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1971 central american and caribbean championships in athletics | https://en.wikipedia.org/wiki/1971_Central_American_and_Caribbean_Championships_in_Athletics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14417813-3.html.csv | majority | at the 1971 central american and caribbean championships in athletics , of the countries that won gold medals , most of them won under 10 silver medals . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '0'}} | {'func': 'most_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gold', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; gold ; 0 }', 'tointer': 'select the rows whose gold record is greater than 0 .'}, 'total', '10'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose gold ... | most_less { filter_greater { all_rows ; gold ; 0 } ; total ; 10 } = true | select the rows whose gold record is greater than 0 . for the total records of these rows , most of them are less than 10 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'gold_4': 4, '0_5': 5, 'total_6': 6, '10_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '0_5': '0', 'total_6': 'total', '10_7': '10'} | {'most_less_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'gold_4': [0], '0_5': [0], 'total_6': [1], '10_7': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'cuba', '22', '19', '10', '51'], ['2', 'jamaica', '9', '6', '7', '22'], ['3', 'mexico', '3', '4', '4', '11'], ['4', 'venezuela', '2', '1', '5', '8'], ['5', 'puerto rico', '1', '7', '4', '12'], ['6', 'trinidad and tobago', '1', '0', '3', '4'], ['7', 'guatemala', '0', '1', '0', '1'], ['8', 'suriname', '0', '0', '2... |
grado labs | https://en.wikipedia.org/wiki/Grado_Labs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1601027-1.html.csv | comparative | the grado labs ps500 and ps1000 both use the same headphone class , professional . | {'row_1': '10', 'row_2': '11', 'col': '2', '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', 'headphone model', 'ps500'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose headphone model record fuzzily matches to ps500 .', 'tostr': 'filter_eq { all_rows ; headphone model ;... | and { eq { hop { filter_eq { all_rows ; headphone model ; ps500 } ; headphone class } ; hop { filter_eq { all_rows ; headphone model ; ps1000 } ; headphone class } } ; and { eq { hop { filter_eq { all_rows ; headphone model ; ps500 } ; headphone class } ; professional } ; eq { hop { filter_eq { all_rows ; headphone mod... | select the rows whose headphone model record fuzzily matches to ps500 . take the headphone class record of this row . select the rows whose headphone model record fuzzily matches to ps1000 . take the headphone class record of this row . the first record fuzzily matches to the second record . the headphone class record ... | 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, 'headphone model_11': 11, 'ps500_12': 12, 'headphone class_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'headphone model_15': 15, 'ps1000_16': 16, 'headphone class_17': 17, 'and_7': 7, 'str_eq_5': 5,... | {'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', 'headphone model_11': 'headphone model', 'ps500_12': 'ps500', 'headphone class_13': 'headphone class', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_1... | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'headphone model_11': [0], 'ps500_12': [0], 'headphone class_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'headphone model_15': [1], 'ps1000_16': [1], 'headphone class_17': [3],... | ['headphone model', 'headphone class', 'driver - matched db', 'construction', 'earpads', 'termination', 'us msrp'] | [['igrado', 'prestige', '0.1', 'plastic', 'comfort pads', '1 / 8 ( 3.5 mm ) plug', '49'], ['sr60i', 'prestige', '0.1', 'plastic', 'comfort pads', '1 / 8 ( 3.5 mm ) plug with 1 / 4 adaptor', '79'], ['sr80i', 'prestige', '0.1', 'plastic', 'comfort pads', '1 / 8 ( 3.5 mm ) plug with 1 / 4 adaptor', '99'], ['sr125i', 'pres... |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-20.html.csv | majority | all of the incumbents were re-elected in the year 1954 . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 're-elected', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , all of them fuzzily match to re-elected .', 'tostr': 'all_eq { all_rows ; result ; re-elected } = true'} | all_eq { all_rows ; result ; re-elected } = true | for the result records of all rows , all of them fuzzily match to re-elected . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're-elected_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're-elected_4': 're-elected'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're-elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['massachusetts 1', 'john w heselton', 'republican', '1944', 're - elected', 'john w heselton ( r ) 55.6 % john j dwyer ( d ) 44.4 %'], ['massachusetts 3', 'philip philbin', 'democratic', '1942', 're - elected', 'philip philbin ( d ) unopposed'], ['massachusetts 5', 'edith nourse rogers', 'republican', '1925', 're - e... |
north american soccer league ( 1968 - 84 ) | https://en.wikipedia.org/wiki/North_American_Soccer_League_%281968%E2%80%9384%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-237757-3.html.csv | comparative | the new york cosmos scored more points in the 1980 north american soccer league season than the 1982 season . | {'row_1': '13', 'row_2': '15', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1980'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1980 .', 'tostr': 'filter_eq { all_rows ; year ; 1980 }'}, 'top team in regular season ( points )'], 'resul... | greater { hop { filter_eq { all_rows ; year ; 1980 } ; top team in regular season ( points ) } ; hop { filter_eq { all_rows ; year ; 1982 } ; top team in regular season ( points ) } } = true | select the rows whose year record fuzzily matches to 1980 . take the top team in regular season ( points ) record of this row . select the rows whose year record fuzzily matches to 1982 . take the top team in regular season ( points ) 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, 'year_7': 7, '1980_8': 8, 'top team in regular season (points)_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1982_12': 12, 'top team in regular season (points)_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', 'year_7': 'year', '1980_8': '1980', 'top team in regular season (points)_9': 'top team in regular season ( points )', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_1... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1980_8': [0], 'top team in regular season (points)_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1982_12': [1], 'top team in regular season (points)_13': [3]} | ['year', 'winner ( number of titles )', 'runners - up', 'top team in regular season ( points )', 'top scorer ( points )', 'winning coach'] | [['1968', 'atlanta chiefs ( 1 )', 'san diego toros', 'san diego toros ( 186 points )', 'janusz kowalik', 'phil woosnam'], ['1969', 'kansas city spurs ( 1 )', 'atlanta chiefs', 'kansas city spurs ( 110 points )', 'kaizer motaung', 'janos bedl'], ['1970', 'rochester lancers ( 1 )', 'washington darts', 'washington darts (... |
wheelchair basketball at the 2000 summer paralympics | https://en.wikipedia.org/wiki/Wheelchair_basketball_at_the_2000_Summer_Paralympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18781865-4.html.csv | aggregation | a total of two silver medals were won in wheelchair basketball at the 2000 summer paralympics . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'silver'], 'result': '2', 'ind': 0, 'tostr': 'sum { all_rows ; silver }'}, '2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; silver } ; 2 } = true', 'tointer': 'the sum of the silver record of all rows is 2 .'} | round_eq { sum { all_rows ; silver } ; 2 } = true | the sum of the silver record of all rows is 2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'silver_4': 4, '2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'silver_4': 'silver', '2_5': '2'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'silver_4': [0], '2_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'canada ( can )', '2', '0', '0', '2'], ['2', 'australia ( aus )', '0', '1', '0', '1'], ['2', 'netherlands ( ned )', '0', '1', '0', '1'], ['4', 'united states ( usa )', '0', '0', '1', '1'], ['4', 'japan ( jpn )', '0', '0', '1', '1']] |
2008 - 09 denver nuggets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Denver_Nuggets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17355408-4.html.csv | majority | in the 08 - 09 denver nuggets season most of the games at the pepsi center had an attendance of less than 19000 . | {'scope': 'subset', 'col': '8', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '19000', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'pepsi center'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'pepsi center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; pepsi center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to pepsi center .'}, 'locat... | most_less { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance ; 19000 } = true | select the rows whose location attendance record fuzzily matches to pepsi center . for the location attendance records of these rows , most of them are less than 19000 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, 'pepsi center_5': 5, 'location attendance_6': 6, '19000_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', 'pepsi center_5': 'pepsi center', 'location attendance_6': 'location attendance', '19000_7': '19000'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], 'pepsi center_5': [0], 'location attendance_6': [1], '19000_7': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['3', 'november 1', 'la lakers', 'l 97 - 104 ( ot )', 'anthony carter ( 20 )', 'chris andersen ( 7 )', 'allen iverson ( 7 )', 'pepsi center 19651', '1 - 2'], ['4', 'november 5', 'golden state', 'l 101 - 111 ( ot )', 'carmelo anthony ( 28 )', 'nenê ( 15 )', 'anthony carter ( 11 )', 'oracle arena 18194', '1 - 3'], ['5',... |
2007 - 08 philadelphia flyers season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11902580-4.html.csv | majority | all games of the philadelphia flyers ' in the 2007 - 08 season were scheduled for the month of november . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'november', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to november .', 'tostr': 'all_eq { all_rows ; date ; november } = true'} | all_eq { all_rows ; date ; november } = true | for the date records of all rows , all of them fuzzily match to november . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'november_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'november_4': 'november'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'november_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 1', 'philadelphia', '2 - 5', 'montreal', 'biron', '21173', '7 - 4 - 0'], ['november 2', 'philadelphia', '3 - 2', 'washington', 'niittymaki', '16055', '8 - 4 - 0'], ['november 5', 'philadelphia', '0 - 2', 'ny rangers', 'biron', '18200', '8 - 5 - 0'], ['november 7', 'philadelphia', '3 - 1', 'pittsburgh', 'bir... |
1990 pga championship | https://en.wikipedia.org/wiki/1990_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18132874-4.html.csv | ordinal | representing the united states , fred couples won 135000 dollars , coming in 2nd at the 1990 pga championship . | {'scope': 'all', 'row': '2', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'money', '2'], 'result': '135000', 'ind': 0, 'tostr': 'nth_max { all_rows ; money ; 2 }', 'tointer': 'the 2nd maximum money record of all rows is 135000 .'}, '135000'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ;... | and { eq { nth_max { all_rows ; money ; 2 } ; 135000 } ; eq { hop { nth_argmax { all_rows ; money ; 2 } ; player } ; fred couples } } = true | the 2nd maximum money record of all rows is 135000 . the player record of the row with 2nd maximum money record is fred couples . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'money_8': 8, '2_9': 9, '135000_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'money_12': 12, '2_13': 13, 'player_14': 14, 'fred couples_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'money_8': 'money', '2_9': '2', '135000_10': '135000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'money_12': 'money', '2_13': '2', 'player_14': 'player', 'fre... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'money_8': [0], '2_9': [0], '135000_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'money_12': [2], '2_13': [2], 'player_14': [3], 'fred couples_15': [4]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'wayne grady', 'australia', '72 + 67 + 72 + 71 = 282', '- 6', '225000'], ['2', 'fred couples', 'united states', '69 + 71 + 73 + 72 = 285', '- 3', '135000'], ['3', 'gil morgan', 'united states', '77 + 72 + 65 + 72 = 286', '- 2', '90000'], ['4', 'bill britton', 'united states', '72 + 74 + 72 + 71 = 289', '+ 1', '7... |
2005 - 06 primeira liga | https://en.wikipedia.org/wiki/2005%E2%80%9306_Primeira_Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17933603-1.html.csv | ordinal | of the clubs listed benfica finished 1st in the liga . | {'row': '3', 'col': '5', 'order': '1', 'col_other': '1', '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', '2004 - 2005 season', '1'], 'result': '1st in the liga', 'ind': 0, 'tostr': 'nth_min { all_rows ; 2004 - 2005 season ; 1 }', 'tointer': 'the 1st minimum 2004 - 2005 season record of all rows is 1st in the liga .'}, '1st in the lig... | and { eq { nth_min { all_rows ; 2004 - 2005 season ; 1 } ; 1st in the liga } ; eq { hop { nth_argmin { all_rows ; 2004 - 2005 season ; 1 } ; club } ; benfica } } = true | the 1st minimum 2004 - 2005 season record of all rows is 1st in the liga . the club record of the row with 1st minimum 2004 - 2005 season record is benfica . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, '2004 - 2005 season_8': 8, '1_9': 9, '1st in the liga_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, '2004 - 2005 season_12': 12, '1_13': 13, 'club_14': 14, 'benfica_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', '2004 - 2005 season_8': '2004 - 2005 season', '1_9': '1', '1st in the liga_10': '1st in the liga', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', '2004 - 2005 seas... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], '2004 - 2005 season_8': [0], '1_9': [0], '1st in the liga_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], '2004 - 2005 season_12': [2], '1_13': [2], 'club_14': [3], 'benfica_15': [4]} | ['club', "season 's last head coach", 'city', 'stadium', '2004 - 2005 season'] | [['académica de coimbra', 'nelo vingada', 'coimbra', 'estádio cidade de coimbra', '14th in the liga'], ['belenenses', 'carlos carvalhal', 'lisbon', 'estádio do restelo', '9th in the liga'], ['benfica', 'ronald koeman', 'lisbon', 'estádio da luz', '1st in the liga'], ['boavista', 'carlos brito', 'porto', 'estádio do bes... |
indiana high school athletics conferences : ohio river valley - western indiana | https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Ohio_River_Valley_%E2%80%93_Western_Indiana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18974097-1.html.csv | superlative | switzerland county school had the biggest size in indiana high school athletics conferences . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'size'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; size }'}, 'school'], 'result': 'switzerland county', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; size } ; school }'}, 'switzerland county'], 'result': True,... | eq { hop { argmax { all_rows ; size } ; school } ; switzerland county } = true | select the row whose size record of all rows is maximum . the school record of this row is switzerland county . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'size_5': 5, 'school_6': 6, 'switzerland county_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'size_5': 'size', 'school_6': 'school', 'switzerland county_7': 'switzerland county'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'size_5': [0], 'school_6': [1], 'switzerland county_7': [2]} | ['school', 'location', 'mascot', 'size', 'ihsaa class', 'county'] | [['jac - cen - del', 'osgood , indiana', 'eagles', '279', 'a', '69 ripley'], ['milan', 'milan', 'indians', '408', 'aa', '69 ripley'], ['rising sun', 'rising sun', 'shiners', '243', 'a', '58 ohio'], ['madison shawe', 'madison', 'hilltoppers', '112', 'a', '39 jefferson'], ['south ripley', 'versailles', 'raiders', '375', ... |
2008 manx grand prix | https://en.wikipedia.org/wiki/2008_Manx_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18649514-10.html.csv | superlative | daniel kneen had the highest speed among all riders at the 2008 manx grand prix . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'speed'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; speed }'}, 'rider'], 'result': 'daniel kneen', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; speed } ; rider }'}, 'daniel kneen'], 'result': True, 'ind': 2, ... | eq { hop { argmax { all_rows ; speed } ; rider } ; daniel kneen } = true | select the row whose speed record of all rows is maximum . the rider record of this row is daniel kneen . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'speed_5': 5, 'rider_6': 6, 'daniel kneen_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'speed_5': 'speed', 'rider_6': 'rider', 'daniel kneen_7': 'daniel kneen'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'speed_5': [0], 'rider_6': [1], 'daniel kneen_7': [2]} | ['rank', 'rider', 'team', 'speed', 'time'] | [['1', 'daniel kneen', '400cc honda', '106.619 mph', '1:03.41.86'], ['2', 'kirk farrow', '400cc honda', '105.905 mph', '1:04.07.62'], ['3', 'ross johnson', '400cc kawasaki', '105.161 mph', '1:04.34.85'], ['4', 'tim sayers', '400cc kawasaki', '105.009 mph', '1:04.40.47'], ['5', 'dan hobson', '400c honda', '104.574 mph',... |
darya pchelnik | https://en.wikipedia.org/wiki/Darya_Pchelnik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12583435-1.html.csv | superlative | the best position for darya pchelnik came at the universiade competition . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', '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', 'position'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; position }'}, 'competition'], 'result': 'universiade', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; position } ; competition }'}, 'universiade'], 'result... | eq { hop { argmin { all_rows ; position } ; competition } ; universiade } = true | select the row whose position record of all rows is minimum . the competition record of this row is universiade . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'position_5': 5, 'competition_6': 6, 'universiade_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'position_5': 'position', 'competition_6': 'competition', 'universiade_7': 'universiade'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'position_5': [0], 'competition_6': [1], 'universiade_7': [2]} | ['year', 'competition', 'venue', 'position', 'notes'] | [['2005', 'world championships', 'helsinki , finland', '15th ( q )', '65.54 m'], ['2005', 'universiade', 'izmir , turkey', '10th', '63.89 m'], ['2007', 'universiade', 'bangkok , thailand', '1st', '68.74 m'], ['2008', 'olympic games', 'beijing , china', '4th', '73.65 m'], ['2009', 'world championships', 'berlin , german... |
