnaises sportives . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, 'chassis'], 'result': 'ags jh22', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 2 } ; chassis }'}, 'ags jh22'], 'result'... | eq { hop { nth_argmin { all_rows ; year ; 2 } ; chassis } ; ags jh22 } = true | select the row whose year record of all rows is 2nd minimum . the chassis record of this row is ags jh22 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'chassis_7': 7, 'ags jh22_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', '2_6': '2', 'chassis_7': 'chassis', 'ags jh22_8': 'ags jh22'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'chassis_7': [1], 'ags jh22_8': [2]} | ['year', 'chassis', 'engine', 'tyres', 'points'] | [['1986', 'ags jh21c', 'motori moderni 615 - 90 v6 ( t / c )', 'p', '0'], ['1987', 'ags jh22', 'ford dfz v8', 'g', '1'], ['1988', 'ags jh23', 'ford dfz v8', 'g', '0'], ['1989', 'ags jh23b ags jh24', 'ford dfr v8', 'g', '1'], ['1990', 'ags jh24 ags jh25', 'ford dfr v8', 'g', '0'], ['1991', 'ags jh25b ags jh27', 'ford df... |
united states house of representatives elections , 1834 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1834 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668199-2.html.csv | majority | most of the incumbents in the 1834 house of representatives elections were re - elected . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 're - elected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to re - elected .', 'tostr': 'most_eq { all_rows ; result ; re - elected } = true'} | most_eq { all_rows ; result ; re - elected } = true | for the result records of all rows , most of them fuzzily match to re - elected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're - elected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're - elected_4': 're - elected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 1', 'joel b sutherland', 'jacksonian', '1826', 're - elected', 'joel b sutherland ( j ) 61.7 % james gowen 38.3 %'], ['pennsylvania 5', 'joel k mann', 'jacksonian', '1830', 'retired jacksonian hold', 'jacob fry , jr ( j ) 55.3 % james royer 44.7 %'], ['pennsylvania 6', 'robert ramsey', 'jacksonian', '18... |
1994 foster 's cup | https://en.wikipedia.org/wiki/1994_Foster%27s_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16387953-1.html.csv | aggregation | the average attendance in the first round of the 1994 foster 's cup was 18,978 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '18978', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '18978', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '18978'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 18978 } = true', 'tointer': 'the average of the crowd record of all rows is 18978 .'} | round_eq { avg { all_rows ; crowd } ; 18978 } = true | the average of the crowd record of all rows is 18978 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '18978_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '18978_5': '18978'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '18978_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'time'] | [['collingwood', '13.14 ( 92 )', 'north melbourne', '13.13 ( 91 )', 'waverley park', '25708', 'saturday , 19 february 1994', '8:00 pm'], ['st kilda', '14.12 ( 96 )', 'richmond', '17.14 ( 116 )', 'waverley park', '18662', 'monday , 21 february 1994', '8:00 pm'], ['adelaide', '16.17 ( 113 )', 'west coast', '14.10 ( 94 )'... |
2009 belmont stakes | https://en.wikipedia.org/wiki/2009_Belmont_Stakes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22517564-3.html.csv | superlative | mine that bird had the best opening odds of all the other horses in the 2009 belmont stakes horse race . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'opening odds'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; opening odds }'}, 'horse name'], 'result': 'mine that bird', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; opening odds } ; horse name }'}, 'mine that... | eq { hop { argmin { all_rows ; opening odds } ; horse name } ; mine that bird } = true | select the row whose opening odds record of all rows is minimum . the horse name record of this row is mine that bird . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'opening odds_5': 5, 'horse name_6': 6, 'mine that bird_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'opening odds_5': 'opening odds', 'horse name_6': 'horse name', 'mine that bird_7': 'mine that bird'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'opening odds_5': [0], 'horse name_6': [1], 'mine that bird_7': [2]} | ['post', 'horse name', 'trainer', 'jockey', 'opening odds', 'starting odds', 'finishing pos'] | [['1', 'chocolate candy', 'jerry hollendorfer', 'garrett gomez', '10 - 1', '9.50', '9'], ['2', 'dunkirk', 'todd pletcher', 'john velazquez', '4 - 1', '4.60', '2'], ['3', 'mr hot stuff', 'eoin harty', 'edgar prado', '15 - 1', '22.60', '8'], ['4', 'summer bird', 'tim ice', 'kent desormeaux', '12 - 1', '11.90', '1'], ['5'... |
portuguese legislative election , 1991 | https://en.wikipedia.org/wiki/Portuguese_legislative_election%2C_1991 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1886589-1.html.csv | majority | the majority of years had a total lead of at least 10 % . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '10', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'lead', '10'], 'result': True, 'ind': 0, 'tointer': 'for the lead records of all rows , most of them are greater than or equal to 10 .', 'tostr': 'most_greater_eq { all_rows ; lead ; 10 } = true'} | most_greater_eq { all_rows ; lead ; 10 } = true | for the lead records of all rows , most of them are greater than or equal to 10 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'lead_3': 3, '10_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'lead_3': 'lead', '10_4': '10'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'lead_3': [0], '10_4': [0]} | ['date released', 'polling institute', 'social democratic', 'socialist', 'green - communist', 'democratic and social centre', 'lead'] | [['october 6 , 1991', 'election results', '50.6 % 135 seats', '29.1 % 72 seats', '8.8 % 17 seats', '4.4 % 5 seats', '21.5 %'], ['october 6 , 1991', 'exit poll - rtp1 universidade católica', '48.0 % - 51.9 %', '28.5 % - 31.5 %', '7.5 % - 10.0 %', '4.5 % - 5.5 %', '19.5 % - 20.4 %'], ['october 6 , 1991', 'exit poll - tsf... |
2010 - 11 oklahoma city thunder season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Oklahoma_City_Thunder_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27712702-11.html.csv | ordinal | in the 2010 - 11 oklahoma city thunder season , the second highest attendance was on march 13th . | {'row': '7', 'col': '8', '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', 'location attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 2 }'}, 'date'], 'result': 'march 13', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ... | eq { hop { nth_argmax { all_rows ; location attendance ; 2 } ; date } ; march 13 } = true | select the row whose location attendance record of all rows is 2nd maximum . the date record of this row is march 13 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '2_6': 6, 'date_7': 7, 'march 13_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', 'location attendance_5': 'location attendance', '2_6': '2', 'date_7': 'date', 'march 13_8': 'march 13'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '2_6': [0], 'date_7': [1], 'march 13_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 2', 'indiana', 'w 113 - 89 ( ot )', 'kevin durant , russell westbrook ( 21 )', 'serge ibaka ( 12 )', 'russell westbrook ( 9 )', 'oklahoma city arena 18203', '37 - 22'], ['60', 'march 4', 'atlanta', 'w 111 - 104 ( ot )', 'kevin durant ( 29 )', 'kevin durant ( 8 )', 'russell westbrook ( 9 )', 'philips aren... |
politics of veneto | https://en.wikipedia.org/wiki/Politics_of_Veneto | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10747104-1.html.csv | aggregation | the average number of inhabitants among italian provinces voting for the liga veneta party is 708,899 . | {'scope': 'subset', 'col': '2', 'type': 'average', 'result': '708899', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'liga veneta'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'liga veneta'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; liga veneta }', 'tointer': 'select the rows whose party record fuzzily matches to liga veneta .'}, 'inhabitants'], 'result': '... | round_eq { avg { filter_eq { all_rows ; party ; liga veneta } ; inhabitants } ; 708899 } = true | select the rows whose party record fuzzily matches to liga veneta . the average of the inhabitants record of these rows is 708899 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'liga veneta_6': 6, 'inhabitants_7': 7, '708899_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'liga veneta_6': 'liga veneta', 'inhabitants_7': 'inhabitants', '708899_8': '708899'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'liga veneta_6': [0], 'inhabitants_7': [1], '708899_8': [2]} | ['province', 'inhabitants', 'president', 'party', 'election'] | [['padua', '934216', 'barbara degani', 'the people of freedom', '2009'], ['verona', '920158', 'giovanni miozzi', 'the people of freedom', '2009'], ['treviso', '888249', 'leonardo muraro', 'liga veneta', '2011'], ['vicenza', '870740', 'attilio schneck', 'liga veneta', '2007'], ['venice', '863133', 'francesca zaccariotto... |
chennai super kings | https://en.wikipedia.org/wiki/Chennai_Super_Kings | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15829930-5.html.csv | unique | for the chennai super kings , when they were the runners-up , the only time they had 11 losses was in 2012 . | {'scope': 'subset', 'row': '5', 'col': '4', 'col_other': '1,9', 'criterion': 'equal', 'value': '11', 'subset': {'col': '9', 'criterion': 'equal', 'value': 'runners - up'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'summary', 'runners - up'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; summary ; runners - up }', 'tointer': 'select the rows whose summary record fuzzily matches to runners -... | and { only { filter_eq { filter_eq { all_rows ; summary ; runners - up } ; losses ; 11 } } ; eq { hop { filter_eq { filter_eq { all_rows ; summary ; runners - up } ; losses ; 11 } ; year } ; 2012 } } = true | select the rows whose summary record fuzzily matches to runners - up . among these rows , select the rows whose losses record is equal to 11 . there is only one such row in the table . the year record of this unqiue row is 2012 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'summary_8': 8, 'runners - up_9': 9, 'losses_10': 10, '11_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'year_12': 12, '2012_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'summary_8': 'summary', 'runners - up_9': 'runners - up', 'losses_10': 'losses', '11_11': '11', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'year_12': 'year', '2012_13': '2012'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'summary_8': [0], 'runners - up_9': [0], 'losses_10': [1], '11_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'year_12': [3], '2012_13': [4]} | ['year', 'matches', 'wins', 'losses', 'no result', 'tied', 'success rate', 'position', 'summary'] | [['2008', '16', '9', '7', '0', '0', '56.25 %', '2nd', 'runners - up'], ['2009', '15', '8', '6', '1', '0', '53.33 %', '4th', 'semi - finalists'], ['2010', '16', '9', '7', '0', '0', '56.25 %', '1st', 'champions'], ['2011', '16', '11', '5', '0', '0', '68.75 %', '1st', 'champions'], ['2012', '19', '19', '11', '8', '0', '52... |
