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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 record is greater than 0 . for the total records of these rows , most of them are less than 10 .', 'tostr': 'most_less { filter_greater { all_rows ; gold ; 0 } ; total ; 10 } = true'} | 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', '2'], ['9', 'panama', '0', '0', '1', '1'], ['9', 'grenada', '0', '0', '1', '1'], ['9', 'bahamas', '0', '0', '1', '1']] |
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 ; ps500 }'}, 'headphone class'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; headphone model ; ps500 } ; headphone class }', 'tointer': 'select the rows whose headphone model record fuzzily matches to ps500 . take the headphone class record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'headphone model', 'ps1000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose headphone model record fuzzily matches to ps1000 .', 'tostr': 'filter_eq { all_rows ; headphone model ; ps1000 }'}, 'headphone class'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; headphone model ; ps1000 } ; headphone class }', 'tointer': 'select the rows whose headphone model record fuzzily matches to ps1000 . take the headphone class record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; headphone model ; ps500 } ; headphone class } ; hop { filter_eq { all_rows ; headphone model ; ps1000 } ; headphone class } }', 'tointer': '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 .'}, {'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 ; ps500 }'}, 'headphone class'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; headphone model ; ps500 } ; headphone class }', 'tointer': 'select the rows whose headphone model record fuzzily matches to ps500 . take the headphone class record of this row .'}, 'professional'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; headphone model ; ps500 } ; headphone class } ; professional }', 'tointer': 'the headphone class record of the first row is professional .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'headphone model', 'ps1000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose headphone model record fuzzily matches to ps1000 .', 'tostr': 'filter_eq { all_rows ; headphone model ; ps1000 }'}, 'headphone class'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; headphone model ; ps1000 } ; headphone class }', 'tointer': 'select the rows whose headphone model record fuzzily matches to ps1000 . take the headphone class record of this row .'}, 'professional'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; headphone model ; ps1000 } ; headphone class } ; professional }', 'tointer': 'the headphone class record of the second row is professional .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; headphone model ; ps500 } ; headphone class } ; professional } ; eq { hop { filter_eq { all_rows ; headphone model ; ps1000 } ; headphone class } ; professional } }', 'tointer': 'the headphone class record of the first row is professional . the headphone class record of the second row is professional .'}], 'result': True, 'ind': 8, 'tostr': '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 model ; ps1000 } ; headphone class } ; professional } } } = true', 'tointer': '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 of the first row is professional . the headphone class record of the second row is professional .'} | 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 model ; ps1000 } ; headphone class } ; professional } } } = true | 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 of the first row is professional . the headphone class record of the second row is professional . | 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, 'professional_18': 18, 'str_eq_6': 6, 'professional_19': 19} | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', '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_14': 'all_rows', 'headphone model_15': 'headphone model', 'ps1000_16': 'ps1000', 'headphone class_17': 'headphone class', 'and_7': 'and', 'str_eq_5': 'str_eq', 'professional_18': 'professional', 'str_eq_6': 'str_eq', 'professional_19': 'professional'} | {'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], 'and_7': [8], 'str_eq_5': [7], 'professional_18': [5], 'str_eq_6': [7], 'professional_19': [6]} | ['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', 