toronto raptors all - time roster | https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-3.html.csv | unique | keon clark was the only player to play the forward-center position . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'forward-center', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'forward-center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to forward-center .', 'tostr': 'filter_eq { all_rows ; position ; forward-center }'}], 'result': Tr... | and { only { filter_eq { all_rows ; position ; forward-center } } ; eq { hop { filter_eq { all_rows ; position ; forward-center } ; player } ; keon clark } } = true | select the rows whose position record fuzzily matches to forward-center . there is only one such row in the table . the player record of this unqiue row is keon clark . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'forward-center_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'keon clark_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'forward-center_8': 'forward-center', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'keon clark_10': 'keon clark'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'forward-center_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'keon clark_10': [3]} | ['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team'] | [['josé calderón', '8', 'spain', 'guard', '2005 - 2013', 'tau cerámica ( spain )'], ['marcus camby', '21', 'united states', 'center', '1996 - 98', 'massachusetts'], ['anthony carter', '25', 'united states', 'guard', '2011 - 12', 'hawaii'], ['vince carter', '15', 'united states', 'guard - forward', '1998 - 2004', 'north... |
2002 - 03 boston celtics season | https://en.wikipedia.org/wiki/2002%E2%80%9303_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17621978-10.html.csv | aggregation | in the 8 games between 4/2 - 4/16/2003 , the boston celtics averaged 90.5 points per game . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '90.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '90.5', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '90.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 90.5 } = true', 'tointer': 'the average of the score record of all rows is 90.5 .'} | round_eq { avg { all_rows ; score } ; 90.5 } = true | the average of the score record of all rows is 90.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '90.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '90.5_5': '90.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '90.5_5': [1]} | ['game', 'date', 'opponent', 'score', 'location', 'record'] | [['75', 'april 2', 'miami heat', 'w 90 - 62', 'fleetcenter', '41 - 34'], ['76', 'april 4', 'sacramento kings', 'l 92 - 93', 'fleetcenter', '41 - 35'], ['77', 'april 6', 'washington wizards', 'l 98 - 99 ( ot )', 'fleetcenter', '41 - 36'], ['78', 'april 9', 'washington wizards', 'w 87 - 83', 'mci center', '42 - 36'], ['7... |
eastern collegiate hockey league | https://en.wikipedia.org/wiki/Eastern_Collegiate_Hockey_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16381914-1.html.csv | aggregation | the eastern collegiate hockey league included three private catholic schools with an average enrollment of 3,847 students . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '3,847', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'private/catholic'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'affiliation', 'private/catholic'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; affiliation ; private/catholic }', 'tointer': 'select the rows whose affiliation record fuzzily matches to private/catholic... | round_eq { avg { filter_eq { all_rows ; affiliation ; private/catholic } ; enrollment } ; 3,847 } = true | select the rows whose affiliation record fuzzily matches to private/catholic . the average of the enrollment record of these rows is 3,847 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'affiliation_5': 5, 'private/catholic_6': 6, 'enrollment_7': 7, '3,847_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'affiliation_5': 'affiliation', 'private/catholic_6': 'private/catholic', 'enrollment_7': 'enrollment', '3,847_8': '3,847'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'affiliation_5': [0], 'private/catholic_6': [0], 'enrollment_7': [1], '3,847_8': [2]} | ['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname', 'primary conference'] | [['university at buffalo', 'buffalo , new york', '1846', 'public', '28192', 'bulls', 'mid - american conference ( d - i )'], ['canisius college', 'buffalo , new york', '1870', 'private / catholic', '3490', 'golden griffins', 'metro atlantic athletic conference ( d - i )'], ['suny canton', 'canton , new york', '1906', '... |
18 to life | https://en.wikipedia.org/wiki/18_to_Life | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25304789-1.html.csv | superlative | the episode with the highest numbers of viewers of 18 to life sitcom was entitled " a modest proposal " . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'rating'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; rating }'}, 'episode'], 'result': 'a modest proposal', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; rating } ; episode }'}, 'a modest proposal'], 'result':... | eq { hop { argmax { all_rows ; rating } ; episode } ; a modest proposal } = true | select the row whose rating record of all rows is maximum . the episode record of this row is a modest proposal . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'rating_5': 5, 'episode_6': 6, 'a modest proposal_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'rating_5': 'rating', 'episode_6': 'episode', 'a modest proposal_7': 'a modest proposal'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'rating_5': [0], 'episode_6': [1], 'a modest proposal_7': [2]} | ['order', 'episode', 'us air date', 'rating', 'share', 'rating / share ( 1849 )', 'viewers ( millions )', 'rank ( timeslot )'] | [['1', 'a modest proposal', 'august 3 , 2010', '0.7', '1', '0.4 / 1', '1.010', '5'], ['2', 'no strings attached', 'august 3 , 2010', '0.6', '1', '0.3 / 1', '0.862', '5'], ['3', "it 's my party", 'august 10 , 2010', '0.6', '1', '0.3 / 1', '0.747', '5'], ['4', 'detour', 'august 10 , 2010', '0.5', '1', '0.3 / 1', '0.776',... |
2007 - 08 oakland golden grizzlies men 's basketball team | https://en.wikipedia.org/wiki/2007%E2%80%9308_Oakland_Golden_Grizzlies_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15748977-1.html.csv | majority | most of the people on the 2007 - 08 oakland golden grizzlies men 's basketball team are at least six feet tall . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': "6 ' 0", 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'height', "6 ' 0"], 'result': True, 'ind': 0, 'tointer': "for the height records of all rows , most of them are greater than or equal to 6 ' 0 .", 'tostr': "most_greater_eq { all_rows ; height ; 6 ' 0 } = true"} | most_greater_eq { all_rows ; height ; 6 ' 0 } = true | for the height records of all rows , most of them are greater than or equal to 6 ' 0 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'height_3': 3, "6'0_4": 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'height_3': 'height', "6'0_4": "6 ' 0"} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'height_3': [0], "6'0_4": [0]} | ['name', 'pos', 'height', 'weight', 'year', 'hometown ( previous school )'] | [['derick nelson', 'f', "6 ' 5", '226', 'jr', 'lansing , mi ( bridgton academy )'], ['peter bunn', 'g', "6 ' 1", '165', 'fr', 'lansing , mi ( lansing christian )'], ['will hudson', 'f', "6 ' 9", '220', 'fr', 'verona , wi ( middleton )'], ['b - jay walker', 'g', "5 ' 8", '149', 'so', 'lathrup village , mi ( shrine catho... |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17596418-5.html.csv | majority | most of the start source are revealed by bbc sport . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'bbc sport', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'start source', 'bbc sport'], 'result': True, 'ind': 0, 'tointer': 'for the start source records of all rows , most of them fuzzily match to bbc sport .', 'tostr': 'most_eq { all_rows ; start source ; bbc sport } = true'} | most_eq { all_rows ; start source ; bbc sport } = true | for the start source records of all rows , most of them fuzzily match to bbc sport . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'start source_3': 3, 'bbc sport_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'start source_3': 'start source', 'bbc sport_4': 'bbc sport'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'start source_3': [0], 'bbc sport_4': [0]} | ['name', 'country', 'loan club', 'started', 'ended', 'start source', 'end source'] | [['heaton', 'eng', 'manchester united', '5 may', '30 june', 'bbc sport', 'south wales echo'], ['e johnson', 'usa', 'fulham', '22 august', '30 june', 'bbc sport', 'south wales echo'], ['chopra', 'eng', 'sunderland', '6 november', '30 december', 'bbc sport', 'bbc sport'], ['routledge', 'eng', 'aston villa', '20 november'... |
list of latvian submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Latvian_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17822046-1.html.csv | superlative | the child of man is the first best foreign language film for the latvian submission award . | {'scope': 'all', 'col_superlative': '1', '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', 'year ( ceremony )'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; year ( ceremony ) }'}, 'film title used in nomination'], 'result': 'the child of man', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; year ( cerem... | eq { hop { argmin { all_rows ; year ( ceremony ) } ; film title used in nomination } ; the child of man } = true | select the row whose year ( ceremony ) record of all rows is minimum . the film title used in nomination record of this row is the child of man . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'year (ceremony)_5': 5, 'film title used in nomination_6': 6, 'the child of man_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'year (ceremony)_5': 'year ( ceremony )', 'film title used in nomination_6': 'film title used in nomination', 'the child of man_7': 'the child of man'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'year (ceremony)_5': [0], 'film title used in nomination_6': [1], 'the child of man_7': [2]} | ['year ( ceremony )', 'film title used in nomination', 'original title', 'director', 'result'] | [['1992 ( 65th )', 'the child of man', 'cilvēka bērns', 'jānis streičs', 'not nominated'], ['2008 ( 81st )', 'defenders of riga', 'rīgas sargi', 'aigars grauba', 'not nominated'], ['2010 ( 83rd )', 'hong kong confidential', 'amaya', 'māris martinsons', 'not nominated'], ['2012 ( 85th )', 'gulf stream under the iceberg'... |
ka commuter jabodetabek | https://en.wikipedia.org/wiki/KA_Commuter_Jabodetabek | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15039992-1.html.csv | aggregation | the train lines of the ka commuter jabodetabek serve an average of 17.5 stations . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '17.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'stations served'], 'result': '17.5', 'ind': 0, 'tostr': 'avg { all_rows ; stations served }'}, '17.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; stations served } ; 17.5 } = true', 'tointer': 'the average of the stations served r... | round_eq { avg { all_rows ; stations served } ; 17.5 } = true | the average of the stations served record of all rows is 17.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'stations served_4': 4, '17.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'stations served_4': 'stations served', '17.5_5': '17.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'stations served_4': [0], '17.5_5': [1]} | ['line color', 'line', 'route', 'stations served', 'length'] | [['orange', 'jakarta loopline', 'jatinegara to depok / bogor', '30', '71.8 km'], ['red', 'jakarta - bogor', 'jakarta kota to depok / bogor', '25', '54.6 km'], ['green', 'jakarta - south tangerang', 'tanah abang to serpong / parung panjang / maja', '19', '55.7 km'], ['blue', 'jakarta - bekasi', 'jakarta kota to bekasi',... |
usa today all - usa high school baseball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677100-3.html.csv | majority | the majority of players on the usa today all - usa high school baseball team entered the 1995 draft instead of attending college . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '1995', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'mlb draft', '1995'], 'result': True, 'ind': 0, 'tointer': 'for the mlb draft records of all rows , most of them fuzzily match to 1995 .', 'tostr': 'most_eq { all_rows ; mlb draft ; 1995 } = true'} | most_eq { all_rows ; mlb draft ; 1995 } = true | for the mlb draft records of all rows , most of them fuzzily match to 1995 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'mlb draft_3': 3, '1995_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'mlb draft_3': 'mlb draft', '1995_4': '1995'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'mlb draft_3': [0], '1995_4': [0]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['ben davis', 'catcher', 'malvern prep', 'malvern , pa', '1st round - 2nd pick of 1995 draft ( padres )'], ['chad hutchinson', 'pitcher', 'torrey pines high school', 'san diego , ca', 'attended stanford'], ['kerry wood', 'pitcher', 'grand prairie high school', 'grand prairie , tx', '1st round - 4th pick of 1995 draft ... |
liga mx | https://en.wikipedia.org/wiki/Liga_MX | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18143210-2.html.csv | superlative | america and guadalajara had the greatest number of seasons in liga mix . | {'scope': 'all', 'col_superlative': '5', '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', 'number of seasons in liga mx'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; number of seasons in liga mx }'}, 'club'], 'result': 'américa', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; number of seasons in lig... | eq { hop { argmax { all_rows ; number of seasons in liga mx } ; club } ; américa } = true | select the row whose number of seasons in liga mx record of all rows is maximum . the club record of this row is américa . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'number of seasons in liga mx_5': 5, 'club_6': 6, 'américa_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'number of seasons in liga mx_5': 'number of seasons in liga mx', 'club_6': 'club', 'américa_7': 'américa'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'number of seasons in liga mx_5': [0], 'club_6': [1], 'américa_7': [2]} | ['club', 'first season in top division', 'number of seasons in top division', 'first season of current spell in top division', 'number of seasons in liga mx', 'top division titles'] | [['américa', '1943 - 44', '89', '1943 - 44', '89', '11'], ['atlante', '1943 - 44', '87', '1991 - 92', '40', '3'], ['atlas', '1943 - 44', '86', '1979 - 80', '51', '1'], ['chiapas', '2002 - 03', '22', '2002 - 03', '22', '0'], ['cruz azul', '1964 - 65', '68', '1964 - 65', '68', '8'], ['guadalajara', '1943 - 44', '89', '19... |
1981 san francisco 49ers season | https://en.wikipedia.org/wiki/1981_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15353865-2.html.csv | ordinal | the san francisco 49ers ' match on december 20 was the latest in the 1981 season . | {'row': '16', 'col': '2', 'order': '16', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '16'], 'result': 'december 20 , 1981', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 16 }', 'tointer': 'the 16th minimum date record of all rows is december 20 , 1981 .'}, 'december 20 , 1981'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min {... | eq { nth_min { all_rows ; date ; 16 } ; december 20 , 1981 } = true | the 16th minimum date record of all rows is december 20 , 1981 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'date_4': 4, '16_5': 5, 'december 20 , 1981_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'date_4': 'date', '16_5': '16', 'december 20 , 1981_6': 'december 20 , 1981'} | {'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'date_4': [0], '16_5': [0], 'december 20 , 1981_6': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 6 , 1981', 'detroit lions', 'l 17 - 24', '63710'], ['2', 'september 13 , 1981', 'chicago bears', 'w 28 - 17', '49520'], ['3', 'september 20 , 1981', 'atlanta falcons', 'l 17 - 34', '56653'], ['4', 'september 27 , 1981', 'new orleans saints', 'w 21 - 14', '44433'], ['5', 'october 4 , 1981', 'washington... |
ai miyazato | https://en.wikipedia.org/wiki/Ai_Miyazato | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2126093-3.html.csv | comparative | ai miyazato 's margin of victory was two strokes more on november 20 , 2005 , than on september 10 , 2006 . | {'row_1': '11', 'row_2': '12', 'col': '6', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '2 strokes', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '20 nov 2005'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 20 nov 2005 .', 'tostr': 'filter_eq { all_rows ; date ; 20 nov 2005 }'}, 'margi... | eq { diff { hop { filter_eq { all_rows ; date ; 20 nov 2005 } ; margin of victory } ; hop { filter_eq { all_rows ; date ; 10 sep 2006 } ; margin of victory } } ; 2 strokes } = true | select the rows whose date record fuzzily matches to 20 nov 2005 . take the margin of victory record of this row . select the rows whose date record fuzzily matches to 10 sep 2006 . take the margin of victory record of this row . the first record is 2 strokes larger than the second record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'date_8': 8, '20 nov 2005_9': 9, 'margin of victory_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'date_12': 12, '10 sep 2006_13': 13, 'margin of victory_14': 14, '2 strokes_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'date_8': 'date', '20 nov 2005_9': '20 nov 2005', 'margin of victory_10': 'margin of victory', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'al... | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'date_8': [0], '20 nov 2005_9': [0], 'margin of victory_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'date_12': [1], '10 sep 2006_13': [1], 'margin of victory_14': [3], '2 strokes_15'... | ['no', 'date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up'] | [['1', '28 sep 2003', 'miyagi tv cup dunlop ladies open ( as an amateur )', '70 + 70 + 71 = 211', '- 5', '1 stroke', 'mari katayama hiroko yamaguchi'], ['2', '7 mar 2004', 'daikin orchid ladies', '70 + 66 + 70 = 206', '- 10', '3 strokes', 'kaori higo'], ['3', '13 jun 2004', 'suntory ladies open', '69 + 70 + 70 + 68 = 2... |