1998 major league baseball draft | https://en.wikipedia.org/wiki/1998_Major_League_Baseball_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18468611-2.html.csv | comparative | jeff urban was selected later in the draft than chris george was . | {'row_1': '11', 'row_2': '1', 'col': '1', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jeff urban'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jeff urban .', 'tostr': 'filter_eq { all_rows ; player ; jeff urban }'},... | and { greater { hop { filter_eq { all_rows ; player ; jeff urban } ; pick } ; hop { filter_eq { all_rows ; player ; chris george } ; pick } } ; and { eq { hop { filter_eq { all_rows ; player ; jeff urban } ; pick } ; 41 } ; eq { hop { filter_eq { all_rows ; player ; chris george } ; pick } ; 31 } } } = true | select the rows whose player record fuzzily matches to jeff urban . take the pick record of this row . select the rows whose player record fuzzily matches to chris george . take the pick record of this row . the first record is greater than the second record . the pick record of the first row is 41 . the pick record of... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'player_11': 11, 'jeff urban_12': 12, 'pick_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'player_15': 15, 'chris george_16': 16, 'pick_17': 17, 'and_7': 7, 'eq_5': 5, '41_18': 18, 'eq_6': 6, '31_19'... | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'jeff urban_12': 'jeff urban', 'pick_13': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'player_15':... | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'player_11': [0], 'jeff urban_12': [0], 'pick_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'player_15': [1], 'chris george_16': [1], 'pick_17': [3], 'and_7': [8], 'eq_5': [7], ... | ['pick', 'player', 'team', 'position', 'school'] | [['31', 'chris george', 'kansas city royals', 'p', 'klein hs ( klein , tx )'], ['32', 'ben diggins', 'st louis cardinals', 'p', 'bradshaw mountain hs ( prescott valley , az )'], ['33', 'brad wilkerson', 'montreal expos', 'of', 'university of florida'], ['34', 'nate cornejo', 'detroit tigers', 'p', 'wellington hs ( well... |
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 | majority | dustley mulder played the majority of seasons with the club rkc waalwijk . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rkc waalwijk', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'club', 'rkc waalwijk'], 'result': True, 'ind': 0, 'tointer': 'for the club records of all rows , most of them fuzzily match to rkc waalwijk .', 'tostr': 'most_eq { all_rows ; club ; rkc waalwijk } = true'} | most_eq { all_rows ; club ; rkc waalwijk } = true | for the club records of all rows , most of them fuzzily match to rkc waalwijk . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'club_3': 3, 'rkc waalwijk_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'club_3': 'club', 'rkc waalwijk_4': 'rkc waalwijk'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'club_3': [0], 'rkc waalwijk_4': [0]} | ['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... |
2007 - 08 isthmian league | https://en.wikipedia.org/wiki/2007%E2%80%9308_Isthmian_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17494040-9.html.csv | aggregation | for the 2007-08 isthmian league the total combined attendance was 558 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '558', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '558', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '558'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 558 } = true', 'tointer': 'the sum of the attendance record of all rows is 558 .'... | round_eq { sum { all_rows ; attendance } ; 558 } = true | the sum of the attendance record of all rows is 558 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '558_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '558_5': '558'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '558_5': [1]} | ['tie no', 'home team', 'score', 'away team', 'attendance'] | [['59', 'afc sudbury', '1 - 0', 'edgware town', '176'], ['60', 'carshalton athletic', '1 - 1', 'walton casuals', '95'], ['walton casuals advance 5 - 4 on penalties', 'walton casuals advance 5 - 4 on penalties', 'walton casuals advance 5 - 4 on penalties', 'walton casuals advance 5 - 4 on penalties', 'walton casuals adv... |
bluebird k7 | https://en.wikipedia.org/wiki/Bluebird_K7 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17829496-1.html.csv | majority | donald campbell was the pilot for all of the bluebird k7 speed record attempts . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'donald campbell', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'pilot', 'donald campbell'], 'result': True, 'ind': 0, 'tointer': 'for the pilot records of all rows , all of them fuzzily match to donald campbell .', 'tostr': 'all_eq { all_rows ; pilot ; donald campbell } = true'} | all_eq { all_rows ; pilot ; donald campbell } = true | for the pilot records of all rows , all of them fuzzily match to donald campbell . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'pilot_3': 3, 'donald campbell_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'pilot_3': 'pilot', 'donald campbell_4': 'donald campbell'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'pilot_3': [0], 'donald campbell_4': [0]} | ['speed', 'craft', 'pilot', 'location', 'date'] | [['-', 'bluebird k7', 'donald campbell', 'ullswater', '23 july 1955'], ['-', 'bluebird k7', 'donald campbell', 'lake mead', '16 november 1955'], ['-', 'bluebird k7', 'donald campbell', 'coniston water', '19 september 1956'], ['-', 'bluebird k7', 'donald campbell', 'coniston water', '7 november 1957'], ['-', 'bluebird k... |
list of schools in the wellington region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Wellington_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12214488-8.html.csv | superlative | of the schools in the featherston area , st. teresa 's school has the highest roll . | {'scope': 'subset', 'col_superlative': '7', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'featherston'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'area', 'featherston'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; area ; featherston }', 'tointer': 'select the rows whose area record fuzzily matches to featherston .'}, ... | eq { hop { argmax { filter_eq { all_rows ; area ; featherston } ; roll } ; name } ; st teresa 's school } = true | select the rows whose area record fuzzily matches to featherston . select the row whose roll record of these rows is maximum . the name record of this row is st teresa 's school . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'area_6': 6, 'featherston_7': 7, 'roll_8': 8, 'name_9': 9, "st teresa 's school_10": 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'area_6': 'area', 'featherston_7': 'featherston', 'roll_8': 'roll', 'name_9': 'name', "st teresa 's school_10": "st teresa 's school"} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'area_6': [0], 'featherston_7': [0], 'roll_8': [1], 'name_9': [2], "st teresa 's school_10": [3]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['featherston school', '1 - 8', 'coed', 'featherston', 'state', '3', '64'], ['greytown school', '1 - 8', 'coed', 'greytown', 'state', '6', '348'], ['kahutara school', '1 - 8', 'coed', 'kahutara', 'state', '7', '100'], ['kuranui college', '9 - 13', 'coed', 'greytown', 'state', '5', '488'], ['martinborough school', '1 -... |
list of csi : ny characters | https://en.wikipedia.org/wiki/List_of_CSI%3A_NY_characters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11240028-1.html.csv | count | there are 8 characters of csi : ny who have their last appearance on the episode today is life . | {'scope': 'all', 'criterion': 'equal', 'value': 'today is life', 'result': '8', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'last appearance', 'today is life'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose last appearance record fuzzily matches to today is life .', 'tostr': 'filter_eq { all_rows ; last appearance ; today is life ... | eq { count { filter_eq { all_rows ; last appearance ; today is life } } ; 8 } = true | select the rows whose last appearance record fuzzily matches to today is life . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'last appearance_5': 5, 'today is life_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'last appearance_5': 'last appearance', 'today is life_6': 'today is life', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'last appearance_5': [0], 'today is life_6': [0], '8_7': [2]} | ['character', 'portrayed by', 'first appearance', 'last appearance', 'duration', 'episodes'] | [['mac taylor csi detective', 'gary sinise', 'blink 1 , 2 , 3', 'today is life', '1.01 - 9.17', '197'], ['jo danville csi detective', 'sela ward', 'the 34th floor', 'today is life', '7.01 - 9.17', '57'], ['danny messer csi detective', 'carmine giovinazzo', 'blink 1', 'today is life', '1.01 - 9.17', '197'], ['lindsay mo... |
steve vigneault | https://en.wikipedia.org/wiki/Steve_Vigneault | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17442303-2.html.csv | superlative | the shortest fight that steve vigneault had was against jeff davis . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '15', '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', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'opponent'], 'result': 'jeff davis', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; opponent }'}, 'jeff davis'], 'result': True, 'ind': 2, '... | eq { hop { argmin { all_rows ; time } ; opponent } ; jeff davis } = true | select the row whose time record of all rows is minimum . the opponent record of this row is jeff davis . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'opponent_6': 6, 'jeff davis_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'opponent_6': 'opponent', 'jeff davis_7': 'jeff davis'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'opponent_6': [1], 'jeff davis_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '12 - 6', 'dan chambers', 'tko ( punches )', 'ringside mma - rivalry', '1', '4:03', 'quebec , canada'], ['loss', '11 - 6', 'mike swick', 'submission ( guillotine choke )', 'ufc 58', '1', '2:09', 'las vegas , nevada , united states'], ['win', '11 - 5', 'jason st louis', 'tko', 'tko 22 - lionheart', '2', '0:30',... |
2004 arizona cardinals season | https://en.wikipedia.org/wiki/2004_Arizona_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18722259-2.html.csv | ordinal | during the 2004 season , the arizona cardinals game with the second lowest attendance was played in january 2005 . | {'row': '16', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'january 2 , 2005', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; attendance ; 2 } ; date }'}, '... | eq { hop { nth_argmin { all_rows ; attendance ; 2 } ; date } ; january 2 , 2005 } = true | select the row whose attendance record of all rows is 2nd minimum . the date record of this row is january 2 , 2005 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'january 2 , 2005_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', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'january 2 , 2005_8': 'january 2 , 2005'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'january 2 , 2005_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 12 , 2004', 'st louis rams', 'l 17 - 10', '65538'], ['2', 'september 19 , 2004', 'new england patriots', 'l 23 - 12', '51557'], ['3', 'september 26 , 2004', 'atlanta falcons', 'l 6 - 3', '70534'], ['4', 'october 3 , 2004', 'new orleans saints', 'w 34 - 10', '28109'], ['5', 'october 10 , 2004', 'san fr... |