'prestige', '0.1', 'plastic', 'comfort pads', '1 / 4 ( 6.5 mm ) plug', '150'], ['sr225i', 'prestige', '0.05', 'plastic', 'bowls', '1 / 4 ( 6.5 mm ) plug', '200'], ['sr325is', 'prestige', '0.05', 'aluminum alloy / plastic inner sleeve', 'bowls', '1 / 4 ( 6.5 mm ) plug', '295'], ['rs2i', 'reference', '0.05', 'hand - crafted mahogany', 'bowls', '1 / 4 ( 6.5 mm ) plug', '495'], ['rs1i', 'reference', '0.05', 'hand - crafted mahogany', 'bowls', '1 / 4 ( 6.5 mm ) plug', '695'], ['gs1000i', 'statement', '0.05', 'hand - crafted mahogany', 'circumaural bowls', '1 / 4 ( 6.5 mm ) plug', '995'], ['ps500', 'professional', '0.05', 'hand - crafted mahogany / aluminum', 'bowls', '1 / 4 ( 6.5 mm ) plug', '595'], ['ps1000', 'professional', '0.05', 'hand - crafted mahogany / aluminum', 'circumaural bowls', '1 / 4 ( 6.5 mm ) plug', '1695']] |
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 - elected', 'edith nourse rogers ( r ) unopposed'], ['massachusetts 7', 'thomas j lane', 'democratic', '1941', 're - elected', 'thomas j lane ( d ) unopposed'], ['massachusetts 11', "tip o'neill", 'democratic', '1952', 're - elected', "tip o'neill ( d ) 78.2 % charles s bolster ( r ) 21.8 %"]] |
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 )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1980 } ; top team in regular season ( points ) }', 'tointer': 'select the rows whose year record fuzzily matches to 1980 . take the top team in regular season ( points ) record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1982'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1982 .', 'tostr': 'filter_eq { all_rows ; year ; 1982 }'}, 'top team in regular season ( points )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1982 } ; top team in regular season ( points ) }', 'tointer': 'select the rows whose year record fuzzily matches to 1982 . take the top team in regular season ( points ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': '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', 'tointer': '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 .'} | 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_10': 'all_rows', 'year_11': 'year', '1982_12': '1982', 'top team in regular season (points)_13': 'top team in regular season ( points )'} | {'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 ( 137 points )', 'kirk apostolidis', 'sal derosa'], ['1971', 'dallas tornado ( 1 )', 'atlanta chiefs', 'rochester lancers ( 141 points )', 'carlos metidieri', 'ron newman'], ['1972', 'new york cosmos ( 1 )', 'st louis stars', 'new york cosmos ( 77 points )', 'randy horton', 'gordon bradley'], ['1973', 'philadelphia atoms ( 1 )', 'dallas tornado', 'dallas tornado ( 111 points )', 'kyle rote , jr', 'al miller'], ['1974', 'los angeles aztecs ( 1 )', 'miami toros', 'los angeles aztecs ( 110 points )', 'paul child', 'alex perolli'], ['1975', 'tampa bay rowdies ( 1 )', 'portland timbers', 'portland timbers ( 138 points )', 'steve david', 'eddie firmani'], ['1976', 'toronto metros - croatia ( 1 )', 'minnesota kicks', 'tampa bay rowdies ( 154 points )', 'giorgio chinaglia', 'domagoj kapetanović'], ['1977', 'new york cosmos ( 2 )', 'seattle sounders', 'fort lauderdale strikers ( 161 points )', 'steve david', 'eddie firmani'], ['1978', 'new york cosmos ( 3 )', 'tampa bay rowdies', 'new york cosmos ( 212 points )', 'giorgio chinaglia', 'eddie firmani'], ['1979', 'vancouver whitecaps ( 1 )', 'tampa bay rowdies', 'new york cosmos ( 216 points )', 'oscar fabbiani', 'tony waiters'], ['1980', 'new york cosmos ( 4 )', 'fort lauderdale strikers', 'new york cosmos ( 213 points )', 'giorgio chinaglia', 'hennes weisweiler & yasin özdenak'], ['1981', 'chicago sting ( 1 )', 'new york cosmos', 'new york cosmos ( 200 points )', 'giorgio chinaglia', 'willy roy'], ['1982', 'new york cosmos ( 5 )', 'seattle sounders', 'new york cosmos ( 203 points )', 'giorgio chinaglia', 'julio mazzei'], ['1983', 'tulsa roughnecks ( 1 )', 'toronto blizzard', 'new york cosmos ( 194 points )', 'roberto cabañas', 'terry hennessey']] |