2008 iaaf world indoor championships - men 's 400 metres | https://en.wikipedia.org/wiki/2008_IAAF_World_Indoor_Championships_%E2%80%93_Men%27s_400_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16194679-3.html.csv | aggregation | for the 2008 iaaf world indoor championships men 's 400 metres the athletes from russia had an average mark of 47.05 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '47.05', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'mark'], 'result': '47.05', 'ind': 0, 'tostr': 'avg { all_rows ; mark }'}, '47.05'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; mark } ; 47.05 } = true', 'tointer': 'the average of the mark record of all rows is 47.05 .'} | round_eq { avg { all_rows ; mark } ; 47.05 } = true | the average of the mark record of all rows is 47.05 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'mark_4': 4, '47.05_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'mark_4': 'mark', '47.05_5': '47.05'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'mark_4': [0], '47.05_5': [1]} | ['heat', 'lane', 'name', 'country', 'mark', 'react'] | [['1', '5', 'tyler christopher', 'canada', '46.57', '0.253'], ['1', '6', 'johan wissman', 'sweden', '46.86', '0.242'], ['1', '3', 'sean wroe', 'australia', '47.13 pb', '0.257'], ['1', '2', 'denis alekseyev', 'russia', '47.18', '0.292'], ['1', '4', 'california molefe', 'botswana', '47.74', '0.342'], ['1', '1', 'david ne... |
target house 200 | https://en.wikipedia.org/wiki/Target_House_200 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17801022-1.html.csv | unique | steve grissom is the only driver to use and oldsmobile in the target house 200 . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'oldsmobile', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'oldsmobile'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manufacturer record fuzzily matches to oldsmobile .', 'tostr': 'filter_eq { all_rows ; manufacturer ; oldsmobile }'}], 'result': Tr... | and { only { filter_eq { all_rows ; manufacturer ; oldsmobile } } ; eq { hop { filter_eq { all_rows ; manufacturer ; oldsmobile } ; driver } ; steve grissom } } = true | select the rows whose manufacturer record fuzzily matches to oldsmobile . there is only one such row in the table . the driver record of this unqiue row is steve grissom . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manufacturer_7': 7, 'oldsmobile_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'steve grissom_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manufacturer_7': 'manufacturer', 'oldsmobile_8': 'oldsmobile', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'steve grissom_10': 'steve grissom'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manufacturer_7': [0], 'oldsmobile_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'steve grissom_10': [3]} | ['year', 'date', 'driver', 'manufacturer', 'laps', '-', 'race time', 'average speed ( mph )'] | [['1984', 'october 20', 'geoffrey bodine', 'pontiac', '197', '200.349 ( 322.43 )', '2:06:51', '94.765'], ['1985', 'october 19', 'brett bodine', 'pontiac', '197', '200.349 ( 322.43 )', '1:56:00', '103.629'], ['1986', 'october 18', 'morgan shepherd', 'buick', '197', '200.349 ( 322.43 )', '1:39:08', '101.177'], ['1987', '... |
list of the busiest airports in brazil | https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_Brazil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15494883-26.html.csv | count | two of the top 15 busiest airports in brazil were in rio de janeiro . | {'scope': 'all', 'criterion': 'equal', 'value': 'rio de janeiro', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'rio de janeiro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to rio de janeiro .', 'tostr': 'filter_eq { all_rows ; location ; rio de janeiro }'}], 'result': '2... | eq { count { filter_eq { all_rows ; location ; rio de janeiro } } ; 2 } = true | select the rows whose location record fuzzily matches to rio de janeiro . 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, 'location_5': 5, 'rio de janeiro_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', 'location_5': 'location', 'rio de janeiro_6': 'rio de janeiro', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'rio de janeiro_6': [0], '2_7': [2]} | ['rank', 'location', 'total passengers', 'annual change', 'capacity in use'] | [['1', 'são paulo', '13611227', '12.8 %', '113.4 %'], ['2', 'são paulo', '12940193', '11.7 %', '78.4 %'], ['3', 'brasília', '9926786', '45.1 %', '134.1 %'], ['4', 'rio de janeiro', '6024930', '30.4 %', '40.2 %'], ['5', 'rio de janeiro', '4887306', '9.2 %', '152.7 %'], ['6', 'salvador', '4145371', '20.0 %', '69.1 %'], [... |
2010 southeastern conference football season | https://en.wikipedia.org/wiki/2010_Southeastern_Conference_football_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26842217-6.html.csv | majority | most of the 2010 southeastern conference football season games broadcast by espn had an attendance less than 100000 . | {'scope': 'subset', 'col': '8', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '100000', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'espn'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'broadcast', 'espn'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; broadcast ; espn }', 'tointer': 'select the rows whose broadcast record fuzzily matches to espn .'}, 'attendance', '100000'], 'result': True, 'ind': 1, 'tointer'... | most_less { filter_eq { all_rows ; broadcast ; espn } ; attendance ; 100000 } = true | select the rows whose broadcast record fuzzily matches to espn . for the attendance records of these rows , most of them are less than 100000 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'broadcast_4': 4, 'espn_5': 5, 'attendance_6': 6, '100000_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'broadcast_4': 'broadcast', 'espn_5': 'espn', 'attendance_6': 'attendance', '100000_7': '100000'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'broadcast_4': [0], 'espn_5': [0], 'attendance_6': [1], '100000_7': [1]} | ['date', 'time', 'visiting team', 'home team', 'site', 'broadcast', 'result', 'attendance'] | [['september 9', '7:30 pm', '21 auburn', 'mississippi state', 'davis wade stadium starkville , ms', 'espn', 'aub 17 - 14', '54806'], ['september 11', '12:00 pm', '22 georgia', '24 south carolina', 'williams - brice stadium columbia , sc', 'espn', 'usc 17 - 6', '80974'], ['september 11', '12:21 pm', 'south florida', '8 ... |
2005 u.s. open ( golf ) | https://en.wikipedia.org/wiki/2005_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14064009-4.html.csv | comparative | jason gore was more under par than mark hensby . | {'row_1': '3', 'row_2': '5', 'col': '5', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jason gore'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jason gore .', 'tostr': 'filter_eq { all_rows ; player ; jason gore }'}, 'to par'], 'result': None, ... | less { hop { filter_eq { all_rows ; player ; jason gore } ; to par } ; hop { filter_eq { all_rows ; player ; mark hensby } ; to par } } = true | select the rows whose player record fuzzily matches to jason gore . take the to par record of this row . select the rows whose player record fuzzily matches to mark hensby . take the to par record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'jason gore_8': 8, 'to par_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'mark hensby_12': 12, 'to par_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'jason gore_8': 'jason gore', 'to par_9': 'to par', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'mark hensb... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'jason gore_8': [0], 'to par_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'mark hensby_12': [1], 'to par_13': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'olin browne', 'united states', '67 + 71 = 138', '- 2'], ['t1', 'retief goosen', 'south africa', '68 + 70 = 138', '- 2'], ['t1', 'jason gore', 'united states', '71 + 67 = 138', '- 2'], ['t4', 'k j choi', 'south korea', '69 + 70 = 139', '- 1'], ['t4', 'mark hensby', 'australia', '71 + 68 = 139', '- 1'], ['t6', '... |
world tourism rankings | https://en.wikipedia.org/wiki/World_Tourism_rankings | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14752049-6.html.csv | ordinal | in the world tourism rankings , spain has the highest change ( 2011 to 2012 ) among countries with international tourist arrivals ( 2012 ) more than 40 million . | {'scope': 'subset', 'row': '2', 'col': '5', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '40 million'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'international tourist arrivals ( 2012 )', '40 million'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; international tourist arrivals ( 2012 ) ; 40 million }', 'toi... | eq { hop { nth_argmax { filter_greater { all_rows ; international tourist arrivals ( 2012 ) ; 40 million } ; change ( 2011 to 2012 ) ; 1 } ; country } ; spain } = true | select the rows whose international tourist arrivals ( 2012 ) record is greater than 40 million . select the row whose change ( 2011 to 2012 ) record of these rows is 1st maximum . the country record of this row is spain . | 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, 'international tourist arrivals (2012)_6': 6, '40 million_7': 7, 'change (2011 to 2012)_8': 8, '1_9': 9, 'country_10': 10, 'spain_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', 'international tourist arrivals (2012)_6': 'international tourist arrivals ( 2012 )', '40 million_7': '40 million', 'change (2011 to 2012)_8': 'change ( 2011 t... | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'international tourist arrivals (2012)_6': [0], '40 million_7': [0], 'change (2011 to 2012)_8': [1], '1_9': [1], 'country_10': [2], 'spain_11': [3]} | ['rank', 'country', 'international tourist arrivals ( 2012 )', 'international tourist arrivals ( 2011 )', 'change ( 2011 to 2012 )', 'change ( 2010 to 2011 )'] | [['1', 'france', '83.0 million', '81.6 million', '+ 1.8 %', '+ 5.0 %'], ['2', 'spain', '57.7 million', '56.2 million', '+ 6.6 %', '+ 6.6 %'], ['3', 'italy', '46.4 million', '46.1 million', '+ 0.5 %', '+ 5.7 %'], ['4', 'turkey', '35.7 million', '34.7 million', '+ 3.0 %', '+ 10.5 %'], ['5', 'germany', '30.4 million', '28... |
list of superleague formula drivers and teams | https://en.wikipedia.org/wiki/List_of_Superleague_Formula_drivers_and_teams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19312274-2.html.csv | aggregation | there are a a total of ten current superleague formula teams . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '10', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'current'], 'result': '10', 'ind': 0, 'tostr': 'sum { all_rows ; current }'}, '10'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; current } ; 10 } = true', 'tointer': 'the sum of the current record of all rows is 10 .'} | round_eq { sum { all_rows ; current } ; 10 } = true | the sum of the current record of all rows is 10 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'current_4': 4, '10_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'current_4': 'current', '10_5': '10'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'current_4': [0], '10_5': [1]} | ['country', 'total', 'champions', 'current', 'first driver ( s )', 'last / current driver ( s )'] | [['argentina', '1', '0', '0', 'esteban guerrieri ( 2009 )', 'esteban guerrieri ( 2010 )'], ['australia', '1', '0', '1', 'john martin ( 2009 )', 'john martin'], ['belgium', '2', '0', '1', 'bertrand baguette ( 2008 )', 'frédéric vervisch'], ['brazil', '3', '0', '1', 'tuka rocha ( 2008 )', 'antônio pizzonia'], ['china', '... |
luis ernesto pérez | https://en.wikipedia.org/wiki/Luis_Ernesto_P%C3%A9rez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1257488-1.html.csv | ordinal | in the table of international goals scored by luis ernesto pérez , he scored his first goal in the 2000 nike us cup . | {'row': '1', 'col': '6', 'order': '1', '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', 'competition', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; competition ; 1 }'}, 'goal'], 'result': '1', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; competition ; 1 } ; goal }'}, '1'], 'result': T... | eq { hop { nth_argmin { all_rows ; competition ; 1 } ; goal } ; 1 } = true | select the row whose competition record of all rows is 1st minimum . the goal record of this row is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'competition_5': 5, '1_6': 6, 'goal_7': 7, '1_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'competition_5': 'competition', '1_6': '1', 'goal_7': 'goal', '1_8': '1'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'competition_5': [0], '1_6': [0], 'goal_7': [1], '1_8': [2]} | ['goal', 'date', 'venue', 'score', 'result', 'competition'] | [['1', 'june 7 , 2000', 'cotton bowl , dallas , united states', '2 - 0', '4 - 0', '2000 nike us cup'], ['2', 'november 17 , 2004', 'estadio tecnológico , monterrey , mexico', '2 - 0', '8 - 0', '2006 fifa world cup qualification'], ['3', 'november 17 , 2004', 'estadio tecnológico , monterrey , mexico', '4 - 0', '8 - 0',... |
usa today all - usa high school basketball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677760-33.html.csv | unique | one player on the usa today all-usa basketball team was from canada . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'brampton , on', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'hometown', 'brampton , on'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose hometown record fuzzily matches to brampton , on .', 'tostr': 'filter_eq { all_rows ; hometown ; brampton , on }'}], 'result': True, 'ind': 1, 'tostr': 'only... | only { filter_eq { all_rows ; hometown ; brampton , on } } = true | select the rows whose hometown record fuzzily matches to brampton , on . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'hometown_4': 4, 'brampton , on_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'hometown_4': 'hometown', 'brampton , on_5': 'brampton , on'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'hometown_4': [0], 'brampton , on_5': [0]} | ['player', 'height', 'school', 'hometown', 'college', 'nba draft'] | [['tyler lewis', "5 ' 11", 'oak hill academy', 'statesville , nc', 'nc state', 'has not yet declared for the nba draft'], ['kasey hill', "6 ' 1", 'montverde academy', 'eustis , fl', 'florida', 'not eligible for the draft until 2014'], ['amile jefferson', "6 ' 9", "friends ' central school", 'wynnewood , pa', 'duke', 'h... |
erik fisher | https://en.wikipedia.org/wiki/Erik_Fisher | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16891410-1.html.csv | majority | erik fisher finished below the top 10 in majority of his races . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'place', '10'], 'result': True, 'ind': 0, 'tointer': 'for the place records of all rows , most of them are greater than 10 .', 'tostr': 'most_greater { all_rows ; place ; 10 } = true'} | most_greater { all_rows ; place ; 10 } = true | for the place records of all rows , most of them are greater than 10 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'place_3': 3, '10_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'place_3': 'place', '10_4': '10'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'place_3': [0], '10_4': [0]} | ['season', 'date', 'location', 'race', 'place'] | [['2009', '19 dec 2008', 'val gardena , italy', 'super g', '20th'], ['2009', '20 dec 2008', 'val gardena , italy', 'downhill', '7th'], ['2009', '24 jan 2009', 'kitzbühel , austria', 'downhill', '11th'], ['2010', '18 dec 2009', 'val gardena , italy', 'downhill', '19th'], ['2010', '23 jan 2010', 'kitzbühel , austria', 'd... |
2005 cfl draft | https://en.wikipedia.org/wiki/2005_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10960039-5.html.csv | superlative | in the 2005 cfl draft , the first ol was picked by motreal alouettes . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2,4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'ol'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'ol'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; ol }', 'tointer': 'select the rows whose position record fuzzily matches to ol .'}, 'pick'], 'resul... | eq { hop { argmin { filter_eq { all_rows ; position ; ol } ; pick } ; cfl team } ; montreal alouettes } = true | select the rows whose position record fuzzily matches to ol . select the row whose pick record of these rows is minimum . the cfl team record of this row is montreal alouettes . | 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, 'position_6': 6, 'ol_7': 7, 'pick_8': 8, 'cfl team_9': 9, 'montreal alouettes_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', 'position_6': 'position', 'ol_7': 'ol', 'pick_8': 'pick', 'cfl team_9': 'cfl team', 'montreal alouettes_10': 'montreal alouettes'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'position_6': [0], 'ol_7': [0], 'pick_8': [1], 'cfl team_9': [2], 'montreal alouettes_10': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['36', 'calgary stampeders', 'david hewson', 'db', 'manitoba'], ['37', 'ottawa renegades', 'adrian baird', 'de', 'ottawa'], ['38', 'winnipeg blue bombers', 'martin lapostolle', 'dl', 'indiana'], ['39', 'saskatchewan roughriders', 'dustin cherniawski', 'db', 'british columbia'], ['40', 'edmonton eskimos', 'robert lebla... |
november nine | https://en.wikipedia.org/wiki/November_Nine | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23696862-6.html.csv | comparative | greg merson had more wsop cashes than michael esposito as a november nine player . | {'row_1': '3', 'row_2': '6', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'greg merson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to greg merson .', 'tostr': 'filter_eq { all_rows ; name ; greg merson }'}, 'wsop cashes'], 'result': N... | greater { hop { filter_eq { all_rows ; name ; greg merson } ; wsop cashes } ; hop { filter_eq { all_rows ; name ; michael esposito } ; wsop cashes } } = true | select the rows whose name record fuzzily matches to greg merson . take the wsop cashes record of this row . select the rows whose name record fuzzily matches to michael esposito . take the wsop cashes 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, 'name_7': 7, 'greg merson_8': 8, 'wsop cashes_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'michael esposito_12': 12, 'wsop cashes_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', 'name_7': 'name', 'greg merson_8': 'greg merson', 'wsop cashes_9': 'wsop cashes', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', '... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'greg merson_8': [0], 'wsop cashes_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'michael esposito_12': [1], 'wsop cashes_13': [3]} | ['name', 'starting chip count', 'wsop bracelets', 'wsop cashes', 'wsop earnings', 'final place', 'prize'] | [['jesse sylvia', '43875000', '0', '2', '36372', '2nd', '5295149'], ['andras koroknai', '29375000', '0', '2', '39371', '6th', '1640461'], ['greg merson', '28725000', '1', '5', '1253501', '1st', '8531853'], ['russell thomas', '24800000', '0', '3', '126796', '4th', '2850494'], ['steven gee', '16860000', '1', '4', '480822... |