southern athletic conference of indiana | https://en.wikipedia.org/wiki/Southern_Athletic_Conference_of_Indiana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18956862-1.html.csv | majority | the majority of the teams joined the southern athletic conference of indiana before 1978 . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1978', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'year joined', '1978'], 'result': True, 'ind': 0, 'tointer': 'for the year joined records of all rows , most of them are less than 1978 .', 'tostr': 'most_less { all_rows ; year joined ; 1978 } = true'} | most_less { all_rows ; year joined ; 1978 } = true | for the year joined records of all rows , most of them are less than 1978 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year joined_3': 3, '1978_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year joined_3': 'year joined', '1978_4': '1978'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'year joined_3': [0], '1978_4': [0]} | ['school', 'location', 'mascot', 'county', 'enrollment', 'ihsaa class', 'year joined', 'previous conference'] | [['borden', 'borden', 'braves', '228', 'a', '10 clark', '1974', 'lost river'], ['crothersville', 'crothersville', 'tigers', '180', 'a', '36 jackson', '1974', 'mid - hoosier'], ['henryville', 'henryville', 'hornets', '347', 'aa', '10 clark', '1977', 'lost river'], ['lanesville', 'lanesville', 'eagles', '237', 'a', '31 h... |
comparison of brainwave entrainment software | https://en.wikipedia.org/wiki/Comparison_of_brainwave_entrainment_software | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15038373-1.html.csv | count | only three of the brainwave entrainment software programs are able to be used on the linux operating system . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'linux', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'operating systems', 'linux'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose operating systems record fuzzily matches to linux .', 'tostr': 'filter_eq { all_rows ; operating systems ; linux }'}], 'result': '3... | eq { count { filter_eq { all_rows ; operating systems ; linux } } ; 3 } = true | select the rows whose operating systems record fuzzily matches to linux . 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, 'operating systems_5': 5, 'linux_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', 'operating systems_5': 'operating systems', 'linux_6': 'linux', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'operating systems_5': [0], 'linux_6': [0], '3_7': [2]} | ['software', 'version', 'operating systems', 'developer', 'license'] | [['beeone smod / hms', '3.1', 'windows', 'hemi - synths explorers', 'proprietary'], ['brainwave generator', '3.1', 'windows', 'noromaa solutions oy', 'proprietary'], ['gnaural', '1.0.20100707', 'freebsd , linux , mac os x , windows', 'gnaural', 'gpl'], ['brainigniter player', '6.0', 'windows', 'volition', 'proprietary'... |
1903 in paleontology | https://en.wikipedia.org/wiki/1903_in_paleontology | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15689683-1.html.csv | comparative | in 1903 paleontology , a telmatosaurus was recorded in romania , whereas a brachiosaurus was recorded in colorado . | {'row_1': '5', 'row_2': '1', 'col': '6', 'col_other': '1', 'relation': 'not_equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'not_str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'telmatosaurus'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to telmatosaurus .', 'tostr': 'filter_eq { all_rows ; name ; telmatosauru... | and { not_eq { hop { filter_eq { all_rows ; name ; telmatosaurus } ; location } ; hop { filter_eq { all_rows ; name ; brachiosaurus } ; location } } ; and { eq { hop { filter_eq { all_rows ; name ; telmatosaurus } ; location } ; romania } ; eq { hop { filter_eq { all_rows ; name ; brachiosaurus } ; location } ; usa } }... | select the rows whose name record fuzzily matches to telmatosaurus . take the location record of this row . select the rows whose name record fuzzily matches to brachiosaurus . take the location record of this row . the first record does not match to the second record . the location record of the first row is romania .... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'not_str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'name_11': 11, 'telmatosaurus_12': 12, 'location_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'name_15': 15, 'brachiosaurus_16': 16, 'location_17': 17, 'and_7': 7, 'str_eq_5': 5, 'romania_18': 18... | {'and_8': 'and', 'result_9': 'true', 'not_str_eq_4': 'not_str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'telmatosaurus_12': 'telmatosaurus', 'location_13': 'location', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_row... | {'and_8': [9], 'result_9': [], 'not_str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'name_11': [0], 'telmatosaurus_12': [0], 'location_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'name_15': [1], 'brachiosaurus_16': [1], 'location_17': [3], 'and_7': [8], 's... | ['name', 'novelty', 'status', 'authors', 'unit', 'location'] | [['brachiosaurus', 'gen et sp', 'valid', 'riggs', 'morrison formation , colorado', 'usa'], ['haplocanthosaurus', 'gen et sp', 'valid , nomen conservandum', 'hatcher', 'morrison formation , colorado', 'usa'], ['haplocanthus', 'gen et sp', 'nomen oblitum', 'hatcher', 'morrison formation , colorado', 'usa'], ['ornitholest... |
1956 cleveland browns season | https://en.wikipedia.org/wiki/1956_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10651573-1.html.csv | superlative | the game against the college all-stars at chicago drew the highest attendance in the 1956 cleveland browns season . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'college all - stars at chicago', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'col... | eq { hop { argmax { all_rows ; attendance } ; opponent } ; college all - stars at chicago } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is college all - stars at chicago . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'college all - stars at chicago_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'college all - stars at chicago_7': 'college all - stars at chicago'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'college all - stars at chicago_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 10 , 1956', 'college all - stars at chicago', 'w 26 - 0', '75000'], ['2', 'august 19 , 1956', 'san francisco 49ers', 'l 28 - 17', '38741'], ['3', 'august 24 , 1956', 'los angeles rams', 'l 17 - 6', '40175'], ['4', 'september 1 , 1956', 'green bay packers', 'l 21 - 20', '15456'], ['5', 'september 7 , 1956... |
1953 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1953_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17290169-1.html.csv | superlative | ben hogan is the player with the lowest scores in 1953 u.s golf opens . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; score }'}, 'player'], 'result': 'ben hogan', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; score } ; player }'}, 'ben hogan'], 'result': True, 'ind': 2, 'tos... | eq { hop { argmin { all_rows ; score } ; player } ; ben hogan } = true | select the row whose score record of all rows is minimum . the player record of this row is ben hogan . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'score_5': 5, 'player_6': 6, 'ben hogan_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'score_5': 'score', 'player_6': 'player', 'ben hogan_7': 'ben hogan'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'score_5': [0], 'player_6': [1], 'ben hogan_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'ben hogan', 'united states', '67', '- 5'], ['t2', 'walter burkemo', 'united states', '70', '- 2'], ['t2', 'george fazio', 'united states', '70', '- 2'], ['t2', 'frank souchak ( a )', 'united states', '70', '- 2'], ['t5', 'jimmy demaret', 'united states', '71', '- 1'], ['t5', 'bill ogden', 'united states', '71',... |
bedford blues | https://en.wikipedia.org/wiki/Bedford_Blues | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1620305-1.html.csv | ordinal | zoo sport ltd is the most recent supplier for rugby union bedford blues . | {'row': '5', 'col': '1', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'year', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year ; 1 }'}, 'year'], 'result': '2011 - 2014', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year ; 1 } ; year }'}, '2011 - 2014'], 'result'... | eq { hop { nth_argmax { all_rows ; year ; 1 } ; year } ; 2011 - 2014 } = true | select the row whose year record of all rows is 1st maximum . the year record of this row is 2011 - 2014 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, '1_6': 6, 'year_7': 7, '2011 - 2014_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'year_5': 'year', '1_6': '1', 'year_7': 'year', '2011 - 2014_8': '2011 - 2014'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], '1_6': [0], 'year_7': [1], '2011 - 2014_8': [2]} | ['year', 'supplier', 'chest', 'sleeves', 'back'] | [['unknown', 'gilbert', 'unknown', 'unknown', 'unknown'], ['2006 - 2008', 'kooga', 'autoglass', 'wells bombardier', 'lifesure'], ['2008 - 2010', 'kooga', 'autoglass', 'wells bombardier', 'lifesure'], ['2010 - 2011', 'kooga', 'autoglass', 'wells bombardier', 'lifesure'], ['2011 - 2014', 'zoo sport ltd', 'autoglass', 'we... |
list of one - day cricket records for new zealand | https://en.wikipedia.org/wiki/List_of_one-day_cricket_records_for_New_Zealand | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13322378-10.html.csv | unique | only chris pringle had less than 3000 runs in the list of one - day cricket records for new zealand . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'less_than', 'value': '3000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'runs', '3000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runs record is less than 3000 .', 'tostr': 'filter_less { all_rows ; runs ; 3000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all... | and { only { filter_less { all_rows ; runs ; 3000 } } ; eq { hop { filter_less { all_rows ; runs ; 3000 } ; } ; chris pringle } } = true | select the rows whose runs record is less than 3000 . there is only one such row in the table . the record of this unqiue row is chris pringle . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'runs_7': 7, '3000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, '_9': 9, 'chris pringle_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'runs_7': 'runs', '3000_8': '3000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', '_9': '', 'chris pringle_10': 'chris pringle'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'runs_7': [0], '3000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], '_9': [2], 'chris pringle_10': [3]} | ['', 'matches', 'runs', 'wickets', 'average', 'economy rate', 'best bowling', '4wi', '5wi'] | [['shane bond', '82', '3070', '147', '20.88', '4.28', '6 / 19', '7', '4'], ['richard hadlee', '115', '3407', '158', '21.56', '4.20', '5 / 25', '1', '5'], ['chris pringle', '64', '2459', '103', '23.87', '4.45', '5 / 45', '2', '1'], ['ewen chatfield', '114', '3618', '140', '25.84', '3.57', '5 / 34', '3', '1'], ['kyle mil... |