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 .'}, 'location attendance', '19000'], 'result': True, 'ind': 1, 'tointer': '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 .', 'tostr': 'most_less { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance ; 19000 } = true'} | 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', 'november 7', 'dallas', 'w 108 - 105 ( ot )', 'carmelo anthony ( 28 )', 'carmelo anthony ( 8 )', 'anthony carter ( 7 )', 'pepsi center 19175', '2 - 3'], ['6', 'november 9', 'memphis', 'w 100 - 90 ( ot )', 'carmelo anthony ( 24 )', 'nenê ( 12 )', 'chauncey billups ( 10 )', 'pepsi center 14359', '3 - 3'], ['7', 'november 11', 'charlotte', 'w 88 - 80 ( ot )', 'carmelo anthony ( 25 )', 'nenê , linas kleiza ( 8 )', 'anthony carter ( 6 )', 'time warner cable arena 10753', '4 - 3'], ['8', 'november 13', 'cleveland', 'l 99 - 110 ( ot )', 'chauncey billups ( 26 )', 'kenyon martin ( 10 )', 'chauncey billups ( 6 )', 'quicken loans arena 20562', '4 - 4'], ['9', 'november 14', 'boston', 'w 94 - 85 ( ot )', 'chauncey billups , carmelo anthony ( 18 )', 'carmelo anthony ( 13 )', 'chauncey billups ( 7 )', 'td banknorth garden 18624', '5 - 4'], ['10', 'november 16', 'minnesota', 'w 90 - 84 ( ot )', 'chauncey billups ( 26 )', 'carmelo anthony ( 12 )', 'chauncey billups ( 5 )', 'pepsi center 16721', '6 - 4'], ['11', 'november 18', 'milwaukee', 'w 114 - 105 ( ot )', 'linas kleiza ( 25 )', 'nenê ( 6 )', 'chauncey billups ( 5 )', 'pepsi center 14413', '7 - 4'], ['12', 'november 19', 'san antonio', 'w 91 - 81 ( ot )', 'chauncey billups ( 22 )', 'carmelo anthony , nenê ( 9 )', 'carmelo anthony ( 7 )', 'at & t center 16559', '8 - 4'], ['13', 'november 21', 'la lakers', 'l 90 - 104 ( ot )', 'j r smith , nenê ( 18 )', 'carmelo anthony ( 10 )', 'chauncey billups ( 9 )', 'staples center 18997', '8 - 5'], ['14', 'november 23', 'chicago', 'w 114 - 101 ( ot )', 'kenyon martin ( 26 )', 'carmelo anthony ( 13 )', 'chauncey billups , carmelo anthony ( 8 )', 'pepsi center 16202', '9 - 5'], ['15', 'november 26', 'la clippers', 'w 106 - 105 ( ot )', 'carmelo anthony ( 30 )', 'carmelo anthony ( 11 )', 'chauncey billups ( 11 )', 'staples center 14934', '10 - 5'], ['16', 'november 27', 'new orleans', 'l 101 - 105 ( ot )', 'j r smith ( 32 )', 'chris andersen ( 8 )', 'anthony carter ( 8 )', 'pepsi center 15563', '10 - 6'], ['17', 'november 29', 'minnesota', 'w 106 - 97 ( ot )', 'chauncey billups ( 27 )', 'carmelo anthony ( 10 )', 'chucky atkins ( 5 )', 'target center 14197', '11 - 6']] |
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', 'biron', '17132', '9 - 5 - 0'], ['november 8', 'philadelphia', '1 - 4', 'new jersey', 'biron', '14948', '9 - 6 - 0'], ['november 10', 'pittsburgh', '2 - 5', 'philadelphia', 'biron', '19859', '10 - 6 - 0'], ['november 12', 'ny islanders', '2 - 3', 'philadelphia', 'biron', '19312', '11 - 6 - 0'], ['november 15', 'ny rangers', '4 - 3', 'philadelphia', 'biron', '19571', '11 - 6 - 1'], ['november 17', 'new jersey', '6 - 2', 'philadelphia', 'biron', '19621', '11 - 7 - 1'], ['november 21', 'philadelphia', '6 - 3', 'carolina', 'biron', '16351', '12 - 7 - 1'], ['november 23', 'washington', '4 - 3', 'philadelphia', 'biron', '19727', '12 - 7 - 2'], ['november 24', 'philadelphia', '4 - 3', 'ottawa', 'niittymaki', '20128', '13 - 7 - 2'], ['november 26', 'boston', '6 - 3', 'philadelphia', 'niittymaki', '19457', '13 - 8 - 2'], ['november 28', 'philadelphia', '3 - 1', 'carolina', 'biron', '15108', '14 - 8 - 2']] |
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 ; money ; 2 } ; 135000 }', 'tointer': 'the 2nd maximum money record of all rows is 135000 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'money', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; money ; 2 }'}, 'player'], 'result': 'fred couples', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; money ; 2 } ; player }'}, 'fred couples'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; money ; 2 } ; player } ; fred couples }', 'tointer': 'the player record of the row with 2nd maximum money record is fred couples .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; money ; 2 } ; 135000 } ; eq { hop { nth_argmax { all_rows ; money ; 2 } ; player } ; fred couples } } = true', 'tointer': 'the 2nd maximum money record of all rows is 135000 . the player record of the row with 2nd maximum money record is fred couples .'} | 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', 'fred couples_15': 'fred couples'} | {'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', '73500'], ['t5', 'chip beck', 'united states', '71 + 70 + 78 + 71 = 290', '+ 2', '51667'], ['t5', 'billy mayfair', 'united states', '70 + 71 + 75 + 74 = 290', '+ 2', '51667'], ['t5', 'loren roberts', 'united states', '73 + 71 + 70 + 76 = 290', '+ 2', '51667'], ['t8', 'mark mcnulty', 'zimbabwe', '74 + 72 + 75 + 71 = 292', '+ 4', '34375'], ['t8', 'don pooley', 'united states', '75 + 74 + 71 + 72 = 292', '+ 4', '34375'], ['t8', 'tim simpson', 'united states', '71 + 73 + 75 + 73 = 292', '+ 4', '34375'], ['t8', 'payne stewart', 'united states', '71 + 72 + 70 + 79 = 292', '+ 4', '34375']] |