mid - states football association | https://en.wikipedia.org/wiki/Mid-States_Football_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-262560-2.html.csv | unique | trine university is the only mid - states institution with the whac primary conference when joining the msfa . | {'scope': 'all', 'row': '10', 'col': '9', 'col_other': '1', 'criterion': 'equal', 'value': 'whac', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'primary conference when joining the msfa', 'whac'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose primary conference when joining the msfa record fuzzily matches to whac .', 'tostr': 'filter_eq { all_rows ; ... | and { only { filter_eq { all_rows ; primary conference when joining the msfa ; whac } } ; eq { hop { filter_eq { all_rows ; primary conference when joining the msfa ; whac } ; institution } ; trine university } } = true | select the rows whose primary conference when joining the msfa record fuzzily matches to whac . there is only one such row in the table . the institution record of this unqiue row is trine university . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'primary conference when joining the msfa_7': 7, 'whac_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'institution_9': 9, 'trine university_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'primary conference when joining the msfa_7': 'primary conference when joining the msfa', 'whac_8': 'whac', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'institution_9': 'institution', 'trine university... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'primary conference when joining the msfa_7': [0], 'whac_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'institution_9': [2], 'trine university_10': [3]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'joined', 'left', 'nickname', 'primary conference when joining the msfa', 'current primary conference'] | [['university of findlay', 'findlay , ohio', '1882', 'private', '4600', '1994 - 95', '1997 - 98', 'oilers', 'american mideast', 'gliac ( ncaa division ii )'], ['geneva college', 'beaver falls , pennsylvania', '1848', 'private', '1791', '1994 - 95', '2006 - 07', 'golden tornadoes', 'american mideast', "presidents ' ( pa... |
1992 open championship | https://en.wikipedia.org/wiki/1992_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18122130-3.html.csv | aggregation | the average total for all the players at the 1992 open championship was 146.4 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '146.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '146.4', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '146.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 146.4 } = true', 'tointer': 'the average of the total record of all rows is 146.4 .'} | round_eq { avg { all_rows ; total } ; 146.4 } = true | the average of the total record of all rows is 146.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '146.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '146.4_5': '146.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '146.4_5': [1]} | ['player', 'country', 'year ( s ) won', 'total', 'to par'] | [['seve ballesteros', 'spain', '1979 , 1984 , 1988', '145', '+ 1'], ['tom weiskopf', 'united states', '1973', '145', '+ 1'], ['gary player', 'south africa', '1959 , 1968 , 1974', '146', '+ 2'], ['jack nicklaus', 'united states', '1966 , 1970 , 1978', '148', '+ 4'], ['tom watson', 'united states', '1975 , 1977 , 1980 , ... |
list of california golden seals draft picks | https://en.wikipedia.org/wiki/List_of_California_Golden_Seals_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18272351-4.html.csv | unique | there was only one pick from a usa national during this period . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'usa', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to usa .', 'tostr': 'filter_eq { all_rows ; nationality ; usa }'}], 'result': True, 'ind': 1, 'tostr': '... | and { only { filter_eq { all_rows ; nationality ; usa } } ; eq { hop { filter_eq { all_rows ; nationality ; usa } ; pick } ; 12 } } = true | select the rows whose nationality record fuzzily matches to usa . there is only one such row in the table . the pick record of this unqiue row is 12 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'usa_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'pick_9': 9, '12_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'usa_8': 'usa', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'pick_9': 'pick', '12_10': '12'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'usa_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'pick_9': [2], '12_10': [3]} | ['draft', 'round', 'pick', 'player', 'nationality'] | [['1967', '1', '3', 'ken hicks', 'canada'], ['1967', '2', '12', 'gary wood', 'usa'], ['1967', '3', '18', 'kevin smith', 'canada'], ['1968', '2', '13', 'doug smith', 'canada'], ['1968', '3', '20', 'jim trewin', 'canada'], ['1969', '1', '7', 'tony featherstone', 'canada'], ['1969', '2', '18', 'ron stackhouse', 'canada'],... |
forklift truck | https://en.wikipedia.org/wiki/Forklift_truck | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-237199-1.html.csv | majority | japan has the majority number of companies and car brands . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'japan', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'japan'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to japan .', 'tostr': 'most_eq { all_rows ; country ; japan } = true'} | most_eq { all_rows ; country ; japan } = true | for the country records of all rows , most of them fuzzily match to japan . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'japan_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'japan_4': 'japan'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'japan_4': [0]} | ['rank', 'company name', '2008 rank', '2009 revenue', 'north american brands', 'world headquarters', 'country'] | [['1', 'toyota industries', '1', '4600000000', 'toyota , bt , raymond', 'aichi', 'japan'], ['2', 'kion group', '2', '4100000000', 'voltas , linde , still , om , baoli', 'wiesbaden', 'germany'], ['3', 'jungheinrich lift truck corp', '3', '2300000000', 'jungheinrich', 'hamburg', 'germany'], ['4', 'crown equipment corpora... |
2007 rexall grand prix of edmonton | https://en.wikipedia.org/wiki/2007_Rexall_Grand_Prix_of_Edmonton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12167074-2.html.csv | aggregation | in the 2007 rexall grand prix of edmonton , contenders completing 96 laps averaged a total of 20.5 points earned . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '20.5', 'subset': {'col': '3', 'criterion': 'equal', 'value': '96'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '96'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; laps ; 96 }', 'tointer': 'select the rows whose laps record is equal to 96 .'}, 'points'], 'result': '20.5', 'ind': 1, 'tostr': 'avg { filter_eq { a... | round_eq { avg { filter_eq { all_rows ; laps ; 96 } ; points } ; 20.5 } = true | select the rows whose laps record is equal to 96 . the average of the points record of these rows is 20.5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'laps_5': 5, '96_6': 6, 'points_7': 7, '20.5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '96_6': '96', 'points_7': 'points', '20.5_8': '20.5'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'laps_5': [0], '96_6': [0], 'points_7': [1], '20.5_8': [2]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['sãbastien bourdais', 'n / h / l racing', '96', '1:45:41.953', '2', '33'], ['justin wilson', 'rsports', '96', '+ 3.9 secs', '3', '27'], ['graham rahal', 'n / h / l racing', '96', '+ 6.6 secs', '4', '25'], ['simon pagenaud ( r )', 'team australia', '96', '+ 24.8 secs', '7', '23'], ['paul tracy', 'forsythe racing', '96... |
1959 vfl season | https://en.wikipedia.org/wiki/1959_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775038-8.html.csv | ordinal | fitzroy had the second lowest home team score of all these football teams . | {'row': '3', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'home team score', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; home team score ; 2 }'}, 'home team'], 'result': 'fitzroy', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; home team score ; 2 } ; ... | eq { hop { nth_argmin { all_rows ; home team score ; 2 } ; home team } ; fitzroy } = true | select the row whose home team score record of all rows is 2nd minimum . the home team record of this row is fitzroy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'home team score_5': 5, '2_6': 6, 'home team_7': 7, 'fitzroy_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', 'home team score_5': 'home team score', '2_6': '2', 'home team_7': 'home team', 'fitzroy_8': 'fitzroy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'home team score_5': [0], '2_6': [0], 'home team_7': [1], 'fitzroy_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '4.13 ( 37 )', 'richmond', '9.9 ( 63 )', 'western oval', '11533', '13 june 1959'], ['north melbourne', '12.12 ( 84 )', 'hawthorn', '8.6 ( 54 )', 'arden street oval', '12500', '13 june 1959'], ['fitzroy', '5.10 ( 40 )', 'collingwood', '3.12 ( 30 )', 'brunswick street oval', '17632', '13 june 1959'], ['sou... |
list of fish hooks episodes | https://en.wikipedia.org/wiki/List_of_Fish_Hooks_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28146944-2.html.csv | superlative | bea stays in the picture had the most us viewers of any fish hooks episode . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( millions ) }'}, 'title'], 'result': 'bea stays in the picture', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( mil... | eq { hop { argmax { all_rows ; us viewers ( millions ) } ; title } ; bea stays in the picture } = true | select the row whose us viewers ( millions ) record of all rows is maximum . the title record of this row is bea stays in the picture . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, 'title_6': 6, 'bea stays in the picture_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (millions)_5': 'us viewers ( millions )', 'title_6': 'title', 'bea stays in the picture_7': 'bea stays in the picture'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], 'title_6': [1], 'bea stays in the picture_7': [2]} | ['no in series', 'title', 'directed by', 'story & storyboards by', 'original air date', 'us viewers ( millions )'] | [['1', 'bea stays in the picture', 'maxwell atoms', 'tim mckeon ( story ) maxwell atoms ( storyboards )', 'september 3 , 2010', '4.8'], ['2', 'fish sleepover party', 'william reiss', 'justin roiland ( story ) william reiss ( storyboards )', 'september 24 , 2010', '3.0'], ['8', 'doggonit', 'maxwell atoms', 'tim mckeon (... |
maine locations by per capita income | https://en.wikipedia.org/wiki/Maine_locations_by_per_capita_income | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1421760-1.html.csv | superlative | cumberland has the highest median family income out of all the locations in maine . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'median family income'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; median family income }'}, 'county'], 'result': 'cumberland', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; median family income } ; county }'}... | eq { hop { argmax { all_rows ; median family income } ; county } ; cumberland } = true | select the row whose median family income record of all rows is maximum . the county record of this row is cumberland . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'median family income_5': 5, 'county_6': 6, 'cumberland_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'median family income_5': 'median family income', 'county_6': 'county', 'cumberland_7': 'cumberland'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'median family income_5': [0], 'county_6': [1], 'cumberland_7': [2]} | ['county', 'per capita income', 'median household income', 'median family income', 'population', 'number of households'] | [['cumberland', '31041', '55658', '71335', '281674', '117339'], ['lincoln', '28003', '47678', '58028', '34457', '15149'], ['united states', '27334', '51914', '62982', '308745538', '116716292'], ['york', '27137', '55008', '65077', '197131', '81009'], ['sagadahoc', '26983', '55486', '66650', '35293', '15088'], ['hancock'... |
2008 - 09 chicago bulls season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Chicago_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058151-11.html.csv | superlative | the largest attendance occurred in the game on april 30th . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'location attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; location attendance }'}, 'date'], 'result': 'april 30', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; location attendance } ; date }'}, 'april ... | eq { hop { argmax { all_rows ; location attendance } ; date } ; april 30 } = true | select the row whose location attendance record of all rows is maximum . the date record of this row is april 30 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'date_6': 6, 'april 30_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'date_6': 'date', 'april 30_7': 'april 30'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'date_6': [1], 'april 30_7': [2]} | ['game', 'date', 'team', 'score', 'location attendance', 'series'] | [['1', 'april 18', 'boston', 'w 105 - 103 ( ot )', 'td banknorth garden 18624', '1 - 0'], ['2', 'april 20', 'boston', 'l 115 - 118 ( ot )', 'td banknorth garden 18624', '1 - 1'], ['3', 'april 23', 'boston', 'l 86 - 107 ( ot )', 'united center 23072', '1 - 2'], ['4', 'april 26', 'boston', 'w 121 - 118 ( 2ot )', 'united ... |
list of town tramway systems in the netherlands | https://en.wikipedia.org/wiki/List_of_town_tramway_systems_in_the_Netherlands | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12562214-1.html.csv | comparative | in the list of town tramway systems in the netherlands arnhem had a system before nijmegen . | {'row_1': '3', 'row_2': '8', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'arnhem'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to arnhem .', 'tostr': 'filter_eq { all_rows ; location ; arnhem }'}, 'date ( from )'], 'result': None,... | less { hop { filter_eq { all_rows ; location ; arnhem } ; date ( from ) } ; hop { filter_eq { all_rows ; location ; nijmegen } ; date ( from ) } } = true | select the rows whose location record fuzzily matches to arnhem . take the date ( from ) record of this row . select the rows whose location record fuzzily matches to nijmegen . take the date ( from ) 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, 'location_7': 7, 'arnhem_8': 8, 'date (from)_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'location_11': 11, 'nijmegen_12': 12, 'date (from)_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', 'location_7': 'location', 'arnhem_8': 'arnhem', 'date (from)_9': 'date ( from )', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'location_11': 'location',... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'location_7': [0], 'arnhem_8': [0], 'date (from)_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'location_11': [1], 'nijmegen_12': [1], 'date (from)_13': [3]} | ['name of system', 'location', 'traction type', 'date ( from )', 'date ( to )'] | [['atm ( 1897 - 1917 ) gta ( 1919 - 1922 )', 'apeldoorn', 'horse', '12 august 1897', '11 november 1917'], ['atm ( 1897 - 1917 ) gta ( 1919 - 1922 )', 'apeldoorn', 'petrol ( gasoline )', '5 june 1919', '8 october 1922'], ['atm ( 1880 - 1911 ) geta ( 1911 - 1944 )', 'arnhem', 'horse', '3 may 1880', '12 june 1912'], ['atm... |
kris kin | https://en.wikipedia.org/wiki/Kris_Kin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12927663-1.html.csv | aggregation | the horse kris kin helped earn a total of 1920k in prizes while with the jockey kieren fallon . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '1920', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'prize ( k )'], 'result': '1920', 'ind': 0, 'tostr': 'sum { all_rows ; prize ( k ) }'}, '1920'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; prize ( k ) } ; 1920 } = true', 'tointer': 'the sum of the prize ( k ) record of all rows is... | round_eq { sum { all_rows ; prize ( k ) } ; 1920 } = true | the sum of the prize ( k ) record of all rows is 1920 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'prize (k)_4': 4, '1920_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'prize (k)_4': 'prize ( k )', '1920_5': '1920'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'prize (k)_4': [0], '1920_5': [1]} | ['race', 'dist ( f )', 'course', 'class', 'prize ( k )', 'odds', 'runners', 'placing', 'margin', 'time', 'jockey', 'trainer'] | [['unfuwain ebf maiden stakes', '7', 'newmarket - rowley', 'm', '7', '20 / 1', '26', '15', '14.5', '1:24.71', 'johnny murtagh', 'michael stoute'], ['weatherbys bank ebf maiden stakes', '7', 'doncaster', 'm', '5', '5 / 1', '12', '1', '2.5', '1:35.36', 'fergal lynch', 'michael stoute'], ['dee stakes', '10', 'chester', '3... |
türk telekom arena | https://en.wikipedia.org/wiki/T%C3%BCrk_Telekom_Arena | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12243387-4.html.csv | unique | in türk telekom arena , when the round is euro 2012 qualifying , the only time there were under 40000 spectators was on october 11 , 2011 . | {'scope': 'subset', 'row': '4', 'col': '7', 'col_other': '1,5', 'criterion': 'less_than', 'value': '40000', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'euro 2012 qualifying'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'round', 'euro 2012 qualifying'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; round ; euro 2012 qualifying }', 'tointer': 'select the rows whose round record fuzzily matches ... | and { only { filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 } } ; and { eq { hop { filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 } ; date } ; 11 october 2011 } ; eq { hop { filter_less { filter_eq { all_rows ; round ; euro 2012 qualify... | select the rows whose round record fuzzily matches to euro 2012 qualifying . among these rows , select the rows whose spectators record is less than 40000 . there is only one such row in the table . the date record of this unqiue row is 11 october 2011 . the team 2 record of this unqiue row is azerbaijan . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'only_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'round_11': 11, 'euro 2012 qualifying_12': 12, 'spectators_13': 13, '40000_14': 14, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'date_15': 15, '11 october 2011_16': 16, 'str_eq_6': 6, 'str_hop_5': 5, 'team 2_17': 17, 'a... | {'and_8': 'and', 'result_9': 'true', 'only_2': 'only', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'round_11': 'round', 'euro 2012 qualifying_12': 'euro 2012 qualifying', 'spectators_13': 'spectators', '40000_14': '40000', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop... | {'and_8': [9], 'result_9': [], 'only_2': [8], 'filter_less_1': [2, 3, 5], 'filter_str_eq_0': [1], 'all_rows_10': [0], 'round_11': [0], 'euro 2012 qualifying_12': [0], 'spectators_13': [1], '40000_14': [1], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'date_15': [3], '11 october 2011_16': [4], 'str_eq_6': [7], 'str_... | ['date', 'time ( cest )', 'team 1', 'res', 'team 2', 'round', 'spectators'] | [['10 august 2011', '20.30', 'turkey', '3 - 0', 'estonia', 'friendly', '25000'], ['2 september 2011', '19.00', 'turkey', '2 - 1', 'kazakhstan', 'euro 2012 qualifying', '47756'], ['7 october 2011', '20.30', 'turkey', '1 - 3', 'germany', 'euro 2012 qualifying', '49532'], ['11 october 2011', '19.00', 'turkey', '1 - 0', 'a... |