felice herrig | https://en.wikipedia.org/wiki/Felice_Herrig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16182887-2.html.csv | unique | the event unconquered 1 : november reign was the only event with a time of 2:03 . | {'scope': 'all', 'row': '11', 'col': '7', 'col_other': '5', 'criterion': 'equal', 'value': '2:03', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', '2:03'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to 2:03 .', 'tostr': 'filter_eq { all_rows ; time ; 2:03 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq {... | and { only { filter_eq { all_rows ; time ; 2:03 } } ; eq { hop { filter_eq { all_rows ; time ; 2:03 } ; event } ; unconquered 1 : november reign } } = true | select the rows whose time record fuzzily matches to 2:03 . there is only one such row in the table . the event record of this unqiue row is unconquered 1 : november reign . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time_7': 7, '2:03_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'event_9': 9, 'unconquered 1: november reign_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time_7': 'time', '2:03_8': '2:03', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'event_9': 'event', 'unconquered 1: november reign_10': 'unconquered 1 : november reign'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], '2:03_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'event_9': [2], 'unconquered 1: november reign_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '9 - 4', 'heather clark', 'decision ( split )', 'bellator 94', '3', '5:00', 'tampa , florida , united states'], ['win', '8 - 4', 'patricia vidonic', 'decision ( unanimous )', 'bellator 84', '3', '5:00', 'hammond , indiana , united states'], ['win', '7 - 4', 'simona soukupova', 'decision ( unanimous )', 'xfc 19... |
anastasija sevastova | https://en.wikipedia.org/wiki/Anastasija_Sevastova | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16484261-3.html.csv | superlative | anastasija sevastova 's first match in 2006 took place in germany . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': '2006'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2006'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 2006 }', 'tointer': 'select the rows whose date record fuzzily matches to 2006 .'}, 'date'], 'result': No... | eq { hop { argmin { filter_eq { all_rows ; date ; 2006 } ; date } ; opponent } ; josipa bek } = true | select the rows whose date record fuzzily matches to 2006 . select the row whose date record of these rows is minimum . the opponent record of this row is josipa bek . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, '2006_7': 7, 'date_8': 8, 'opponent_9': 9, 'josipa bek_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', '2006_7': '2006', 'date_8': 'date', 'opponent_9': 'opponent', 'josipa bek_10': 'josipa bek'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], '2006_7': [0], 'date_8': [1], 'opponent_9': [2], 'josipa bek_10': [3]} | ['date', 'tournament', 'surface', 'opponent', 'score'] | [['august 6 , 2006', 'bad saulgau , germany', 'clay', 'josipa bek', '6 - 1 , 6 - 0'], ['august 20 , 2006', 'bratislava , slovakia', 'clay', 'klaudia malenovska', '4 - 6 , 6 - 0 , 6 - 3'], ['march 22 , 2008', 'noida , india', 'hard', 'sunitha rao', '6 - 2 , 6 - 1'], ['june 1 , 2008', 'galatina , italy', 'clay', 'estrell... |
list of preakness stakes broadcasters | https://en.wikipedia.org/wiki/List_of_Preakness_Stakes_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22654139-2.html.csv | majority | bob costas and tom hammond were the s hosts for all of the preaknass stakes broadcasts . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'bob costas and tom hammond', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 's host', 'bob costas and tom hammond'], 'result': True, 'ind': 0, 'tointer': 'for the s host records of all rows , all of them fuzzily match to bob costas and tom hammond .', 'tostr': 'all_eq { all_rows ; s host ; bob costas and tom hammond } = true'} | all_eq { all_rows ; s host ; bob costas and tom hammond } = true | for the s host records of all rows , all of them fuzzily match to bob costas and tom hammond . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 's host_3': 3, 'bob costas and tom hammond_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 's host_3': 's host', 'bob costas and tom hammond_4': 'bob costas and tom hammond'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 's host_3': [0], 'bob costas and tom hammond_4': [0]} | ['year', 'network', 'race caller', 's host', 's analyst', 'reporters', 'trophy presentation'] | [['2009', 'nbc', 'tom durkin', 'bob costas and tom hammond', 'gary l stevens , bob neumeier and mike battaglia', 'kenny rice and donna barton brothers', 'bob costas and mike battaglia'], ['2008', 'nbc', 'tom durkin', 'bob costas and tom hammond', 'gary l stevens , bob neumeier and mike battaglia', 'kenny rice and donna... |
2005 - 06 ottawa senators season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Ottawa_Senators_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622632-3.html.csv | count | hasek was the decision 4 times when the senators had ottawa as home games in the 2005-6 season . | {'scope': 'subset', 'criterion': 'equal', 'value': 'hasek', 'result': '4', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'ottawa'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home', 'ottawa'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; home ; ottawa }', 'tointer': 'select the rows whose home record fuzzily matches to ottawa .'}, 'decision', 'h... | eq { count { filter_eq { filter_eq { all_rows ; home ; ottawa } ; decision ; hasek } } ; 4 } = true | select the rows whose home record fuzzily matches to ottawa . among these rows , select the rows whose decision record fuzzily matches to hasek . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'home_6': 6, 'ottawa_7': 7, 'decision_8': 8, 'hasek_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'home_6': 'home', 'ottawa_7': 'ottawa', 'decision_8': 'decision', 'hasek_9': 'hasek', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'home_6': [0], 'ottawa_7': [0], 'decision_8': [1], 'hasek_9': [1], '4_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['october 5', 'ottawa', '3 - 2', 'toronto maple leafs', 'hasek', '19452', '1 - 0 - 0'], ['october 8', 'buffalo sabres', '0 - 5', 'ottawa', 'hasek', '19661', '2 - 0 - 0'], ['october 10', 'toronto maple leafs', '5 - 6', 'ottawa', 'hasek', '18680', '3 - 0 - 0'], ['october 11', 'ottawa', '4 - 2', 'montreal canadiens', 'em... |
naval campaign of the war of the pacific | https://en.wikipedia.org/wiki/Naval_Campaign_of_the_War_of_the_Pacific | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23614702-1.html.csv | unique | the warship manco capac was the only ship that was equipped with 10 inch armour . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'armour ( inch )', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose armour ( inch ) record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; armour ( inch ) ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'on... | and { only { filter_eq { all_rows ; armour ( inch ) ; 10 } } ; eq { hop { filter_eq { all_rows ; armour ( inch ) ; 10 } ; warship } ; manco cápac } } = true | select the rows whose armour ( inch ) record is equal to 10 . there is only one such row in the table . the warship record of this unqiue row is manco cápac . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'armour (inch)_7': 7, '10_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'warship_9': 9, 'manco cápac_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'armour (inch)_7': 'armour ( inch )', '10_8': '10', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'warship_9': 'warship', 'manco cápac_10': 'manco cápac'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'armour (inch)_7': [0], '10_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'warship_9': [2], 'manco cápac_10': [3]} | ['warship', 'tons ( lton )', 'horse - power', 'speed ( knots )', 'armour ( inch )', 'main artillery', 'built year'] | [['cochrane', '3560', '2000', '9 - 12 , 8', 'up to 9', '6x9 inch', '1874'], ['blanco encalada', '3560', '3000', '9 - 12 , 8', 'up to 9', '6x9 inch', '1874'], ['huascar', '1130', '1200', '10 - 11', '4 ½', '2x300 - pounders', '1865'], ['independencia', '2004', '1500', '12 - 13', '4 ½', '2x150 - pounders', '1865'], ['manc... |
howard county delegation | https://en.wikipedia.org/wiki/Howard_County_Delegation | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14009909-1.html.csv | count | two of the elected delegates for howard represent baltimore county . | {'scope': 'all', 'criterion': 'equal', 'value': 'baltimore county , howard', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'counties represented', 'baltimore county , howard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose counties represented record fuzzily matches to baltimore county , howard .', 'tostr': 'filter_eq { all_rows ... | eq { count { filter_eq { all_rows ; counties represented ; baltimore county , howard } } ; 2 } = true | select the rows whose counties represented record fuzzily matches to baltimore county , howard . 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, 'counties represented_5': 5, 'baltimore county, howard_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', 'counties represented_5': 'counties represented', 'baltimore county, howard_6': 'baltimore county , howard', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'counties represented_5': [0], 'baltimore county, howard_6': [0], '2_7': [2]} | ['district', 'counties represented', 'delegate', 'party', 'first elected', 'committee'] | [['09.1 9a', 'howard', 'bates , gail h gail h bates', 'republican', '2002', 'appropriations'], ['09.1 9a', 'howard', 'miller , warren e warren e miller', 'republican', '2003', 'economic matters'], ['12.1 12a', 'baltimore county , howard', 'deboy , steven j sr steven j deboy , sr', 'democratic', '2002', 'appropriations'... |
list of are you afraid of the dark ? episodes | https://en.wikipedia.org/wiki/List_of_Are_You_Afraid_of_the_Dark%3F_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10470082-6.html.csv | count | there were four episodes in the 5th season of " are you afraid of the dark " where there was no villain . | {'scope': 'all', 'criterion': 'equal', 'value': 'none', 'result': '4', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'villains', 'none'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose villains record fuzzily matches to none .', 'tostr': 'filter_eq { all_rows ; villains ; none }'}], 'result': '4', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; villains ; none } } ; 4 } = true | select the rows whose villains record fuzzily matches to none . 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, 'villains_5': 5, 'none_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', 'villains_5': 'villains', 'none_6': 'none', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'villains_5': [0], 'none_6': [0], '4_7': [2]} | ['no', '-', 'title', 'director', 'writer', 'us air date', 'storyteller', 'villains'] | [['53', '1', "the tale of the dead man 's float", 'd j machale', 'will dixon', 'october 7 , 1995', 'stig', 'the pool zombie'], ['54', '2', 'the tale of the jagged sign', 'will dixon', 'susan kim', 'october 14 , 1995', 'kiki', 'none'], ['55', '3', 'the tale of station 109.1', 'ron oliver', 'scott peters', 'november 4 , ... |
rizal | https://en.wikipedia.org/wiki/Rizal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-232458-1.html.csv | count | a total of two cities in rizal have a total number of eleven barangays . | {'scope': 'all', 'criterion': 'equal', 'value': '11', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'no of barangays', '11'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no of barangays record is equal to 11 .', 'tostr': 'filter_eq { all_rows ; no of barangays ; 11 }'}], 'result': '2', 'ind': 1, 'tostr': 'cou... | eq { count { filter_eq { all_rows ; no of barangays ; 11 } } ; 2 } = true | select the rows whose no of barangays record is equal to 11 . 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, 'no of barangays_5': 5, '11_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'no of barangays_5': 'no of barangays', '11_6': '11', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'no of barangays_5': [0], '11_6': [0], '2_7': [2]} | ['city / municipality', 'no of barangays', 'area ( km square )', 'population ( 2010 census )', 'pop density ( per km square )'] | [['angono', '10', '26.22', '102407', '3905.68'], ['antipolo', '16', '306.10', '677741', '2214.12'], ['baras', '10', '84.93', '32609', '383.95'], ['binangonan', '40', '66.34', '249872', '3766.54'], ['cainta', '7', '42.99', '311845', '7253.90'], ['cardona', '18', '28.56', '47414', '1660.15'], ['jalajala', '11', '44.12', ... |