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 liga'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; 2004 - 2005 season ; 1 } ; 1st in the liga }', 'tointer': 'the 1st minimum 2004 - 2005 season record of all rows is 1st in the liga .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', '2004 - 2005 season', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; 2004 - 2005 season ; 1 }'}, 'club'], 'result': 'benfica', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; 2004 - 2005 season ; 1 } ; club }'}, 'benfica'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; 2004 - 2005 season ; 1 } ; club } ; benfica }', 'tointer': 'the club record of the row with 1st minimum 2004 - 2005 season record is benfica .'}], 'result': True, 'ind': 5, 'tostr': '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', 'tointer': '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 .'} | 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 season_12': '2004 - 2005 season', '1_13': '1', 'club_14': 'club', 'benfica_15': 'benfica'} | {'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 bessa - século xxi', '6th in the liga'], ['braga', 'jesualdo ferreira', 'braga', 'estádio municipal de braga - axa', '4th in the liga'], ['estrela da amadora', 'toni', 'amadora', 'estádio josé gomes', '3rd in the liga de honra'], ['gil vicente', 'paulo alves', 'barcelos', 'estádio cidade de barcelos', '13th in the liga'], ['união de leiria', 'jorge jesus', 'leiria', 'estádio dr magalhães pessoa', '15th in the liga'], ['penafiel', 'luís castro', 'penafiel', 'estádio municipal 25 de abril', '11th in the liga'], ['marítimo', 'ulisses morais', 'funchal', 'estádio dos barreiros', '7th in the liga'], ['nacional', 'manuel machado', 'funchal', 'estádio da madeira', '12th in the liga'], ['naval 1 degree de maio', 'rogério gonçalves', 'figueira da foz', 'estádio municipal josé bento pessoa', '2nd in the liga de honra'], ['paços de ferreira', 'josé mota', 'paços de ferreira', 'estádio da mata real', '1st in the liga de honra'], ['porto', 'co adriaanse', 'porto', 'estádio do dragão', '2nd in the liga'], ['sporting cp', 'paulo bento', 'lisbon', 'estádio josé alvalade - século xxi', '3rd in the liga'], ['rio ave', 'joão eusébio', 'vila do conde', 'estádio dos arcos', '8th in the liga'], ['vitória de guimarães', 'vítor pontes', 'guimarães', 'estádio d afonso henriques', '5th in the liga'], ['vitória de setúbal', 'hélio sousa', 'setúbal', 'estádio do bonfim', '10th in the liga']] |
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, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; size } ; school } ; switzerland county } = true', 'tointer': 'select the row whose size record of all rows is maximum . the school record of this row is switzerland county .'} | 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', 'aa', '69 ripley'], ['southwestern hanover', 'hanover', 'rebels', '411', 'aa', '39 jefferson'], ['switzerland county', 'vevay', 'pacers', '432', 'aa', '78 switzerland']] |
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, 'tostr': 'eq { hop { argmax { all_rows ; speed } ; rider } ; daniel kneen } = true', 'tointer': 'select the row whose speed record of all rows is maximum . the rider record of this row is daniel kneen .'} | 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', '1:04.56.60'], ['6', 'marie costello', '400cc honda', '103.668 mph', '1:05.30.66'], ['7', 'mike minns', '650cc kawasaki', '103.659 mph', '1:05.31.01'], ['8', 'anthony davies', '399cc yamaha', '103.389 mph', '1:05.41.28'], ['9', 'anthony redmond', '650cc kawasaki', '103.047 mph', '1:05.54.35'], ['10', 'alistair haworth', '400cc yamaha', '103.015 mph', '1:05.55.58']] |
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': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; position } ; competition } ; universiade } = true', 'tointer': 'select the row whose position record of all rows is minimum . the competition record of this row is universiade .'} | 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 , germany', '15th ( q )', '69.30 m'], ['2009', 'world athletics final', 'thessaloniki , greece', '5th', '69.00 m'], ['2010', 'european championships', 'barcelona , spain', '-', 'nm']] |