1988 - 89 north west counties football league | https://en.wikipedia.org/wiki/1988%E2%80%9389_North_West_Counties_Football_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17790191-2.html.csv | majority | in the 1988 - 89 north west counties football league , most teams scored at least 30 points . | {'scope': 'all', 'col': '9', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '30', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'points 1', '30'], 'result': True, 'ind': 0, 'tointer': 'for the points 1 records of all rows , most of them are greater than or equal to 30 .', 'tostr': 'most_greater_eq { all_rows ; points 1 ; 30 } = true'} | most_greater_eq { all_rows ; points 1 ; 30 } = true | for the points 1 records of all rows , most of them are greater than or equal to 30 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points 1_3': 3, '30_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points 1_3': 'points 1', '30_4': '30'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'points 1_3': [0], '30_4': [0]} | ['position', 'team', 'played', 'drawn', 'lost', 'goals for', 'goals against', 'goal difference', 'points 1'] | [['1', 'vauxhall motors', '34', '8', '1', '68', '17', '+ 51', '58'], ['2', 'maine road', '34', '7', '5', '96', '40', '+ 56', '51'], ['3', 'chadderton', '34', '9', '5', '71', '29', '+ 42', '49'], ['4', 'wren rovers', '34', '10', '5', '77', '45', '+ 32', '48'], ['5', 'nantwich town', '34', '4', '10', '66', '28', '+ 38', ... |
fox television stations | https://en.wikipedia.org/wiki/Fox_Television_Stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1353096-2.html.csv | majority | the majority of fox television stations were originally fox affiliates . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'fox affiliate', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'current status', 'fox affiliate'], 'result': True, 'ind': 0, 'tointer': 'for the current status records of all rows , most of them fuzzily match to fox affiliate .', 'tostr': 'most_eq { all_rows ; current status ; fox affiliate } = true'} | most_eq { all_rows ; current status ; fox affiliate } = true | for the current status records of all rows , most of them fuzzily match to fox affiliate . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'current status_3': 3, 'fox affiliate_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'current status_3': 'current status', 'fox affiliate_4': 'fox affiliate'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'current status_3': [0], 'fox affiliate_4': [0]} | ['city of license / market', 'station', 'channel tv ( dt )', 'years owned', 'current status'] | [['birmingham - tuscaloosa - anniston', 'wbrc - tv', '6 ( 50 )', '1995 - 2008', 'fox affiliate owned by raycom media'], ['san francisco - oakland - san jose', 'kbhk - tv ¤ ¤ ( now kbcw )', '44 ( 45 )', '2001 - 2002', 'cw affiliate owned by cbs corporation'], ['denver', 'kdvr', '31 ( 32 )', '1995 - 2008', 'fox affiliate... |
2007 - 08 birmingham city f.c. season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Birmingham_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15120038-1.html.csv | comparative | the game against walsall was played earlier than the game against sheffield wednesday . | {'row_1': '4', 'row_2': '6', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents', 'walsall'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponents record fuzzily matches to walsall .', 'tostr': 'filter_eq { all_rows ; opponents ; walsall }'}, 'date'], 'result': None, 'i... | less { hop { filter_eq { all_rows ; opponents ; walsall } ; date } ; hop { filter_eq { all_rows ; opponents ; sheffield wednesday } ; date } } = true | select the rows whose opponents record fuzzily matches to walsall . take the date record of this row . select the rows whose opponents record fuzzily matches to sheffield wednesday . 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, 'opponents_7': 7, 'walsall_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponents_11': 11, 'sheffield wednesday_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', 'opponents_7': 'opponents', 'walsall_8': 'walsall', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponents_11': 'opponents', 'sheffiel... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponents_7': [0], 'walsall_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponents_11': [1], 'sheffield wednesday_12': [1], 'date_13': [3]} | ['date', 'opponents', 'venue', 'result', 'score f - a'] | [['16 july 2007', 'hollenbach / hohenlohe auswahl', 'a', 'w', '2 - 0'], ['18 july 2007', '1 . fc heidenheim', 'a', 'w', '2 - 0'], ['23 july 2007', 'fc schweinfurt 05', 'a', 'w', '5 - 2'], ['28 july 2007', 'walsall', 'a', 'w', '2 - 0'], ['31 july 2007', 'peterborough united', 'a', 'w', '3 - 0'], ['4 august 2007', 'sheff... |
list of england national rugby union team results 1990 - 99 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1990%E2%80%9399 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178534-1.html.csv | aggregation | opposing teams scored a combined total of 53 against the england national rugby union team . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '53', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'against'], 'result': '53', 'ind': 0, 'tostr': 'sum { all_rows ; against }'}, '53'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; against } ; 53 } = true', 'tointer': 'the sum of the against record of all rows is 53 .'} | round_eq { sum { all_rows ; against } ; 53 } = true | the sum of the against record of all rows is 53 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'against_4': 4, '53_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'against_4': 'against', '53_5': '53'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'against_4': [0], '53_5': [1]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['ireland', '0', '20 / 01 / 1990', 'twickenham , london', 'five nations'], ['france', '7', '03 / 02 / 1990', 'parc des princes , paris', 'five nations'], ['wales', '6', '17 / 02 / 1990', 'twickenham , london', 'five nations'], ['scotland', '13', '17 / 03 / 1990', 'murrayfield , edinburgh', 'five nations'], ['argentina... |
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/1-1341865-20.html.csv | count | 5 incumbents were re - elected during the 1964 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're-elected', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re-elected .', 'tostr': 'filter_eq { all_rows ; result ; re-elected }'}], 'result': '5', 'ind': 1, 'tost... | eq { count { filter_eq { all_rows ; result ; re-elected } } ; 5 } = true | select the rows whose result record fuzzily matches to re-elected . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're-elected_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're-elected_6': 're-elected', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're-elected_6': [0], '5_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', 'f edward hebert', 'democratic', '1940', 're - elected', 'f edward hebert ( d ) unopposed'], ['louisiana 2', 'hale boggs', 'democratic', '1946', 're - elected', 'hale boggs ( d ) 55.0 % david c treen ( r ) 45.0 %'], ['louisiana 4', 'joe waggonner', 'democratic', '1961', 're - elected', 'joe waggonner (... |
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 | superlative | sean weatherspoon was picked in the earliest round of all the players . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'round'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; round }'}, 'name'], 'result': 'sean weatherspoon', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; round } ; name }'}, 'sean weatherspoon'], 'result': True, 'i... | eq { hop { argmin { all_rows ; round } ; name } ; sean weatherspoon } = true | select the row whose round record of all rows is minimum . the name record of this row is sean weatherspoon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'round_5': 5, 'name_6': 6, 'sean weatherspoon_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'round_5': 'round', 'name_6': 'name', 'sean weatherspoon_7': 'sean weatherspoon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'round_5': [0], 'name_6': [1], 'sean weatherspoon_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... |
philippe étancelin | https://en.wikipedia.org/wiki/Philippe_%C3%89tancelin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235932-2.html.csv | unique | maserati straight - 6 is the only engine used once . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'maserati straight - 6', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'maserati straight - 6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to maserati straight - 6 .', 'tostr': 'filter_eq { all_rows ; engine ; maserati straight - 6 }'}], 'result': True, 'ind':... | only { filter_eq { all_rows ; engine ; maserati straight - 6 } } = true | select the rows whose engine record fuzzily matches to maserati straight - 6 . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'engine_4': 4, 'maserati straight - 6_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'engine_4': 'engine', 'maserati straight - 6_5': 'maserati straight - 6'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'engine_4': [0], 'maserati straight - 6_5': [0]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1950', 'philippe étancelin', 'talbot - lago t26c', 'talbot straight - 6', '3'], ['1950', 'automobiles talbot - darracq', 'talbot - lago t26c da', 'talbot straight - 6', '3'], ['1950', 'philippe étancelin', 'talbot - lago t26c da', 'talbot straight - 6', '3'], ['1951', 'philippe étancelin', 'talbot - lago t26c da', '... |
mars hill network | https://en.wikipedia.org/wiki/Mars_Hill_Network | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12454334-1.html.csv | aggregation | the radio channels on the mars hill network broadcast with an average erp/power wattage of 6012 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '6012', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'erp / power w'], 'result': '6012', 'ind': 0, 'tostr': 'avg { all_rows ; erp / power w }'}, '6012'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; erp / power w } ; 6012 } = true', 'tointer': 'the average of the erp / power w record of... | round_eq { avg { all_rows ; erp / power w } ; 6012 } = true | the average of the erp / power w record of all rows is 6012 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'erp / power w_4': 4, '6012_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'erp / power w_4': 'erp / power w', '6012_5': '6012'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'erp / power w_4': [0], '6012_5': [1]} | ['call sign', 'frequency', 'city of license', 'facility id', 'erp / power w', 'height m ( ft )', 'class'] | [['wmhi', '94.7 fm', 'cape vincent , ny', '40435', '5800', '-', 'a'], ['wmhn', '89.3 fm', 'webster , ny', '40430', '1000', '-', 'a'], ['wmhq', '90.1 fm', 'malone , ny', '89863', '2700', '-', 'a'], ['wmhr', '102.9 fm', 'syracuse , ny', '40432', '20000', '-', 'b'], ['wmhu', '91.1 fm', 'cold brook , ny', '174468', '560', ... |
1990 - 91 argentine primera división | https://en.wikipedia.org/wiki/1990%E2%80%9391_Argentine_Primera_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17968274-2.html.csv | unique | in the 1990-91 argentinian primera división , huracán was the only team that played fewer than 114 games and still maintained an average above 1.0 . | {'scope': 'subset', 'row': '7', 'col': '2', 'col_other': '1', 'criterion': 'greater_than', 'value': '1.0', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '114'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'played', '114'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; played ; 114 }', 'tointer': 'select the rows whose played record is less than 114 .'}, 'average', '1.0'], 're... | and { only { filter_greater { filter_less { all_rows ; played ; 114 } ; average ; 1.0 } } ; eq { hop { filter_greater { filter_less { all_rows ; played ; 114 } ; average ; 1.0 } ; team } ; huracán } } = true | select the rows whose played record is less than 114 . among these rows , select the rows whose average record is greater than 1.0 . there is only one such row in the table . the team record of this unqiue row is huracán . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_less_0': 0, 'all_rows_7': 7, 'played_8': 8, '114_9': 9, 'average_10': 10, '1.0_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'team_12': 12, 'huracán_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_less_0': 'filter_less', 'all_rows_7': 'all_rows', 'played_8': 'played', '114_9': '114', 'average_10': 'average', '1.0_11': '1.0', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'team_12': 'team', 'huracán_13': 'huracán'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_less_0': [1], 'all_rows_7': [0], 'played_8': [0], '114_9': [0], 'average_10': [1], '1.0_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'team_12': [3], 'huracán_13': [4]} | ['team', 'average', 'points', 'played', '1988 - 89', '1989 - 90', '1990 - 1991'] | [['boca juniors', '1.254', '143', '114', '49', '43', '51'], ['river plate', '1.254', '143', '114', '45', '53', '45'], ['independiente', '1.237', '141', '114', '55', '46', '40'], ['san lorenzo', '1.070', '122', '114', '42', '35', '45'], ['racing club', '1.061', '121', '114', '42', '39', '40'], ['vélez sársfield', '1.053... |
1981 senior pga tour | https://en.wikipedia.org/wiki/1981_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11622924-1.html.csv | superlative | the peter jackson champions had the highest purse of any event on the 1981 senior pga tour . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'purse'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; purse }'}, 'tournament'], 'result': 'peter jackson champions', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; purse } ; tournament }'}, 'peter jackson champio... | eq { hop { argmax { all_rows ; purse } ; tournament } ; peter jackson champions } = true | select the row whose purse record of all rows is maximum . the tournament record of this row is peter jackson champions . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'purse_5': 5, 'tournament_6': 6, 'peter jackson champions_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'purse_5': 'purse', 'tournament_6': 'tournament', 'peter jackson champions_7': 'peter jackson champions'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'purse_5': [0], 'tournament_6': [1], 'peter jackson champions_7': [2]} | ['date', 'tournament', 'location', 'purse', 'winner', 'score', '1st prize'] | [['apr 5', 'michelob - egypt temple senior classic', 'florida', '125000', 'don january ( 2 )', '280 ( - 8 )', '20000'], ['jun 7', 'eureka federal savings classic', 'california', '150000', 'don january ( 3 )', '208 ( - 5 )', '25000'], ['jun 14', 'peter jackson champions', 'canada', '200000', 'miller barber ( 1 )', '204 ... |
bojana jovanovski | https://en.wikipedia.org/wiki/Bojana_Jovanovski | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18183850-12.html.csv | count | bojana jovanovski played against the canadian team a total of two times . | {'scope': 'all', 'criterion': 'equal', 'value': 'canada', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent team', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent team record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; opponent team ; canada }'}], 'result': '2', 'ind':... | eq { count { filter_eq { all_rows ; opponent team ; canada } } ; 2 } = true | select the rows whose opponent team record fuzzily matches to canada . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent team_5': 5, 'canada_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent team_5': 'opponent team', 'canada_6': 'canada', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent team_5': [0], 'canada_6': [0], '2_7': [2]} | ['outcome', 'edition', 'round', 'opponent team', 'surface', 'opponent', 'score'] | [['loser', '2010', 'world group playoffs', 'slovakia', 'clay ( i )', 'daniela hantuchová', '6 - 2 , 6 - 2'], ['winner', '2010', 'world group playoffs', 'slovakia', 'clay ( i )', 'magdaléna rybáriková', '6 - 1 , 7 - 6 ( 7 - 4 )'], ['winner', '2011', 'world group ii', 'canada', 'hard ( i )', 'aleksandra wozniak', '6 - 4 ... |
1929 vfl season | https://en.wikipedia.org/wiki/1929_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10767118-15.html.csv | count | there were 6 game venues used during the 1929 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', ... | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '15.17 ( 107 )', 'north melbourne', '6.14 ( 50 )', 'mcg', '8421', '10 august 1929'], ['footscray', '11.6 ( 72 )', 'richmond', '14.15 ( 99 )', 'western oval', '13000', '10 august 1929'], ['essendon', '15.10 ( 100 )', 'hawthorn', '13.14 ( 92 )', 'windy hill', '11000', '10 august 1929'], ['collingwood', '13... |
mori no asagao | https://en.wikipedia.org/wiki/Mori_no_Asagao | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29039942-1.html.csv | superlative | the highest ratings that mori no asagao had was for episode three . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'ratings ( kanto )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; ratings ( kanto ) }'}, 'episode'], 'result': '3', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; ratings ( kanto ) } ; episode }'}, '3'], 'result': Tr... | eq { hop { argmax { all_rows ; ratings ( kanto ) } ; episode } ; 3 } = true | select the row whose ratings ( kanto ) record of all rows is maximum . the episode record of this row is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'ratings (kanto)_5': 5, 'episode_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'ratings (kanto)_5': 'ratings ( kanto )', 'episode_6': 'episode', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'ratings (kanto)_5': [0], 'episode_6': [1], '3_7': [2]} | ['episode', 'title', 'writer', 'director', 'original airdate', 'ratings ( kanto )'] | [['2', 'instruction execution ( 死刑執行命令 )', 'daisuke habara', 'akimitsu sasaki', 'oct 25 , 2010 22.00 - 22.54', '3.8'], ['3', 'give flowers to the condemned ( 死刑囚へ贈る花 )', 'shizuka oki', 'makito murakami', 'nov 1 , 2010 22.00 - 22.54', '4.6'], ['4', 'wedding bride prison ( 獄中結婚の花嫁 )', 'daisuke habara', 'makito murakami',... |
1962 washington redskins season | https://en.wikipedia.org/wiki/1962_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15122771-2.html.csv | aggregation | during the 1962 season , games played against the philadelphia eagles had an average attendance of 46450 . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '46450', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'philadelphia eagles'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'philadelphia eagles'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; philadelphia eagles }', 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles... | round_eq { avg { filter_eq { all_rows ; opponent ; philadelphia eagles } ; attendance } ; 46450 } = true | select the rows whose opponent record fuzzily matches to philadelphia eagles . the average of the attendance record of these rows is 46450 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'philadelphia eagles_6': 6, 'attendance_7': 7, '46450_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'philadelphia eagles_6': 'philadelphia eagles', 'attendance_7': 'attendance', '46450_8': '46450'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'philadelphia eagles_6': [0], 'attendance_7': [1], '46450_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 16 , 1962', 'dallas cowboys', 't 35 - 35', '15730'], ['2', 'september 23 , 1962', 'cleveland browns', 'w 17 - 16', '57491'], ['3', 'september 30 , 1962', 'st louis cardinals', 'w 24 - 14', '37419'], ['4', 'october 7 , 1962', 'los angeles rams', 'w 20 - 14', '18104'], ['5', 'october 14 , 1962', 'st lou... |