southeast asian games | https://en.wikipedia.org/wiki/Southeast_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1575383-9.html.csv | majority | in the southeast asian games , for the countries that won over 200 gold medals , all of them won over 1000 total medals . | {'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '1000', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '200'}} | {'func': 'all_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gold', '200'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; gold ; 200 }', 'tointer': 'select the rows whose gold record is greater than 200 .'}, 'total', '1000'], 'result': True, 'ind': 1, 'tointer': 'select the rows w... | all_greater { filter_greater { all_rows ; gold ; 200 } ; total ; 1000 } = true | select the rows whose gold record is greater than 200 . for the total records of these rows , all of them are greater than 1000 . | 2 | 2 | {'all_greater_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'gold_4': 4, '200_5': 5, 'total_6': 6, '1000_7': 7} | {'all_greater_1': 'all_greater', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '200_5': '200', 'total_6': 'total', '1000_7': '1000'} | {'all_greater_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'gold_4': [0], '200_5': [0], 'total_6': [1], '1000_7': [1]} | ['country', 'gold', 'silver', 'bronze', 'total'] | [['indonesia', '1602', '1413', '1395', '4410'], ['thailand', '1513', '1318', '1315', '4146'], ['philippines', '836', '971', '1191', '2998'], ['malaysia', '805', '772', '1067', '2644'], ['vietnam', '586', '540', '618', '1744'], ['singapore', '508', '559', '841', '1906'], ['myanmar', '249', '410', '579', '1238'], ['laos'... |
persons unknown ( tv series ) | https://en.wikipedia.org/wiki/Persons_Unknown_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25084227-1.html.csv | count | according to the list of episodes of persons unknown ( tv series ) , two of the episodes directed by jonathan frakes were written by linda mcgibney . | {'scope': 'subset', 'criterion': 'equal', 'value': 'linda mcgibney', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'jonathan frakes'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'jonathan frakes'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; directed by ; jonathan frakes }', 'tointer': 'select the rows whose directed by record fuzzil... | eq { count { filter_eq { filter_eq { all_rows ; directed by ; jonathan frakes } ; written by ; linda mcgibney } } ; 2 } = true | select the rows whose directed by record fuzzily matches to jonathan frakes . among these rows , select the rows whose written by record fuzzily matches to linda mcgibney . 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, 'directed by_6': 6, 'jonathan frakes_7': 7, 'written by_8': 8, 'linda mcgibney_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', 'directed by_6': 'directed by', 'jonathan frakes_7': 'jonathan frakes', 'written by_8': 'written by', 'linda mcgibney_9': 'linda mcgibney', '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], 'directed by_6': [0], 'jonathan frakes_7': [0], 'written by_8': [1], 'linda mcgibney_9': [1], '2_10': [3]} | ['no', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( in millions )'] | [['1', 'pilot', 'michael rymer', 'christopher mcquarrie', 'june 7 , 2010', '4002 - 08 - 101', '4.29'], ['2', 'the edge', 'bill eagles', 'remi aubuchon', 'june 14 , 2010', '4002 - 08 - 102', '3.45'], ['3', 'the way through', 'bill eagles', 'sandy isaac', 'june 21 , 2010', '4002 - 08 - 103', '3.43'], ['4', 'exit one', 'l... |
hunt - class mine countermeasures vessel | https://en.wikipedia.org/wiki/Hunt-class_mine_countermeasures_vessel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1162013-1.html.csv | ordinal | ledbury is the second oldest commissioned hunt - class mine countermeasures vessel . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'commissioned', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; commissioned ; 2 }'}, 'name'], 'result': 'ledbury', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; commissioned ; 2 } ; name }'}, 'led... | eq { hop { nth_argmin { all_rows ; commissioned ; 2 } ; name } ; ledbury } = true | select the row whose commissioned record of all rows is 2nd minimum . the name record of this row is ledbury . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'commissioned_5': 5, '2_6': 6, 'name_7': 7, 'ledbury_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', 'commissioned_5': 'commissioned', '2_6': '2', 'name_7': 'name', 'ledbury_8': 'ledbury'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'commissioned_5': [0], '2_6': [0], 'name_7': [1], 'ledbury_8': [2]} | ['navy', 'name', 'pennant', 'commissioned', 'home port'] | [['royal navy', 'brecon', 'm29', '1980', 'hms raleigh'], ['royal navy', 'ledbury', 'm30', '1981', 'portsmouth'], ['royal navy', 'cattistock', 'm31', '1982', 'portsmouth'], ['royal navy', 'cottesmore', 'm32', '1983', 'portsmouth'], ['royal navy', 'brocklesby', 'm33', '1982', 'portsmouth'], ['royal navy', 'middleton', 'm... |
selima sfar | https://en.wikipedia.org/wiki/Selima_Sfar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13604859-2.html.csv | ordinal | selima sfar won her second final in the tournament in moulins . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'tournament'], 'result': 'moulins', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; tournament }'}, 'moulins'], 'res... | eq { hop { nth_argmin { all_rows ; date ; 2 } ; tournament } ; moulins } = true | select the row whose date record of all rows is 2nd minimum . the tournament record of this row is moulins . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'tournament_7': 7, 'moulins_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'tournament_7': 'tournament', 'moulins_8': 'moulins'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'tournament_7': [1], 'moulins_8': [2]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['august 14 , 1994', 'carthage', 'clay', 'anne - gaëlle sidot', '5 - 7 6 - 3 6 - 4'], ['march 26 , 1995', 'moulins', 'hard indoors', 'linda sentis', '3 - 6 6 - 3 6 - 2'], ['november 26 , 1995', 'le havre', 'clay indoors', 'émilie loit', '0 - 6 6 - 3 6 - 4'], ['february 4 , 1996', 'dinan', 'clay indoors', 'virginie mas... |
list of football clubs in hong kong | https://en.wikipedia.org/wiki/List_of_football_clubs_in_Hong_Kong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18408905-13.html.csv | majority | most of the football clubs in hong kong are in the first division . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'first division', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'league / division', 'first division'], 'result': True, 'ind': 0, 'tointer': 'for the league / division records of all rows , most of them fuzzily match to first division .', 'tostr': 'most_eq { all_rows ; league / division ; first division } = true'} | most_eq { all_rows ; league / division ; first division } = true | for the league / division records of all rows , most of them fuzzily match to first division . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'league / division_3': 3, 'first division_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'league / division_3': 'league / division', 'first division_4': 'first division'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'league / division_3': [0], 'first division_4': [0]} | ['club', 'league / division', 'home ground', 'location', 'position in 2012 - 13'] | [['sai kung', 'fourth division', 'n / a', 'n / a', '7th , fourth division'], ['sai kung friends', 'fourth division', 'n / a', 'n / a', '5th , fourth division'], ['sham shui po', 'third division', 'n / a', 'n / a', '11th , second division ( relegated )'], ['shatin', 'second division', 'ma on shan recreation ground', 'ma... |
1982 atlanta falcons season | https://en.wikipedia.org/wiki/1982_Atlanta_Falcons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16710829-2.html.csv | comparative | the atlanta falcons had a game against the los angeles raiders earlier than the st louis cardinals in the 1982 season . | {'row_1': '2', 'row_2': '4', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'los angeles raiders'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to los angeles raiders .', 'tostr': 'filter_eq { all_rows ; opponent ; los angeles raiders... | less { hop { filter_eq { all_rows ; opponent ; los angeles raiders } ; date } ; hop { filter_eq { all_rows ; opponent ; st louis cardinals } ; date } } = true | select the rows whose opponent record fuzzily matches to los angeles raiders . take the date record of this row . select the rows whose opponent record fuzzily matches to st louis cardinals . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'los angeles raiders_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'st louis cardinals_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'los angeles raiders_8': 'los angeles raiders', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': '... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'los angeles raiders_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'st louis cardinals_12': [1], 'date_13': [3]} | ['game', 'date', 'opponent', 'result', 'falcons points', 'opponents', 'record', 'attendance'] | [['1', 'sept 12', 'new york giants', 'win', '16', '14', '1 - 0', '74286'], ['2', 'sept 19', 'los angeles raiders', 'loss', '14', '38', '1 - 1', '54774'], ['3', 'nov 21', 'los angeles rams', 'win', '34', '17', '2 - 1', '39686'], ['4', 'nov 28', 'st louis cardinals', 'loss', '20', '23', '2 - 2', '33411'], ['5', 'dec 5', ... |
list of vehicle speed records | https://en.wikipedia.org/wiki/List_of_vehicle_speed_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16343705-3.html.csv | unique | the schempp-hirth nimbus-4dm was the only vehicle that was manned by two people when achieving its speed record . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': 'and', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pilot', 'and'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pilot record fuzzily matches to and .', 'tostr': 'filter_eq { all_rows ; pilot ; and }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq {... | and { only { filter_eq { all_rows ; pilot ; and } } ; eq { hop { filter_eq { all_rows ; pilot ; and } ; vehicle } ; schempp - hirth nimbus - 4dm } } = true | select the rows whose pilot record fuzzily matches to and . there is only one such row in the table . the vehicle record of this unqiue row is schempp - hirth nimbus - 4dm . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'pilot_7': 7, 'and_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'vehicle_9': 9, 'schempp - hirth nimbus - 4dm_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'pilot_7': 'pilot', 'and_8': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'vehicle_9': 'vehicle', 'schempp - hirth nimbus - 4dm_10': 'schempp - hirth nimbus - 4dm'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'pilot_7': [0], 'and_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'vehicle_9': [2], 'schempp - hirth nimbus - 4dm_10': [3]} | ['category', 'speed ( km / h )', 'speed ( mph )', 'vehicle', 'pilot', 'date'] | [['rocket - powered aircraft', '7258', '4510', 'north american x - 15', 'william j knight', '3 oct 1967'], ['manned air - breathing craft', '3530', '2194', 'lockheed sr - 71 blackbird', 'eldon w joersz', '28 jul 1976'], ['propeller - driven aircraft', '870', '541', 'tupolev tu - 114', 'ivan soukhomline', '00 jan 1960']... |