1995 - 96 winnipeg jets season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Winnipeg_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14052745-12.html.csv | majority | almost all of the players in the 1995-96 winnipeg jets season were of canadian nationality . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to canada .', 'tostr': 'most_eq { all_rows ; nationality ; canada } = true'} | most_eq { all_rows ; nationality ; canada } = true | for the nationality records of all rows , most of them fuzzily match to canada . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'canada_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'canada_4': 'canada'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'canada_4': [0]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team'] | [['1', 'shane doan', 'centre', 'canada', 'kamloops blazers ( whl )'], ['2', 'marc chouinard', 'centre', 'canada', 'beauport harfangs ( qmjhl )'], ['2', 'jason doig', 'defence', 'canada', 'laval titan collège français ( qmjhl )'], ['3', 'brad isbister', 'defence', 'canada', 'portland winter hawks ( whl )'], ['4', 'justi... |
1960 american football league season | https://en.wikipedia.org/wiki/1960_American_Football_League_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11379937-4.html.csv | comparative | jack kemp ran the ball more yards than tom flores . | {'row_1': '2', 'row_2': '7', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jack kemp ( la )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jack kemp ( la ) .', 'tostr': 'filter_eq { all_rows ; player ; jack kemp ( la ) }'}, 'yards... | greater { hop { filter_eq { all_rows ; player ; jack kemp ( la ) } ; yards } ; hop { filter_eq { all_rows ; player ; tom flores ( oak ) } ; yards } } = true | select the rows whose player record fuzzily matches to jack kemp ( la ) . take the yards record of this row . select the rows whose player record fuzzily matches to tom flores ( oak ) . take the yards 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, 'jack kemp (la)_8': 8, 'yards_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'tom flores (oak)_12': 12, 'yards_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', 'jack kemp (la)_8': 'jack kemp ( la )', 'yards_9': 'yards', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'jack kemp (la)_8': [0], 'yards_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'tom flores (oak)_12': [1], 'yards_13': [3]} | ['player', 'comp', 'att', 'comp %', 'yards', "td 's", "int 's"] | [['frank tripucka ( den )', '248', '478', '51.8', '3038', '24', '34'], ['jack kemp ( la )', '211', '406', '52', '3018', '20', '25'], ['al dorow ( nyt )', '201', '396', '50.8', '2748', '26', '26'], ['butch songin ( bos )', '187', '392', '47.7', '2476', '22', '15'], ['cotton davidson ( dal )', '179', '379', '47.2', '2474... |
2008 - 09 philadelphia flyers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17511295-5.html.csv | ordinal | the philadelphia flyers game that took place on december 13 had the 4th highest attendance . | {'row': '6', 'col': '6', 'order': '4', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 4 }'}, 'date'], 'result': 'december 13', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 4 } ; date }'}, 'decem... | eq { hop { nth_argmax { all_rows ; attendance ; 4 } ; date } ; december 13 } = true | select the row whose attendance record of all rows is 4th maximum . the date record of this row is december 13 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '4_6': 6, 'date_7': 7, 'december 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', 'attendance_5': 'attendance', '4_6': '4', 'date_7': 'date', 'december 13_8': 'december 13'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '4_6': [0], 'date_7': [1], 'december 13_8': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 2', 'tampa bay', '3 - 4', 'philadelphia', 'biron', '19227', '12 - 7 - 5'], ['december 4', 'new jersey', '3 - 2', 'philadelphia', 'biron', '19577', '12 - 7 - 6'], ['december 6', 'philadelphia', '2 - 1', 'carolina', 'niittymaki', '14061', '13 - 7 - 6'], ['december 9', 'ny islanders', '3 - 4', 'philadelphia', ... |
1992 - 93 in argentine football | https://en.wikipedia.org/wiki/1992%E2%80%9393_in_Argentine_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14371754-1.html.csv | ordinal | the river plate team recorded the 2nd highest average in the 1992 - 93 argentine football season . | {'row': '2', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'average', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; average ; 2 }'}, 'team'], 'result': 'river plate', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; average ; 2 } ; team }'}, 'river plate'],... | eq { hop { nth_argmax { all_rows ; average ; 2 } ; team } ; river plate } = true | select the row whose average record of all rows is 2nd maximum . the team record of this row is river plate . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'average_5': 5, '2_6': 6, 'team_7': 7, 'river plate_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', 'average_5': 'average', '2_6': '2', 'team_7': 'team', 'river plate_8': 'river plate'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'average_5': [0], '2_6': [0], 'team_7': [1], 'river plate_8': [2]} | ['team', 'average', 'points', 'played', '1991 - 92', '1992 - 93', '1993 - 94'] | [['boca juniors', '1.307', '149', '114', '51', '50', '48'], ['river plate', '1.281', '146', '114', '45', '55', '46'], ['vélez sársfield', '1.237', '141', '114', '45', '48', '48'], ['san lorenzo', '1.088', '124', '114', '45', '45', '45'], ['huracán', '1.061', '121', '114', '40', '38', '43'], ['independiente', '1.026', '... |
documentary film festivals | https://en.wikipedia.org/wiki/Documentary_film_festivals | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12757263-2.html.csv | count | 4 documentary film festivals took place in india . | {'scope': 'all', 'criterion': 'equal', 'value': 'india', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'india'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to india .', 'tostr': 'filter_eq { all_rows ; country ; india }'}], 'result': '4', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; country ; india } } ; 4 } = true | select the rows whose country record fuzzily matches to india . 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, 'country_5': 5, 'india_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', 'country_5': 'country', 'india_6': 'india', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'india_6': [0], '4_7': [2]} | ['name', 'est', 'city', 'country', 'website'] | [['development film festival', '2005', 'chennai', 'india', 'wwwdhanorg / dff'], ['culture unplugged film festival', '2007', 'india', 'india', 'wwwcultureunpluggedcom'], ['dox box - ayyam cinema al waqe', '2008', 'damascus', 'syria', 'wwwdox - boxorg'], ['freedom film fest', '2003', 'malaysia', 'malaysia', 'freedomfilmf... |
1986 pga championship | https://en.wikipedia.org/wiki/1986_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18150398-2.html.csv | unique | david graham was the only player to make the cut in the 1986 pga championship that was not from the united states . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'not_equal', 'value': 'united states', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record does not match to united states .', 'tostr': 'filter_not_eq { all_rows ; country ; united states }'}], 'result': T... | and { only { filter_not_eq { all_rows ; country ; united states } } ; eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; david graham } } = true | select the rows whose country record does not match to united states . there is only one such row in the table . the player record of this unqiue row is david graham . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'united states_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'david graham_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'united states_8': 'united states', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'david graham_10': 'david graham'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'united states_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'david graham_10': [3]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['david graham', 'australia', '1979', '282', '2', 't7'], ['lee trevino', 'united states', '1974 , 1984', '284', 'e', 't11'], ['lanny wadkins', 'united states', '1977', '284', 'e', 't11'], ['jack nicklaus', 'united states', '1963 , 1971 , 1973 1975 , 1980', '296', '+ 1', 't16'], ['hal sutton', 'united states', '1983', ... |
farsi1 | https://en.wikipedia.org/wiki/FARSI1 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28803803-1.html.csv | comparative | the show still standing was launched on farsi1 before falling angel . | {'row_1': '6', 'row_2': '2', 'col': '7', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'still standing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to still standing .', 'tostr': 'filter_eq { all_rows ; name ; still standing }'}, 'launched'], 'result'... | less { hop { filter_eq { all_rows ; name ; still standing } ; launched } ; hop { filter_eq { all_rows ; name ; falling angel } ; launched } } = true | select the rows whose name record fuzzily matches to still standing . take the launched record of this row . select the rows whose name record fuzzily matches to falling angel . take the launched 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, 'name_7': 7, 'still standing_8': 8, 'launched_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'falling angel_12': 12, 'launched_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', 'name_7': 'name', 'still standing_8': 'still standing', 'launched_9': 'launched', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'fallin... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'still standing_8': [0], 'launched_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'falling angel_12': [1], 'launched_13': [3]} | ['no', 'name', 'country', 'original channel', 'no of episodes', 'running time', 'launched', 'date', 'irst'] | [['1', "lara 's choice", 'croatia', 'nova tv ( 2011 )', '182', '45 minutes', '28 jul 2012', 'saturday to wednesday', '21:00 - 22:00'], ['2', 'falling angel', 'united states', 'telemundo ( 2009 )', '182', '45 minutes', '11 mar 2013', 'saturday to wednesday', '20:00 - 21:00'], ['3', 'elisa', 'italy', 'canale 5 ( 2003 )',... |
portland timbers ( 2001 - 10 ) | https://en.wikipedia.org/wiki/Portland_Timbers_%282001%E2%80%9310%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14240688-1.html.csv | aggregation | the portland timbers had an average attendance of 6854 from 2001 to 2009 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '6854', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'avg attendance'], 'result': '6854', 'ind': 0, 'tostr': 'avg { all_rows ; avg attendance }'}, '6854'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; avg attendance } ; 6854 } = true', 'tointer': 'the average of the avg attendance recor... | round_eq { avg { all_rows ; avg attendance } ; 6854 } = true | the average of the avg attendance record of all rows is 6854 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'avg attendance_4': 4, '6854_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'avg attendance_4': 'avg attendance', '6854_5': '6854'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'avg attendance_4': [0], '6854_5': [1]} | ['year', 'division', 'league', 'regular season', 'playoffs', 'open cup', 'avg attendance'] | [['2001', '2', 'usl a - league', '4th , western', 'quarterfinals', 'did not qualify', '7169'], ['2002', '2', 'usl a - league', '2nd , pacific', '1st round', 'did not qualify', '6260'], ['2003', '2', 'usl a - league', '3rd , pacific', 'did not qualify', 'did not qualify', '5871'], ['2004', '2', 'usl a - league', '1st , ... |
sim kwon - ho | https://en.wikipedia.org/wiki/Sim_Kwon-Ho | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16680101-1.html.csv | comparative | sim kwon - ho competed in a higher weight class at the 2000 summer olympics than he did in the 1996 summer olympics . | {'row_1': '1', 'row_2': '5', 'col': '3', 'col_other': '6', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2000 summer olympics'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2000 summer olympics .', 'tostr': 'filter_eq { all_rows ; competition ; 2000 ... | greater { hop { filter_eq { all_rows ; competition ; 2000 summer olympics } ; class } ; hop { filter_eq { all_rows ; competition ; 1996 summer olympics } ; class } } = true | select the rows whose competition record fuzzily matches to 2000 summer olympics . take the class record of this row . select the rows whose competition record fuzzily matches to 1996 summer olympics . take the class 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, 'competition_7': 7, '2000 summer olympics_8': 8, 'class_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'competition_11': 11, '1996 summer olympics_12': 12, 'class_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', 'competition_7': 'competition', '2000 summer olympics_8': '2000 summer olympics', 'class_9': 'class', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', ... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'competition_7': [0], '2000 summer olympics_8': [0], 'class_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'competition_11': [1], '1996 summer olympics_12': [1], 'class_13': [3]} | ['opponent', 'res', 'class', 'score', 'date', 'competition', 'notes'] | [['win', 'lã ¡ zaro rivas', '54 kg', '8:0', '2000 - 06 - 09', '2000 summer olympics', 'won second olympic gold medal'], ['win', 'shamseddin khudoyberdiev', '54 kg', '3:2', '1999 - 05 - 31', '1999 asian championships', 'won third asian championship gold medal'], ['win', 'kang yong - gyun', '54 kg', '5:5', '1998 - 12 - 1... |
1970 - 71 buffalo braves season | https://en.wikipedia.org/wiki/1970%E2%80%9371_Buffalo_Braves_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17062990-1.html.csv | ordinal | john hummer was the first picked in round 1 of the 1970-71 buffalo braves season . | {'scope': 'all', 'row': '1', 'col': '1', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'round', '1'], 'result': '1', 'ind': 0, 'tostr': 'nth_min { all_rows ; round ; 1 }', 'tointer': 'the 1st minimum round record of all rows is 1 .'}, '1'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; round ; 1 } ; ... | and { eq { nth_min { all_rows ; round ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; round ; 1 } ; player } ; john hummer } } = true | the 1st minimum round record of all rows is 1 . the player record of the row with 1st minimum round record is john hummer . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'round_8': 8, '1_9': 9, '1_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'round_12': 12, '1_13': 13, 'player_14': 14, 'john hummer_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'round_8': 'round', '1_9': '1', '1_10': '1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'round_12': 'round', '1_13': '1', 'player_14': 'player', 'john hummer_1... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'round_8': [0], '1_9': [0], '1_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'round_12': [2], '1_13': [2], 'player_14': [3], 'john hummer_15': [4]} | ['round', 'pick', 'player', 'nationality', 'college'] | [['1', '15', 'john hummer', 'united states', 'princeton'], ['2', '24', 'cornell warner', 'united states', 'jackson state'], ['3', '43', 'chip case', 'united states', 'virginia'], ['4', '58', 'ervin polnick', 'united states', 'austin state'], ['5', '77', 'robert moore', 'united states', 'central state'], ['6', '92', 'do... |
v - league 5th season 1st conference | https://en.wikipedia.org/wiki/V-League_5th_Season_1st_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16348031-7.html.csv | ordinal | the sixth-place team in the v - league 5th season 1st conference was the college of saint benilde , with four losses . | {'scope': 'all', 'row': '6', 'col': '1', 'order': '6', 'col_other': '2,3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'rank', '6'], 'result': '6', 'ind': 0, 'tostr': 'nth_min { all_rows ; rank ; 6 }', 'tointer': 'the 6th minimum rank record of all rows is 6 .'}, '6'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; rank ; 6 } ; 6 }'... | and { eq { nth_min { all_rows ; rank ; 6 } ; 6 } ; and { eq { hop { nth_argmin { all_rows ; rank ; 6 } ; team } ; college of saint benilde } ; eq { hop { nth_argmin { all_rows ; rank ; 6 } ; loss } ; 4 } } } = true | the 6th minimum rank record of all rows is 6 . the team record of the row with 6th minimum rank record is college of saint benilde . the loss record of the row with 6th minimum rank record is 4 . | 10 | 9 | {'and_8': 8, 'result_9': 9, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_10': 10, 'rank_11': 11, '6_12': 12, '6_13': 13, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_14': 14, 'rank_15': 15, '6_16': 16, 'team_17': 17, 'college of saint benilde_18': 18, 'eq_6': 6, 'num_hop_5': 5, 'loss_19': 19, '4_20':... | {'and_8': 'and', 'result_9': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_10': 'all_rows', 'rank_11': 'rank', '6_12': '6', '6_13': '6', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_14': 'all_rows', 'rank_15': 'rank', '6_16': '6', 'team_17': 'team', 'co... | {'and_8': [9], 'result_9': [], 'eq_1': [8], 'nth_min_0': [1], 'all_rows_10': [0], 'rank_11': [0], '6_12': [0], '6_13': [1], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'nth_argmin_2': [3, 5], 'all_rows_14': [2], 'rank_15': [2], '6_16': [2], 'team_17': [3], 'college of saint benilde_18': [4], 'eq_6': [7], 'num_hop_... | ['rank', 'team', 'loss', 'sets won', 'sets lost', 'percentage'] | [['1', 'ateneo de manila university', '0', '15', '2', '88 %'], ['2', 'lyceum of the philippines university', '1', '12', '5', '71 %'], ['3', 'university of saint la salle', '3', '9', '10', '47 %'], ['4', 'university of san jose - recoletos', '3', '9', '11', '45 %'], ['5', 'far eastern university', '4', '6', '14', '30 %'... |
list of sumo record holders | https://en.wikipedia.org/wiki/List_of_sumo_record_holders | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634218-22.html.csv | aggregation | for sumo record holders with over 13 total points , the average fighting spirit score is 5 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '5', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '13'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'total', '13'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; total ; 13 }', 'tointer': 'select the rows whose total record is greater than 13 .'}, 'fighting spirit'], 'result': '5', 'ind': 1, 'tostr... | round_eq { avg { filter_greater { all_rows ; total ; 13 } ; fighting spirit } ; 5 } = true | select the rows whose total record is greater than 13 . the average of the fighting spirit record of these rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'total_5': 5, '13_6': 6, 'fighting spirit_7': 7, '5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'total_5': 'total', '13_6': '13', 'fighting spirit_7': 'fighting spirit', '5_8': '5'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'total_5': [0], '13_6': [0], 'fighting spirit_7': [1], '5_8': [2]} | ['name', 'total', 'outstanding performance', 'fighting spirit', 'technique', 'years', 'highest rank'] | [['akinoshima', '19', '7', '8', '4', '1988 - 99', 'sekiwake'], ['kotonishiki', '18', '7', '3', '8', '1990 - 98', 'sekiwake'], ['kaiō', '15', '10', '5', '0', '1994 - 2000', 'ōzeki'], ['tsurugamine', '14', '2', '2', '10', '1956 - 66', 'sekiwake'], ['asashio', '14', '10', '3', '1', '1979 - 83', 'ōzeki'], ['takatōriki', '1... |
2009 - 10 washington wizards season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Washington_Wizards_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23274514-7.html.csv | majority | all the 2009 - 10 washington wizards season games were scheduled for the month of february . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'february', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'february'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to february .', 'tostr': 'all_eq { all_rows ; date ; february } = true'} | all_eq { all_rows ; date ; february } = true | for the date records of all rows , all of them fuzzily match to february . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'february_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'february_4': 'february'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'february_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['47', 'february 1', 'boston', 'l 88 - 99 ( ot )', 'caron butler ( 20 )', 'caron butler ( 11 )', 'randy foye ( 4 )', 'verizon center 20173', '16 - 31'], ['48', 'february 3', 'new york', 'l 85 - 107 ( ot )', 'foye & young ( 15 )', 'brendan haywood ( 8 )', 'earl boykins ( 6 )', 'madison square garden 19225', '16 - 32'],... |
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/1-10470082-8.html.csv | comparative | the tale of the time trap aired before the tale of the last dance . | {'row_1': '8', 'row_2': '10', 'col': '6', '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', 'title', 'the tale of the time trap'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to the tale of the time trap .', 'tostr': 'filter_eq { all_rows ; title ; the tale of the ... | less { hop { filter_eq { all_rows ; title ; the tale of the time trap } ; us air date } ; hop { filter_eq { all_rows ; title ; the tale of the last dance } ; us air date } } = true | select the rows whose title record fuzzily matches to the tale of the time trap . take the us air date record of this row . select the rows whose title record fuzzily matches to the tale of the last dance . take the us air date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'title_7': 7, 'the tale of the time trap_8': 8, 'us air date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'the tale of the last dance_12': 12, 'us air date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'title_7': 'title', 'the tale of the time trap_8': 'the tale of the time trap', 'us air date_9': 'us air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_row... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'the tale of the time trap_8': [0], 'us air date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'the tale of the last dance_12': [1], 'us air date_13': [3]} | ['no', '-', 'title', 'director', 'writer', 'us air date', 'storyteller', 'villains'] | [['79', '1', 'the tale of the silver sight , part 1', 'mark soulard', 'd j machale', 'april 2 , 2000', 'n / a', 'the evil spirit'], ['80', '2', 'the tale of the silver sight , part 2', 'mark soulard', 'd j machale', 'april 2 , 2000', 'n / a', 'the evil spirit'], ['81', '3', 'the tale of the silver sight , part 3', 'mar... |
1962 vfl season | https://en.wikipedia.org/wiki/1962_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10776868-18.html.csv | count | in the 1962 vfl season , among the game where home team scored above 12.00 , 2 of them drew attendance over 20000 people . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '20000', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '12'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '12'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; home team score ; 12 }', 'tointer': 'select the rows whose home team score record is greater th... | eq { count { filter_greater { filter_greater { all_rows ; home team score ; 12 } ; crowd ; 20000 } } ; 2 } = true | select the rows whose home team score record is greater than 12 . among these rows , select the rows whose crowd record is greater than 20000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'home team score_6': 6, '12_7': 7, 'crowd_8': 8, '20000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'home team score_6': 'home team score', '12_7': '12', 'crowd_8': 'crowd', '20000_9': '20000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'home team score_6': [0], '12_7': [0], 'crowd_8': [1], '20000_9': [1], '2_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '9.9 ( 63 )', 'richmond', '12.10 ( 82 )', 'arden street oval', '10602', '25 august 1962'], ['fitzroy', '5.14 ( 44 )', 'geelong', '18.14 ( 122 )', 'brunswick street oval', '18447', '25 august 1962'], ['essendon', '13.15 ( 93 )', 'south melbourne', '13.10 ( 88 )', 'windy hill', '20900', '25 august 19... |
north american catamaran racing association | https://en.wikipedia.org/wiki/North_American_Catamaran_Racing_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17002889-1.html.csv | superlative | the model n20 has the highest length over all among the sailboats in the north american catamaran racing association . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '20', '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', 'length over all'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; length over all }'}, 'model'], 'result': 'n20', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; length over all } ; model }'}, 'n20'], 'result': True... | eq { hop { argmax { all_rows ; length over all } ; model } ; n20 } = true | select the row whose length over all record of all rows is maximum . the model record of this row is n20 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'length over all_5': 5, 'model_6': 6, 'n20_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'length over all_5': 'length over all', 'model_6': 'model', 'n20_7': 'n20'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'length over all_5': [0], 'model_6': [1], 'n20_7': [2]} | ['model', 'length over all', 'beam', 'sail area', 'crew', 'comments'] | [['14sq', '4.5 m', '2.44', '14 m square', '1', 'daggerboards'], ['4.5', '4.50 m', '2.44 m', '17.5 m square', '1 - 2', 'skegs'], ['460', '4.50 m', '2.35 m', '15.2 m square', '1 - 2', 'skegs'], ['blast', '4.80 m', '2.45 m', '15.6 m square', '1 - 2', 'skegs design : alain comyn'], ['16sq', '5.0 m', '2.5 m', '16 m square',... |
1925 vfl season | https://en.wikipedia.org/wiki/1925_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746200-13.html.csv | count | there were 6 game venues used during the 1925 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', ... | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '8.11 ( 59 )', 'st kilda', '8.8 ( 56 )', 'glenferrie oval', '10000', '8 august 1925'], ['geelong', '11.20 ( 86 )', 'richmond', '4.8 ( 32 )', 'corio oval', '13500', '8 august 1925'], ['fitzroy', '17.18 ( 120 )', 'north melbourne', '11.8 ( 74 )', 'brunswick street oval', '7000', '8 august 1925'], ['south me... |
2009 open championship | https://en.wikipedia.org/wiki/2009_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811509-7.html.csv | count | in the 2009 open championship , there were three players from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '3', 'in... | eq { count { filter_eq { all_rows ; country ; united states } } ; 3 } = true | select the rows whose country record fuzzily matches to united states . 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, 'country_5': 5, 'united states_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', 'country_5': 'country', 'united states_6': 'united states', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '3_7': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'stewart cink', 'united states', '66 + 72 + 71 + 69 = 278', '2', 'playoff'], ['t1', 'tom watson', 'united states', '65 + 70 + 71 + 72 = 278', '2', 'playoff'], ['t3', 'lee westwood', 'england', '68 + 70 + 70 + 71 = 279', '1', '255000'], ['t3', 'chris wood', 'england', '70 + 70 + 72 + 67 = 279', '1', '255000'], [... |
sebastian prödl | https://en.wikipedia.org/wiki/Sebastian_Pr%C3%B6dl | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12253254-1.html.csv | majority | most of the competitions that sebastian prödl competed in took place in the same venue in vienna , austria . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'vienna , austria', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'venue', 'vienna , austria'], 'result': True, 'ind': 0, 'tointer': 'for the venue records of all rows , most of them fuzzily match to vienna , austria .', 'tostr': 'most_eq { all_rows ; venue ; vienna , austria } = true'} | most_eq { all_rows ; venue ; vienna , austria } = true | for the venue records of all rows , most of them fuzzily match to vienna , austria . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'venue_3': 3, 'vienna, austria_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'venue_3': 'venue', 'vienna, austria_4': 'vienna , austria'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'venue_3': [0], 'vienna, austria_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['26 march 2008', 'ernst - happel - stadion , vienna , austria', '2 - 0', '3 - 4', 'friendly'], ['26 march 2008', 'ernst - happel - stadion , vienna , austria', '3 - 0', '3 - 4', 'friendly'], ['8 october 2010', 'ernst - happel - stadion , vienna , austria', '1 - 0', '3 - 0', 'uefa euro 2012 qualifying'], ['15 october ... |
1974 world ice hockey championships | https://en.wikipedia.org/wiki/1974_World_Ice_Hockey_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14271063-1.html.csv | comparative | in the 1974 world ice hockey championships east germany had more losses than poland . | {'row_1': '6', 'row_2': '5', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'east germany'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to east germany .', 'tostr': 'filter_eq { all_rows ; team ; east germany }'}, 'lost'], 'result': None,... | greater { hop { filter_eq { all_rows ; team ; east germany } ; lost } ; hop { filter_eq { all_rows ; team ; poland } ; lost } } = true | select the rows whose team record fuzzily matches to east germany . take the lost record of this row . select the rows whose team record fuzzily matches to poland . take the lost 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, 'team_7': 7, 'east germany_8': 8, 'lost_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'poland_12': 12, 'lost_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', 'team_7': 'team', 'east germany_8': 'east germany', 'lost_9': 'lost', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'poland_12': ... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'east germany_8': [0], 'lost_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'poland_12': [1], 'lost_13': [3]} | ['team', 'games', 'drawn', 'lost', 'points difference', 'points'] | [['soviet union', '10', '0', '1', '64 - 18', '18'], ['czechoslovakia', '10', '0', '3', '57 - 20', '14'], ['sweden', '10', '1', '4', '38 - 24', '11'], ['finland', '10', '2', '4', '34 - 39', '10'], ['poland', '10', '2', '7', '22 - 64', '4'], ['east germany', '10', '1', '8', '19 - 82', '3']] |
united states presidential election in nevada , 2008 | https://en.wikipedia.org/wiki/United_States_presidential_election_in_Nevada%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20424014-1.html.csv | comparative | mccain took a higher percentage of the vote in eureka than he did in mineral . | {'row_1': '7', 'row_2': '12', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'eureka'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to eureka .', 'tostr': 'filter_eq { all_rows ; county ; eureka }'}, 'mccain %'], 'result': None, 'ind': ... | greater { hop { filter_eq { all_rows ; county ; eureka } ; mccain % } ; hop { filter_eq { all_rows ; county ; mineral } ; mccain % } } = true | select the rows whose county record fuzzily matches to eureka . take the mccain % record of this row . select the rows whose county record fuzzily matches to mineral . take the mccain % 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, 'county_7': 7, 'eureka_8': 8, 'mccain %_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'county_11': 11, 'mineral_12': 12, 'mccain %_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', 'county_7': 'county', 'eureka_8': 'eureka', 'mccain %_9': 'mccain %', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'county_11': 'county', 'mineral_... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'county_7': [0], 'eureka_8': [0], 'mccain %_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'county_11': [1], 'mineral_12': [1], 'mccain %_13': [3]} | ['county', 'mccain', 'mccain %', 'obama', 'obama %'] | [['carson city', '11419', '48.2 %', '11623', '49.1 %'], ['churchill', '6832', '64.4 %', '3494', '33.0 %'], ['clark', '257078', '39.5 %', '380765', '58.5 %'], ['douglas', '14648', '56.6 %', '10672', '41.2 %'], ['elko', '10969', '68.5 %', '4541', '28.4 %'], ['esmeralda', '303', '69.0 %', '104', '23.7 %'], ['eureka', '564... |
usa today all - usa high school baseball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-3.html.csv | majority | most of the players in the usa high school baseball team have been already drafted . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'draft', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'mlb draft', 'draft'], 'result': True, 'ind': 0, 'tointer': 'for the mlb draft records of all rows , most of them fuzzily match to draft .', 'tostr': 'most_eq { all_rows ; mlb draft ; draft } = true'} | most_eq { all_rows ; mlb draft ; draft } = true | for the mlb draft records of all rows , most of them fuzzily match to draft . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'mlb draft_3': 3, 'draft_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'mlb draft_3': 'mlb draft', 'draft_4': 'draft'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'mlb draft_3': [0], 'draft_4': [0]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['ben davis', 'catcher', 'malvern prep', 'malvern , pa', '1st round - 2nd pick of 1995 draft ( padres )'], ['chad hutchinson', 'pitcher', 'torrey pines high school', 'san diego , ca', 'attended stanford'], ['kerry wood', 'pitcher', 'grand prairie high school', 'grand prairie , tx', '1st round - 4th pick of 1995 draft ... |
loongson | https://en.wikipedia.org/wiki/Loongson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1764207-1.html.csv | ordinal | the l3c model processor is the loongson processor that has the second highest amount of cores . | {'row': '12', 'col': '5', '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', 'cores', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; cores ; 2 }'}, 'model'], 'result': 'l3c', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; cores ; 2 } ; model }'}, 'l3c'], 'result': True, 'in... | eq { hop { nth_argmax { all_rows ; cores ; 2 } ; model } ; l3c } = true | select the row whose cores record of all rows is 2nd maximum . the model record of this row is l3c . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'cores_5': 5, '2_6': 6, 'model_7': 7, 'l3c_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', 'cores_5': 'cores', '2_6': '2', 'model_7': 'model', 'l3c_8': 'l3c'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'cores_5': [0], '2_6': [0], 'model_7': [1], 'l3c_8': [2]} | ['name / generation', 'model', 'frequency', 'architecture version', 'cores', 'process'] | [['godson - 1 ( embedded cpu )', '1', '266', 'mips32', '1', '180'], ['godson - 1 ( embedded cpu )', '1a', '300', 'mips32', '1', '130'], ['godson - 1 ( embedded cpu )', '1b', '200', 'mips32', '1', '130'], ['godson - 2 ( singlecore )', '2b', '250', 'mips - iii 64 - bit', '1', '180'], ['godson - 2 ( singlecore )', '2c', '... |
seattle | https://en.wikipedia.org/wiki/Seattle | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11388236-2.html.csv | aggregation | the total number of championships won by teams from seattle from 1977 to 2012 is 2 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'championships'], 'result': '2', 'ind': 0, 'tostr': 'sum { all_rows ; championships }'}, '2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; championships } ; 2 } = true', 'tointer': 'the sum of the championships record of all rows is ... | round_eq { sum { all_rows ; championships } ; 2 } = true | the sum of the championships record of all rows is 2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'championships_4': 4, '2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'championships_4': 'championships', '2_5': '2'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'championships_4': [0], '2_5': [1]} | ['club', 'sport', 'league', 'venue', 'established', 'championships'] | [['seattle mariners', 'baseball', 'mlb', 'safeco field', '1977', '0'], ['seattle seahawks', 'football', 'nfl', 'centurylink field', '1976', '0'], ['seattle sounders fc', 'soccer', 'mls', 'centurylink field', '2007', '0'], ['seattle storm', 'basketball', 'wnba', 'keyarena', '2000', '2'], ['seattle reign fc', 'soccer', '... |
list of number - one singles of 1981 ( canada ) | https://en.wikipedia.org/wiki/List_of_number-one_singles_of_1981_%28Canada%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15476957-1.html.csv | count | a total of four songs spent exactly 2 weeks on the top of the 1981 canadian chart . | {'scope': 'all', 'criterion': 'equal', 'value': '2', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'weeks on top', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weeks on top record is equal to 2 .', 'tostr': 'filter_eq { all_rows ; weeks on top ; 2 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_... | eq { count { filter_eq { all_rows ; weeks on top ; 2 } } ; 4 } = true | select the rows whose weeks on top record is equal to 2 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'weeks on top_5': 5, '2_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'weeks on top_5': 'weeks on top', '2_6': '2', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'weeks on top_5': [0], '2_6': [0], '4_7': [2]} | ['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist'] | [['34:6 - 8', '20 december 1980 - 31 january 1981', '7', '( just like ) starting over', 'john lennon'], ['34:9 - 12', '7 - 28 february', '4', 'the tide is high', 'blondie'], ['34:13', '7 march', '1', 'the best of times', 'styx'], ['34:14 - 15', '14 - 21 march', '2', 'woman', 'john lennon'], ['34:16 - 18', '28 march - 1... |
gary mcallister | https://en.wikipedia.org/wiki/Gary_McAllister | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1586620-1.html.csv | comparative | gary mcallister played in hampden park before he played in varsity stadium . | {'row_1': '1', 'row_2': '2', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'hampden park , glasgow , scotland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to hampden park , glasgow , scotland .', 'tostr': 'filter_eq { all_rows ; venue ; ... | less { hop { filter_eq { all_rows ; venue ; hampden park , glasgow , scotland } ; date } ; hop { filter_eq { all_rows ; venue ; varsity stadium , toronto , canada } ; date } } = true | select the rows whose venue record fuzzily matches to hampden park , glasgow , scotland . take the date record of this row . select the rows whose venue record fuzzily matches to varsity stadium , toronto , canada . 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, 'venue_7': 7, 'hampden park , glasgow , scotland_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'varsity stadium , toronto , canada_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', 'venue_7': 'venue', 'hampden park , glasgow , scotland_8': 'hampden park , glasgow , scotland', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_r... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'hampden park , glasgow , scotland_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'varsity stadium , toronto , canada_12': [1], 'date_13': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['17 october 1990', 'hampden park , glasgow , scotland', '2 - 1', 'win', 'uefa euro 1992 qualifying'], ['20 may 1992', 'varsity stadium , toronto , canada', '1 - 3', 'win', 'friendly'], ['18 june 1992', 'idrottsparken , norrköping , sweden', '0 - 3', 'win', 'uefa euro 1992'], ['8 june 1997', 'dynama stadium , minsk , ... |