1930 vfl season | https://en.wikipedia.org/wiki/1930_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10767641-16.html.csv | ordinal | lake oval venue recorded the highest crowd participation during the 1930 vfl season . | {'row': '5', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'lake oval', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'lake oval'], 'result... | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; lake oval } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is lake oval . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'lake oval_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', '1_6': '1', 'venue_7': 'venue', 'lake oval_8': 'lake oval'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'lake oval_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '13.11 ( 89 )', 'melbourne', '12.7 ( 79 )', 'windy hill', '15000', '30 august 1930'], ['collingwood', '16.20 ( 116 )', 'footscray', '10.17 ( 77 )', 'victoria park', '10000', '30 august 1930'], ['carlton', '16.12 ( 108 )', 'st kilda', '15.7 ( 97 )', 'princes park', '20000', '30 august 1930'], ['richmond', ... |
1984 atlanta falcons season | https://en.wikipedia.org/wiki/1984_Atlanta_Falcons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16710742-1.html.csv | aggregation | the average pick number for the 1984 atlanta falcons team was 154 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '154', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pick'], 'result': '154', 'ind': 0, 'tostr': 'avg { all_rows ; pick }'}, '154'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pick } ; 154 } = true', 'tointer': 'the average of the pick record of all rows is 154 .'} | round_eq { avg { all_rows ; pick } ; 154 } = true | the average of the pick record of all rows is 154 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pick_4': 4, '154_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pick_4': 'pick', '154_5': '154'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pick_4': [0], '154_5': [1]} | ['round', 'pick', 'player', 'position', 'school'] | [['1', '9', 'rick bryan', 'defensive end', 'oklahoma'], ['2', '32', 'scott case', 'defensive back', 'oklahoma'], ['2', '36', 'thomas benson', 'linebacker', 'oklahoma'], ['3', '63', 'rod mcswain', 'defensive back', 'clemson'], ['4', '94', 'rydell malancon', 'linebacker', 'louisiana state'], ['5', '132', 'cliff benson', ... |
kei nishikori | https://en.wikipedia.org/wiki/Kei_Nishikori | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12299543-2.html.csv | majority | of the finals that kei nishikori participated in , most of them were on a hard surface . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'date', 'surface', 'opponent in the final', 'score in the final'] | [['winner', '11 february 2008', 'hard', 'james blake', '3 - 6 , 6 - 1 , 6 - 4'], ['runner - up', '10 april 2011', 'clay', 'ryan sweeting', '4 - 6 , 6 - 7 ( 3 - 7 )'], ['runner - up', '6 november 2011', 'hard ( i )', 'roger federer', '1 - 6 , 3 - 6'], ['winner', '7 october 2012', 'hard', 'milos raonic', '7 - 6 ( 7 - 5 )... |
2005 - 06 columbus blue jackets season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Columbus_Blue_Jackets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13242342-5.html.csv | aggregation | the average attendance at columbus blue jackets games was 16013 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '16013', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '16013', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '16013'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 16013 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 16013 } = true | the average of the attendance record of all rows is 16013 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '16013_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '16013_5': '16013'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '16013_5': [1]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 1', 'columbus', '1 - 4', 'st louis', 'leclaire', '12307', '7 - 19 - 0'], ['december 8', 'ny islanders', '3 - 4', 'columbus', 'leclaire', '15728', '8 - 19 - 0'], ['december 9', 'columbus', '2 - 5', 'atlanta', 'leclaire', '14260', '8 - 20 - 0'], ['december 11', 'new jersey', '2 - 3', 'columbus', 'denis', '171... |
south africa | https://en.wikipedia.org/wiki/South_Africa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17416221-1.html.csv | ordinal | the province that has the second highest population in south africa is kwazulu-natal . | {'row': '4', 'col': '5', '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', 'population ( 2013 )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ( 2013 ) ; 2 }'}, 'province'], 'result': 'kwazulu - natal', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; populatio... | eq { hop { nth_argmax { all_rows ; population ( 2013 ) ; 2 } ; province } ; kwazulu - natal } = true | select the row whose population ( 2013 ) record of all rows is 2nd maximum . the province record of this row is kwazulu - natal . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population (2013)_5': 5, '2_6': 6, 'province_7': 7, 'kwazulu - natal_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 (2013)_5': 'population ( 2013 )', '2_6': '2', 'province_7': 'province', 'kwazulu - natal_8': 'kwazulu - natal'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population (2013)_5': [0], '2_6': [0], 'province_7': [1], 'kwazulu - natal_8': [2]} | ['province', 'provincial capital', 'largest city', 'area ( km 2 )', 'population ( 2013 )'] | [['eastern cape', 'bhisho', 'port elizabeth', '168966', '6620100'], ['free state', 'bloemfontein', 'bloemfontein', '129825', '2753200'], ['gauteng', 'johannesburg', 'johannesburg', '18178', '12728400'], ['kwazulu - natal', 'pietermaritzburg', 'durban', '94361', '10456900'], ['limpopo', 'polokwane', 'polokwane', '125754... |
stefano modena | https://en.wikipedia.org/wiki/Stefano_Modena | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226330-2.html.csv | unique | 1991 in the braun tyrell honda is the only event where stafano modena managed 10 points . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': '10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; points ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ;... | and { only { filter_eq { all_rows ; points ; 10 } } ; eq { hop { filter_eq { all_rows ; points ; 10 } ; entrant } ; braun tyrrell honda } } = true | select the rows whose points record is equal to 10 . there is only one such row in the table . the entrant record of this unqiue row is braun tyrrell honda . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'points_7': 7, '10_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'entrant_9': 9, 'braun tyrrell honda_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'points_7': 'points', '10_8': '10', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'entrant_9': 'entrant', 'braun tyrrell honda_10': 'braun tyrrell honda'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '10_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'entrant_9': [2], 'braun tyrrell honda_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1987', 'motor racing developments', 'brabham bt56', 'bmw str - 4', '0'], ['1988', 'eurobrun racing', 'eurobrun er188', 'cosworth v8', '0'], ['1989', 'motor racing developments', 'brabham bt58', 'judd v8', '4'], ['1990', 'motor racing developments', 'brabham bt58', 'judd v8', '2'], ['1990', 'motor racing developments... |
2011 - 12 la liga | https://en.wikipedia.org/wiki/2011%E2%80%9312_La_Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29398373-2.html.csv | unique | caja granada only sponsored the granada football club in the 2011-12 season of la liga . | {'scope': 'all', 'row': '7', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'caja granada', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shirt sponsor', 'caja granada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shirt sponsor record fuzzily matches to caja granada .', 'tostr': 'filter_eq { all_rows ; shirt sponsor ; caja granada }'}], 're... | and { only { filter_eq { all_rows ; shirt sponsor ; caja granada } } ; eq { hop { filter_eq { all_rows ; shirt sponsor ; caja granada } ; team } ; granada } } = true | select the rows whose shirt sponsor record fuzzily matches to caja granada . there is only one such row in the table . the team record of this unqiue row is granada . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'shirt sponsor_7': 7, 'caja granada_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'granada_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'shirt sponsor_7': 'shirt sponsor', 'caja granada_8': 'caja granada', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'granada_10': 'granada'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'shirt sponsor_7': [0], 'caja granada_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'granada_10': [3]} | ['team', 'chairman', 'head coach', 'captain', 'kitmaker', 'shirt sponsor'] | [['athletic bilbao', 'josu urrutia', 'marcelo bielsa', 'carlos gurpegui', 'umbro', 'petronor'], ['atlético madrid', 'enrique cerezo', 'diego simeone', 'antonio lópez', 'nike', 'rixos hotels , huawei , and kyocera'], ['barcelona', 'sandro rosell', 'josep guardiola', 'carles puyol', 'nike', 'qatar foundation and unicef']... |
senate of canada | https://en.wikipedia.org/wiki/Senate_of_Canada | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-123498-4.html.csv | aggregation | the average number of members in senate of canada from 1867 to 1999 was 88 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '88', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'normal total'], 'result': '88', 'ind': 0, 'tostr': 'avg { all_rows ; normal total }'}, '88'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; normal total } ; 88 } = true', 'tointer': 'the average of the normal total record of all rows ... | round_eq { avg { all_rows ; normal total } ; 88 } = true | the average of the normal total record of all rows is 88 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'normal total_4': 4, '88_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'normal total_4': 'normal total', '88_5': '88'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'normal total_4': [0], '88_5': [1]} | ['date enacted', 'normal total', 'ยง26 total', 'ont', 'que', 'ns', 'nb'] | [['july 1 , 1867', '72', '78', '24', '24', '12', '12'], ['july 15 , 1870', '74', '80', '24', '24', '12', '12'], ['july 20 , 1871', '77', '83', '24', '24', '12', '12'], ['july 1 , 1873', '77', '83', '24', '24', '10', '10'], ['september 1 , 1905', '85', '91', '24', '24', '10', '10'], ['may 19 , 1915', '96', '104', '24', ... |
henlopen conference | https://en.wikipedia.org/wiki/Henlopen_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-17.html.csv | aggregation | looking at their overall records , the teams of the henlopen conference averaged just over five wins each . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'overall record'], 'result': '5', 'ind': 0, 'tostr': 'avg { all_rows ; overall record }'}, '5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; overall record } ; 5 } = true', 'tointer': 'the average of the overall record record of all ... | round_eq { avg { all_rows ; overall record } ; 5 } = true | the average of the overall record record of all rows is 5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'overall record_4': 4, '5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'overall record_4': 'overall record', '5_5': '5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'overall record_4': [0], '5_5': [1]} | ['school', 'team', 'division record', 'overall record', 'season outcome'] | [['sussex central', 'golden knights', '6 - 0', '7 - 4', 'loss in first round of div i playoffs'], ['dover', 'senators', '5 - 1', '8 - 4', 'loss in semi - finals of div i playoffs'], ['cape henlopen', 'vikings', '4 - 2', '8 - 2', 'failed to make playoffs'], ['caesar rodney', 'riders', '3 - 3', '3 - 7', 'failed to make p... |
york county , new brunswick | https://en.wikipedia.org/wiki/York_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-176533-2.html.csv | ordinal | in york county , new brunswick , douglas has the highest area km 2 among those with population more than 4000 . | {'scope': 'subset', 'row': '2', 'col': '3', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '4000'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'population', '4000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; population ; 4000 }', 'tointer': 'select the rows whose population record is greater than 4000 .... | eq { hop { nth_argmax { filter_greater { all_rows ; population ; 4000 } ; area km 2 ; 1 } ; official name } ; douglas } = true | select the rows whose population record is greater than 4000 . select the row whose area km 2 record of these rows is 1st maximum . the official name record of this row is douglas . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'population_6': 6, '4000_7': 7, 'area km 2_8': 8, '1_9': 9, 'official name_10': 10, 'douglas_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'population_6': 'population', '4000_7': '4000', 'area km 2_8': 'area km 2', '1_9': '1', 'official name_10': 'official name', 'douglas_11': 'douglas'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'population_6': [0], '4000_7': [0], 'area km 2_8': [1], '1_9': [1], 'official name_10': [2], 'douglas_11': [3]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['kingsclear', 'parish', '303.26', '6689', '545 of 5008'], ['douglas', 'parish', '1446.50', '5774', '609 of 5008'], ['saint marys', 'parish', '753.06', '4224', '767 of 5008'], ['bright', 'parish', '404.00', '3159', '958 of 5008'], ['new maryland', 'parish', '375.40', '2348', '1193 of 5008'], ['manners sutton', 'parish... |
rovers cup | https://en.wikipedia.org/wiki/Rovers_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14645146-1.html.csv | majority | most of the teams with at least 5 wins in the rover cup were last runners-up in 1987 or later . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1987', 'subset': {'col': '2', 'criterion': 'greater_than_eq', 'value': '5'}} | {'func': 'most_greater_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'wins', '5'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; wins ; 5 }', 'tointer': 'select the rows whose wins record is greater than or equal to 5 .'}, 'last runners - up', '1987'], 'result': True, 'ind': 1, '... | most_greater_eq { filter_greater_eq { all_rows ; wins ; 5 } ; last runners - up ; 1987 } = true | select the rows whose wins record is greater than or equal to 5 . for the last runners - up records of these rows , most of them are greater than or equal to 1987 . | 2 | 2 | {'most_greater_eq_1': 1, 'result_2': 2, 'filter_greater_eq_0': 0, 'all_rows_3': 3, 'wins_4': 4, '5_5': 5, 'last runners - up_6': 6, '1987_7': 7} | {'most_greater_eq_1': 'most_greater_eq', 'result_2': 'true', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '5_5': '5', 'last runners - up_6': 'last runners - up', '1987_7': '1987'} | {'most_greater_eq_1': [2], 'result_2': [], 'filter_greater_eq_0': [1], 'all_rows_3': [0], 'wins_4': [0], '5_5': [0], 'last runners - up_6': [1], '1987_7': [1]} | ['club', 'wins', 'last win', 'runners - up', 'last runners - up'] | [['mohun bagan ac', '14', '2000 - 01', '10', '1987'], ['east bengal club', '10', '1994', '4', '1988'], ['hyderabad police', '9', '1963', '1', '1943'], ['mohammedan sporting club', '6', '1987', '9', '1991'], ['dempo sc', '4', '1986', '1', '1989'], ['bangalore muslims', '3', '1948', '2', '1953'], ['salgaocar sc', '3', '1... |
english cricket team in australia in 1911 - 12 | https://en.wikipedia.org/wiki/English_cricket_team_in_Australia_in_1911%E2%80%9312 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17470911-1.html.csv | aggregation | 456 is the sum of the results for the english cricket team in australia in 1911 - 12 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '456', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'result'], 'result': '456', 'ind': 0, 'tostr': 'sum { all_rows ; result }'}, '456'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; result } ; 456 } = true', 'tointer': 'the sum of the result record of all rows is 456 .'} | round_eq { sum { all_rows ; result } ; 456 } = true | the sum of the result record of all rows is 456 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'result_4': 4, '456_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'result_4': 'result', '456_5': '456'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'result_4': [0], '456_5': [1]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['15 , 16 , 18 , 19 , 20 , 21 dec 1911', 'clem hill', 'johnny douglas', 'sydney cricket ground', 'aus by 146 runs'], ['30 dec , 1 , 2 , 3 jan 1911 / 2', 'clem hill', 'johnny douglas', 'melbourne cricket ground', 'eng by 8 wkts'], ['12 , 13 , 15 , 16 , 17 jan 1912', 'clem hill', 'johnny douglas', 'adelaide oval', 'eng ... |
asian youth volleyball championship | https://en.wikipedia.org/wiki/Asian_Youth_Volleyball_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16744545-5.html.csv | ordinal | the rank 2 country in the asian youth volleyball championship received the second most bronze medals . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'bronze', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; bronze ; 2 }'}, 'rank'], 'result': '2', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 2 } ; rank }'}, '2'], 'result': True, 'ind':... | eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; rank } ; 2 } = true | select the row whose bronze record of all rows is 2nd maximum . the rank record of this row is 2 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '2_6': 6, 'rank_7': 7, '2_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', '2_6': '2', 'rank_7': 'rank', '2_8': '2'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '2_6': [0], 'rank_7': [1], '2_8': [2]} | ['rank', 'gold', 'silver', 'bronze', 'total'] | [['1', '5', '2', '0', '7'], ['2', '4', '3', '2', '9'], ['3', '0', '3', '1', '4'], ['4', '0', '1', '0', '1'], ['5', '0', '0', '3', '3'], ['total', '9', '9', '9', '27']] |
2005 world women 's curling championship | https://en.wikipedia.org/wiki/2005_World_Women%27s_Curling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1554808-2.html.csv | majority | in the 2005 world women 's curling championship the majority of teams had a shot percentage over 65 % . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '65 %', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'shot pct', '65 %'], 'result': True, 'ind': 0, 'tointer': 'for the shot pct records of all rows , most of them are greater than 65 % .', 'tostr': 'most_greater { all_rows ; shot pct ; 65 % } = true'} | most_greater { all_rows ; shot pct ; 65 % } = true | for the shot pct records of all rows , most of them are greater than 65 % . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'shot pct_3': 3, '65%_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'shot pct_3': 'shot pct', '65%_4': '65 %'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'shot pct_3': [0], '65%_4': [0]} | ['locale', 'skip', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot pct'] | [['sweden', 'anette norberg', '56', '39', '11', '25', '75 %'], ['united states', 'cassandra johnson', '53', '38', '13', '22', '76 %'], ['canada', 'jennifer jones', '48', '45', '3', '21', '68 %'], ['norway', 'dordi nordby', '46', '40', '11', '19', '72 %'], ['russia', 'olga jarkova', '47', '45', '17', '10', '70 %'], ['sc... |
2009 world championships in athletics - men 's 1500 metres | https://en.wikipedia.org/wiki/2009_World_Championships_in_Athletics_%E2%80%93_Men%27s_1500_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23987362-2.html.csv | unique | the world record is the only record to be set in germany . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'germany', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rome , italy', 'germany'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rome , italy record fuzzily matches to germany .', 'tostr': 'filter_eq { all_rows ; rome , italy ; germany }'}], 'result': True, 'ind'... | and { only { filter_eq { all_rows ; rome , italy ; germany } } ; eq { hop { filter_eq { all_rows ; rome , italy ; germany } ; world record } ; world leading } } = true | select the rows whose rome , italy record fuzzily matches to germany . there is only one such row in the table . the world record record of this unqiue row is world leading . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'rome , italy_7': 7, 'germany_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'world record_9': 9, 'world leading_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'rome , italy_7': 'rome , italy', 'germany_8': 'germany', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'world record_9': 'world record', 'world leading_10': 'world leading'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'rome , italy_7': [0], 'germany_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'world record_9': [2], 'world leading_10': [3]} | ['world record', 'hicham el guerrouj ( mar )', '3:26.00', 'rome , italy', '14 july 1998'] | [['championship record', 'hicham el guerrouj ( mar )', '3:27.65', 'seville , spain', '14 august 1999'], ['world leading', 'augustine choge ( ken )', '3:29.47', 'berlin , germany', '14 june 2009'], ['african record', 'hicham el guerrouj ( mar )', '3:26.00', 'rome , italy', '14 july 1998'], ['asian record', 'rashid ramzi... |
marinne giraud | https://en.wikipedia.org/wiki/Marinne_Giraud | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15508602-2.html.csv | majority | the majority of marinne giraud 's tennis tournaments were on a hard surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['winner', '24 - oct - 2005', 'pretoria', 'hard', 'alicia pillay', '6 - 4 6 - 2'], ['runner - up', '09 - oct - 2006', 'braga', 'carpet', 'eloisa compostizo de andres', '4 - 6 , 7 - 5 , 3 - 6'], ['winner', '14 april 2007', 'dubai', 'hard', 'çağla büyükakçay', '6 - 2 6 - 2'], ['winner', '14 - may - 2007', 'trivandrum', ... |
lorenzo bandini | https://en.wikipedia.org/wiki/Lorenzo_Bandini | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226484-1.html.csv | unique | lorenzo bandini used a cooper t53 chassis only in the 1961 season . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'cooper t53', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'cooper t53'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to cooper t53 .', 'tostr': 'filter_eq { all_rows ; chassis ; cooper t53 }'}], 'result': True, 'ind': 1, '... | and { only { filter_eq { all_rows ; chassis ; cooper t53 } } ; eq { hop { filter_eq { all_rows ; chassis ; cooper t53 } ; year } ; 1961 } } = true | select the rows whose chassis record fuzzily matches to cooper t53 . there is only one such row in the table . the year record of this unqiue row is 1961 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'chassis_7': 7, 'cooper t53_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1961_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'chassis_7': 'chassis', 'cooper t53_8': 'cooper t53', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1961_10': '1961'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'chassis_7': [0], 'cooper t53_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1961_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1961', 'scuderia centro sud', 'cooper t53', 'maserati straight - 4', '0'], ['1962', 'scuderia ferrari', 'ferrari 156', 'ferrari v6', '4'], ['1963', 'scuderia centro sud', 'brm p57', 'brm v8', '6'], ['1963', 'scuderia ferrari', 'ferrari 156', 'ferrari v6', '6'], ['1964', 'scuderia ferrari', 'ferrari 156', 'ferrari v6... |