united states house of representatives elections , 1960 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1960 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341897-6.html.csv | ordinal | dale alford is the incumbent with latest first elected year among the incumbents of the 1960 house of representatives elections . | {'row': '5', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'dale alford', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; first elected ; 1 } ; in... | eq { hop { nth_argmax { all_rows ; first elected ; 1 } ; incumbent } ; dale alford } = true | select the row whose first elected record of all rows is 1st maximum . the incumbent record of this row is dale alford . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'dale alford_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', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'dale alford_8': 'dale alford'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'dale alford_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'ezekiel c gathings', 'democratic', '1938', 're - elected', 'ezekiel c gathings ( d ) unopposed'], ['arkansas 2', 'wilbur mills', 'democratic', '1938', 're - elected', 'wilbur mills ( d ) unopposed'], ['arkansas 3', 'james william trimble', 'democratic', '1944', 're - elected', 'james william trimble ( ... |
emergency shipbuilding program | https://en.wikipedia.org/wiki/Emergency_Shipbuilding_program | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11552751-2.html.csv | majority | most of the ones with a 1st ship delivery date in the year 1942 were located in the state of california . | {'scope': 'subset', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'california', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': '1942'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st ship delivery date', '1942'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; 1st ship delivery date ; 1942 }', 'tointer': 'select the rows whose 1st ship delivery date record fuzzily matches to 1942 .'}, 'location ( city , ... | most_eq { filter_eq { all_rows ; 1st ship delivery date ; 1942 } ; location ( city , state ) ; california } = true | select the rows whose 1st ship delivery date record fuzzily matches to 1942 . for the location ( city , state ) records of these rows , most of them fuzzily match to california . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, '1st ship delivery date_4': 4, '1942_5': 5, 'location (city , state)_6': 6, 'california_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', '1st ship delivery date_4': '1st ship delivery date', '1942_5': '1942', 'location (city , state)_6': 'location ( city , state )', 'california_7': 'california'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], '1st ship delivery date_4': [0], '1942_5': [0], 'location (city , state)_6': [1], 'california_7': [1]} | ['yard name', 'location ( city , state )', '1st ship delivery date', 'ship types delivered', 'total number of ways', 'total vessels built'] | [['moore dry dock company', 'oakland , california', 'july 1940', 'c2 type , r2 type , c3 type', '4 ways', '__ ships for usmc ( remainder for usn )'], ['bethlehem steel corp', 'san francisco , california', 'february 1941', 'c1 type', 'number', '5 ships for usmc ( remainder for usn )'], ['seattle - tacoma shipbuilding', ... |
my love : essential collection | https://en.wikipedia.org/wiki/My_Love%3A_Essential_Collection | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18969843-5.html.csv | ordinal | the first date that my love was released was on october 24 , 2008 . | {'row': '1', 'col': '2', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '1'], 'result': 'october 24 , 2008', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 1 }', 'tointer': 'the 1st minimum date record of all rows is october 24 , 2008 .'}, 'october 24 , 2008'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_r... | eq { nth_min { all_rows ; date ; 1 } ; october 24 , 2008 } = true | the 1st minimum date record of all rows is october 24 , 2008 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'date_4': 4, '1_5': 5, 'october 24 , 2008_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'date_4': 'date', '1_5': '1', 'october 24 , 2008_6': 'october 24 , 2008'} | {'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'date_4': [0], '1_5': [0], 'october 24 , 2008_6': [1]} | ['region', 'date', 'label', 'format', 'catalog'] | [['europe', 'october 24 , 2008', 'columbia', 'cd', '88697400492'], ['europe', 'october 24 , 2008', 'columbia', '2cd', '88697400502'], ['australia', 'october 27 , 2008', 'columbia', '2cd', '88697374522'], ['north america', 'october 28 , 2008', 'columbia', 'cd', '88697411432'], ['north america', 'october 28 , 2008', 'col... |
karin knapp | https://en.wikipedia.org/wiki/Karin_Knapp | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11522060-6.html.csv | majority | most of the tournaments were played on a clay surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', '6 october 2003', 'bari , italy', 'clay', 'bettina pirker', '6 - 2 , 7 - 5'], ['runner - up', '14 june 2005', 'lenzerheide , switzerland', 'clay', 'danica krstajić', '6 - 2 , 7 - 5'], ['runner - up', '1 may 2006', 'catania , italy', 'clay', 'maría josé martínez sánchez', '6 - 3 , 4 - 6 , 6 - 4'], ['win... |
vampiro | https://en.wikipedia.org/wiki/Vampiro | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1848273-1.html.csv | comparative | among wrestler vampiro 's luchas de apuestas records , the competition held in houston , texas occurred earlier than the one held in zapopan , jalisco . | {'row_1': '6', 'row_2': '10', 'col': '5', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'houston , texas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to houston , texas .', 'tostr': 'filter_eq { all_rows ; location ; houston , texas }'}, 'date'... | less { hop { filter_eq { all_rows ; location ; houston , texas } ; date } ; hop { filter_eq { all_rows ; location ; zapopan , jalisco } ; date } } = true | select the rows whose location record fuzzily matches to houston , texas . take the date record of this row . select the rows whose location record fuzzily matches to zapopan , jalisco . 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, 'location_7': 7, 'houston , texas_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'location_11': 11, 'zapopan , jalisco_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', 'location_7': 'location', 'houston , texas_8': 'houston , texas', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'location_11': 'location... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'location_7': [0], 'houston , texas_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'location_11': [1], 'zapopan , jalisco_12': [1], 'date_13': [3]} | ['wager', 'winner', 'loser', 'location', 'date'] | [['hair', 'vampiro', 'bestia negra ii', 'xochimilco , mexico city', 'march 21 , 1992'], ['hair', 'vampiro', 'rick patterson', 'monterrey , nuevo león', 'june 28 , 1992'], ['hair', 'vampiro', 'pirata morgan', 'mexico city', 'july 17 , 1992'], ['hair', 'vampiro', 'aaron grundy', 'monterrey , nuevo león', 'august 23 , 199... |
balloon satellite | https://en.wikipedia.org/wiki/Balloon_satellite | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2150068-1.html.csv | comparative | the echo 2 balloon satellite has a higher mass than the mylar balloon . | {'row_1': '4', 'row_2': '8', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'satellite', 'echo 2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose satellite record fuzzily matches to echo 2 .', 'tostr': 'filter_eq { all_rows ; satellite ; echo 2 }'}, 'mass ( kg )'], 'result': N... | greater { hop { filter_eq { all_rows ; satellite ; echo 2 } ; mass ( kg ) } ; hop { filter_eq { all_rows ; satellite ; mylar balloon } ; mass ( kg ) } } = true | select the rows whose satellite record fuzzily matches to echo 2 . take the mass ( kg ) record of this row . select the rows whose satellite record fuzzily matches to mylar balloon . take the mass ( kg ) 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, 'satellite_7': 7, 'echo 2_8': 8, 'mass (kg)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'satellite_11': 11, 'mylar balloon_12': 12, 'mass (kg)_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', 'satellite_7': 'satellite', 'echo 2_8': 'echo 2', 'mass (kg)_9': 'mass ( kg )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'satellite_11': 'satel... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'satellite_7': [0], 'echo 2_8': [0], 'mass (kg)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'satellite_11': [1], 'mylar balloon_12': [1], 'mass (kg)_13': [3]} | ['satellite', 'launch date ( utc )', 'decay', 'mass ( kg )', 'diameter ( m )', 'nssdc id', 'nation', 'usage'] | [['echo 1', '1960 - 08 - 12 09:36:00', '1968 - 05 - 24', '180', '30.48', '1960 - 009a', 'us', 'pcr , ado , spc , tri'], ['explorer 9', '1961 - 02 - 16 13:12:00', '1964 - 04 - 09', '36', '3.66', '1961 - 004a', 'us', 'ado'], ['explorer 19 ( ad - a )', '1963 - 12 - 19 18:43:00', '1981 - 10 - 05', '7.7', '3.66', '1963 - 05... |
united states national rugby union team | https://en.wikipedia.org/wiki/United_States_national_rugby_union_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1145226-7.html.csv | majority | for the united states national rugby union team , the majority of the time , mike hercus had 0 tries . | {'scope': 'subset', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'mike hercus'}} | {'func': 'most_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'mike hercus'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; player ; mike hercus }', 'tointer': 'select the rows whose player record fuzzily matches to mike hercus .'}, 'tries', '0'], 'result': True, 'ind': 1, 'tointer'... | most_eq { filter_eq { all_rows ; player ; mike hercus } ; tries ; 0 } = true | select the rows whose player record fuzzily matches to mike hercus . for the tries records of these rows , most of them are equal to 0 . | 2 | 2 | {'most_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'player_4': 4, 'mike hercus_5': 5, 'tries_6': 6, '0_7': 7} | {'most_eq_1': 'most_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'player_4': 'player', 'mike hercus_5': 'mike hercus', 'tries_6': 'tries', '0_7': '0'} | {'most_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'player_4': [0], 'mike hercus_5': [0], 'tries_6': [1], '0_7': [1]} | ['player', 'tries', 'conv', 'pens', 'drop', 'venue', 'date'] | [["chris o'brien", '3', '7', '0', '0', 'montevideo', '05 / 11 / 1989'], ['mike hercus', '1', '3', '4', '1', 'tokyo', '30 / 05 / 2004'], ['mike hercus', '0', '13', '0', '0', 'santa clara', '01 / 07 / 2006'], ["chris o'brien", '2', '6', '1', '0', 'hamilton', '12 / 03 / 1994'], ['matt alexander', '1', '8', '1', '0', 'san ... |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-35.html.csv | count | in the united states house of representatives election in 2000 , when the incumbent was re-elected , there were 2 times they were first elected in 1990 . | {'scope': 'subset', 'criterion': 'equal', 'value': '1990', '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', 'results', 're - elected'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; results ; re - elected }', 'tointer': 'select the rows whose results record fuzzily matches to re - elec... | eq { count { filter_eq { filter_eq { all_rows ; results ; re - elected } ; first elected ; 1990 } } ; 2 } = true | select the rows whose results record fuzzily matches to re - elected . among these rows , select the rows whose first elected record is equal to 1990 . 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, 'results_6': 6, 're - elected_7': 7, 'first elected_8': 8, '1990_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', 'results_6': 'results', 're - elected_7': 're - elected', 'first elected_8': 'first elected', '1990_9': '1990', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'results_6': [0], 're - elected_7': [0], 'first elected_8': [1], '1990_9': [1], '2_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['ohio 1', 'steve chabot', 'republican', '1994', 're - elected', 'steve chabot ( r ) 54 % john cranley ( d ) 45 %'], ['ohio 3', 'tony p hall', 'democratic', '1978', 're - elected', 'tony p hall ( d ) 83 %'], ['ohio 4', 'michael g oxley', 'republican', '1981', 're - elected', 'michael g oxley ( r ) 68 % daniel dickman ... |
fiba eurobasket 2007 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-1.html.csv | unique | the only eurobasket player born in 1979 is konstantinos tsartsaris . | {'scope': 'all', 'row': '9', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '1979', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year born', '1979'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year born record is equal to 1979 .', 'tostr': 'filter_eq { all_rows ; year born ; 1979 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_... | and { only { filter_eq { all_rows ; year born ; 1979 } } ; eq { hop { filter_eq { all_rows ; year born ; 1979 } ; player } ; konstantinos tsartsaris } } = true | select the rows whose year born record is equal to 1979 . there is only one such row in the table . the player record of this unqiue row is konstantinos tsartsaris . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'year born_7': 7, '1979_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'konstantinos tsartsaris_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'year born_7': 'year born', '1979_8': '1979', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'konstantinos tsartsaris_10': 'konstantinos tsartsaris'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'year born_7': [0], '1979_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'konstantinos tsartsaris_10': [3]} | ['player', 'height', 'position', 'year born', 'current club'] | [['theodoros papaloukas', '2.00', 'guard', '1977', 'cska moscow'], ['ioannis bourousis', '2.13', 'center', '1983', 'olympiacos'], ['nikolaos zisis', '1.95', 'guard', '1983', 'cska moscow'], ['vasileios spanoulis', '1.92', 'guard', '1982', 'panathinaikos'], ['panagiotis vasilopoulos', '2.01', 'forward', '1984', 'olympia... |
korean tour | https://en.wikipedia.org/wiki/Korean_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11613207-1.html.csv | majority | most tournaments of the korean tour are worth a total of six points each . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '6', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'owgr points', '6'], 'result': True, 'ind': 0, 'tointer': 'for the owgr points records of all rows , most of them are equal to 6 .', 'tostr': 'most_eq { all_rows ; owgr points ; 6 } = true'} | most_eq { all_rows ; owgr points ; 6 } = true | for the owgr points records of all rows , most of them are equal to 6 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'owgr points_3': 3, '6_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'owgr points_3': 'owgr points', '6_4': '6'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'owgr points_3': [0], '6_4': [0]} | ['dates', 'tournament', 'location', 'prize fund ( krw )', 'winner', 'owgr points'] | [['apr 25 - 28', "ballantine 's championship", 'icheon', '2205000', 'brett rumford', '34'], ['may 9 - 12', 'gs caltex maekyung open', 'seongnam', '1000000000', 'ryu hyun - woo', '8'], ['may 16 - 19', 'sk telecom open', 'seogwipo', '900000000', 'matthew griffin', '6'], ['may 23 - 26', 'happiness kwangju bank open', 'naj... |
list of top 10 singles in 2010 ( scotland ) | https://en.wikipedia.org/wiki/List_of_Top_10_singles_in_2010_%28Scotland%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27813010-2.html.csv | superlative | meet me halfway was the earliest single entered of the top 10 singles in 2010 . | {'scope': 'all', 'col_superlative': '1', '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', 'entry date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; entry date }'}, 'single'], 'result': 'meet me halfway', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; entry date } ; single }'}, 'meet me halfway'], 're... | eq { hop { argmin { all_rows ; entry date } ; single } ; meet me halfway } = true | select the row whose entry date record of all rows is minimum . the single record of this row is meet me halfway . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'entry date_5': 5, 'single_6': 6, 'meet me halfway_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'entry date_5': 'entry date', 'single_6': 'single', 'meet me halfway_7': 'meet me halfway'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'entry date_5': [0], 'single_6': [1], 'meet me halfway_7': [2]} | ['entry date', 'single', 'artist', 'peak', 'peak reached', 'weeks in top 10'] | [['31 october', 'meet me halfway', 'the black eyed peas', '1', '21 november', '11'], ['7 november', 'bad romance', 'lady gaga', '1', '19 december', '12'], ['5 december', 'the official bbc children in need medley', 'peter kay', '1', '5 december', '5'], ['5 december', 'russian roulette', 'rihanna', '3', '12 december', '6... |
latin americans | https://en.wikipedia.org/wiki/Latin_Americans | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1333612-1.html.csv | count | a total of four countries in latin america have a native american population of 0.0 % . | {'scope': 'all', 'criterion': 'equal', 'value': '0.0 %', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'native american', '0.0 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose native american record fuzzily matches to 0.0 % .', 'tostr': 'filter_eq { all_rows ; native american ; 0.0 % }'}], 'result': '4', 'in... | eq { count { filter_eq { all_rows ; native american ; 0.0 % } } ; 4 } = true | select the rows whose native american record fuzzily matches to 0.0 % . 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, 'native american_5': 5, '0.0%_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', 'native american_5': 'native american', '0.0%_6': '0.0 %', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'native american_5': [0], '0.0%_6': [0], '4_7': [2]} | ['country', 'population', 'native american', 'whites', 's mestizo', 'es mulatto', 'blacks', 's zambo', 'asians'] | [['argentina', '40134425', '1.0 %', '85.0 %', '11.1 %', '0.0 %', '0.0 %', '0.0 %', '2.9 %'], ['bolivia', '10907778', '55.0 %', '15.0 %', '28.0 %', '2.0 %', '0.0 %', '0.0 %', '0.0 %'], ['brazil', '192272890', '0.4 %', '53.8 %', '0.0 %', '39.1 %', '6.2 %', '0.0 %', '0.5 %'], ['chile', '17063000', '3.2 %', '52.7 %', '44.1... |
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