1968 buffalo bills season | https://en.wikipedia.org/wiki/1968_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16982985-3.html.csv | aggregation | in the 1968 buffalo bills season , the average attendance for games in september was 36092.5 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '36092.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '36092.5', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '36092.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 36092.5 } = true', 'tointer': 'the average of the attendance record of al... | round_eq { avg { all_rows ; attendance } ; 36092.5 } = true | the average of the attendance record of all rows is 36092.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '36092.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '36092.5_5': '36092.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '36092.5_5': [1]} | ['date', 'opponent', 'score', 'result', 'record', 'attendance'] | [['september 8', 'boston patriots', '16 - 7', 'loss', '0 - 1', '38865'], ['september 15', 'oakland raiders', '48 - 6', 'loss', '0 - 2', '43056'], ['september 22', 'cincinnati bengals', '34 - 23', 'loss', '0 - 3', '24405'], ['september 29', 'new york jets', '37 - 35', 'win', '1 - 3', '38044'], ['october 5', 'kansas city... |
dorval | https://en.wikipedia.org/wiki/Dorval | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-189893-1.html.csv | ordinal | in 2011 , the third highest population group in dorval were those who spoke spanish as their mother tongue . | {'row': '5', 'col': '4', '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 ( 2011 )', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ( 2011 ) ; 3 }'}, 'mother tongue'], 'result': 'spanish', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population (... | eq { hop { nth_argmax { all_rows ; population ( 2011 ) ; 3 } ; mother tongue } ; spanish } = true | select the row whose population ( 2011 ) record of all rows is 3rd maximum . the mother tongue record of this row is spanish . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population (2011)_5': 5, '3_6': 6, 'mother tongue_7': 7, 'spanish_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 (2011)_5': 'population ( 2011 )', '3_6': '3', 'mother tongue_7': 'mother tongue', 'spanish_8': 'spanish'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population (2011)_5': [0], '3_6': [0], 'mother tongue_7': [1], 'spanish_8': [2]} | ['mother tongue', 'population ( 2006 )', 'percentage ( 2006 )', 'population ( 2011 )', 'percentage ( 2011 )'] | [['english', '8085', '45.22 %', '7615', '42.41 %'], ['french', '5400', '30.20 %', '5490', '30.57 %'], ['chinese languages', '650', '3.64 %', '470', '2.62 %'], ['italian', '590', '3.30 %', '510', '2.84 %'], ['spanish', '315', '1.76 %', '515', '2.87 %'], ['romanian', '300', '1.68 %', '235', '1.31 %'], ['arabic', '295', '... |
outcasts ( tv series ) | https://en.wikipedia.org/wiki/Outcasts_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29574579-1.html.csv | ordinal | episode 4 had the 5th highest amount of uk viewers of all outcasts episodes . | {'row': '4', 'col': '5', 'order': '5', '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', 'uk viewers ( million )', '5'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; uk viewers ( million ) ; 5 }'}, 'title'], 'result': 'episode 4', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; uk viewers (... | eq { hop { nth_argmax { all_rows ; uk viewers ( million ) ; 5 } ; title } ; episode 4 } = true | select the row whose uk viewers ( million ) record of all rows is 5th maximum . the title record of this row is episode 4 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'uk viewers (million)_5': 5, '5_6': 6, 'title_7': 7, 'episode 4_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', 'uk viewers (million)_5': 'uk viewers ( million )', '5_6': '5', 'title_7': 'title', 'episode 4_8': 'episode 4'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'uk viewers (million)_5': [0], '5_6': [0], 'title_7': [1], 'episode 4_8': [2]} | ['episode', 'title', 'directed by', 'written by', 'uk viewers ( million )', 'share ( % )', 'original air date'] | [['1', 'episode 1', 'bharat nalluri', 'ben richards', '4.50', '17.9', '7 february 2011'], ['2', 'episode 2', 'bharat nalluri', 'ben richards', '3.30', '13.0', '8 february 2011'], ['3', 'episode 3', 'omar madha', 'ben richards and simon block', '2.95', '11.8', '14 february 2011'], ['4', 'episode 4', 'omar madha', 'jack ... |
list of countries with mcdonald 's restaurants | https://en.wikipedia.org/wiki/List_of_countries_with_McDonald%27s_restaurants | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1875327-2.html.csv | count | two of the mcdonald 's restaurants opened in the continent of asia . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'asia', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'continent', 'asia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose continent record fuzzily matches to asia .', 'tostr': 'filter_eq { all_rows ; continent ; asia }'}], 'result': '2', 'ind': 1, 'tostr': 'coun... | eq { count { filter_eq { all_rows ; continent ; asia } } ; 2 } = true | select the rows whose continent record fuzzily matches to asia . 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, 'continent_5': 5, 'asia_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', 'continent_5': 'continent', 'asia_6': 'asia', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'continent_5': [0], 'asia_6': [0], '2_7': [2]} | ['continent', 'location', 'city', 'date', 'year'] | [['north america', 'united states', 'san bernardino', 'may 15', '1940'], ['caribbean', 'puerto rico', 'san juan', 'november 10', '1967'], ['central america', 'costa rica', 'san josã', 'december 28', '1970'], ['oceania', 'australia', 'sydney', 'may 30', '1971'], ['asia 1', 'japan', 'tokyo', 'july 20', '1971'], ['europe'... |
jean - christophe boullion | https://en.wikipedia.org/wiki/Jean-Christophe_Boullion | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235885-4.html.csv | majority | on the majority of occasions when jean - christophe boullion was driving for pescarolo sport the team completed more than 300 laps . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '300', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'pescarolo sport'}} | {'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'pescarolo sport'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; pescarolo sport }', 'tointer': 'select the rows whose team record fuzzily matches to pescarolo sport .'}, 'laps', '300'], 'result': True, 'ind': ... | most_greater { filter_eq { all_rows ; team ; pescarolo sport } ; laps ; 300 } = true | select the rows whose team record fuzzily matches to pescarolo sport . for the laps records of these rows , most of them are greater than 300 . | 2 | 2 | {'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'team_4': 4, 'pescarolo sport_5': 5, 'laps_6': 6, '300_7': 7} | {'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'team_4': 'team', 'pescarolo sport_5': 'pescarolo sport', 'laps_6': 'laps', '300_7': '300'} | {'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'team_4': [0], 'pescarolo sport_5': [0], 'laps_6': [1], '300_7': [1]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1994', 'michel hommell', 'alain cudini eric hélary', 'gt1', '230', 'dnf', 'dnf'], ['1997', 'dams', 'franck lagorce éric bernard', 'gt1', '149', 'dnf', 'dnf'], ['1998', 'jb racing', 'vincenzo sospiri jérôme policand', 'lmp1', '187', 'dnf', 'dnf'], ['2000', 'racing organisation course', 'jordi gené jérôme policand', '... |
york county , new brunswick | https://en.wikipedia.org/wiki/York_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-176533-2.html.csv | count | in york county , new brunswick , 4 of those with area km 2 more than 500 has population more than 1000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '1000', 'result': '4', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '500'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'area km 2', '500'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; area km 2 ; 500 }', 'tointer': 'select the rows whose area km 2 record is greater than 500 .'}, 'pop... | eq { count { filter_greater { filter_greater { all_rows ; area km 2 ; 500 } ; population ; 1000 } } ; 4 } = true | select the rows whose area km 2 record is greater than 500 . among these rows , select the rows whose population record is greater than 1000 . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'area km 2_6': 6, '500_7': 7, 'population_8': 8, '1000_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'area km 2_6': 'area km 2', '500_7': '500', 'population_8': 'population', '1000_9': '1000', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'area km 2_6': [0], '500_7': [0], 'population_8': [1], '1000_9': [1], '4_10': [3]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['kingsclear', 'parish', '303.26', '6689', '545 of 5008'], ['douglas', 'parish', '1446.50', '5774', '609 of 5008'], ['saint marys', 'parish', '753.06', '4224', '767 of 5008'], ['bright', 'parish', '404.00', '3159', '958 of 5008'], ['new maryland', 'parish', '375.40', '2348', '1193 of 5008'], ['manners sutton', 'parish... |
antonio ng | https://en.wikipedia.org/wiki/Antonio_Ng | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14834801-1.html.csv | unique | 2005 was the only election year in which antonio ng received a hare quota score of over 10000 . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'greater_than', 'value': '10000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'hare quota', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose hare quota record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; hare quota ; 10000 }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_greater { all_rows ; hare quota ; 10000 } } ; eq { hop { filter_greater { all_rows ; hare quota ; 10000 } ; year } ; 2005 } } = true | select the rows whose hare quota record is greater than 10000 . there is only one such row in the table . the year record of this unqiue row is 2005 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'hare quota_7': 7, '10000_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2005_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'hare quota_7': 'hare quota', '10000_8': '10000', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2005_10': '2005'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'hare quota_7': [0], '10000_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2005_10': [3]} | ['year', 'candidate', 'hare quota', 'mandate', 'list votes', 'list pct'] | [['1992', 'antónio ng ( anmd )', '3412', '№ 4', '3412', '12.39 %'], ['1996', 'antónio ng ( amdp )', '6331', '№ 6', '6331', '8.73 %'], ['2001', 'antónio ng ( amdp )', '8481', '№ 1', '16961', '20.95 %'], ['2005', 'antónio ng ( amdp )', '11745', '№ 1', '23489', '18.80 %'], ['2009', 'antónio ng ( apmd )', '8212', '№ 3', '1... |
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