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': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; forward-center } }', 'tointer': 'select the rows whose position record fuzzily matches to forward-center . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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 }'}, 'player'], 'result': 'keon clark', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; forward-center } ; player }'}, 'keon clark'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; forward-center } ; player } ; keon clark }', 'tointer': 'the player record of this unqiue row is keon clark .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; forward-center } } ; eq { hop { filter_eq { all_rows ; position ; forward-center } ; player } ; keon clark } } = true', 'tointer': '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 .'} | 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 carolina'], ['chris childs', '1', 'united states', 'guard', '2001 - 02', 'boise state'], ['doug christie', '13', 'united states', 'forward', '1996 - 2000', 'pepperdine'], ['keon clark', '7', 'united states', 'forward - center', '2001 - 02', 'unlv'], ['omar cook', '1', 'united states', 'guard', '2005 - 06', "st john 's"], ['tyrone corbin', '23', 'united states', 'guard - forward', '2000 - 01', 'depaul'], ['william cunningham', '54', 'united states', 'center', '1999', 'temple'], ['earl cureton', '35', 'united states', 'forward', '1996 - 97', 'detroit'], ['dell curry', '30', 'united states', 'guard', '1999 - 2002', 'virginia tech']] |
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'], ['79', 'april 10', 'philadelphia 76ers', 'l 78 - 99', 'fleetcenter', '42 - 37'], ['80', 'april 12', 'orlando magic', 'l 86 - 89', 'td waterhouse centre', '42 - 38'], ['81', 'april 13', 'miami heat', 'w 94 - 86', 'american airlines arena', '43 - 38'], ['82', 'april 16', 'detroit pistons', 'w 99 - 92', 'fleetcenter', '44 - 38']] |
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 .'}, 'enrollment'], 'result': '3,847', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; affiliation ; private/catholic } ; enrollment }'}, '3,847'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; affiliation ; private/catholic } ; enrollment } ; 3,847 } = true', 'tointer': 'select the rows whose affiliation record fuzzily matches to private/catholic . the average of the enrollment record of these rows is 3,847 .'} | 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', 'public', '3056', "' roos", 'independent ( uscaa )'], ['mercyhurst college', 'erie , pennsylvania', '1926', 'private / catholic', '3226', 'lakers', 'pennsylvania state athletic conference ( d - ii )'], ['niagara university', 'lewiston , new york', '1856', 'private / catholic', '3746', 'purple eagles', 'metro atlantic athletic conference ( d - i )'], ['rochester institute of technology', 'henrietta , ny', '1829', 'private / non - sectarian', '13861', 'tigers', 'empire 8 ( d - iii )'], ['university of rochester', 'rochester , new york', '1850', 'private / non - sectarian', '9027', 'yellowjackets', 'university athletic association ( d - iii )']] |
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': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; rating } ; episode } ; a modest proposal } = true', 'tointer': 'select the row whose rating record of all rows is maximum . the episode record of this row is a modest proposal .'} | 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', '5'], ['5', 'baby got bank', 'august 17 , 2010', '0.5', '1', '0.3 / 1', '0.802', '5']] |
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 catholic )'], ['brandon cassise', 'g', "6 ' 3", '207', 'sr', "walled lake , mi ( st mary 's preparatory )"], ['shane lawal', 'c', "6 ' 10", '225', 'jr', 'southfield , mi ( lathrup )'], ['ricky bieszki', 'g', "6 ' 2", '186', 'jr', 'shelby township , mi ( notre dame preparatory )'], ['ray goodson', 'g', "6 ' 1", '195', 'fr', 'detroit , mi ( pershing )'], ['johnathon jones', 'g', "5 ' 11", '160', 'so', 'okemos , mi ( okemos )'], ['erik kangas', 'g', "6 ' 3", '210', 'jr', 'dewitt , mi ( dewitt )'], ['john kast', 'g', "6 ' 2", '190', 'fr - r', 'clarkston , mi ( clarkston )'], ['tim williams', 'g', "6 ' 2", '200', 'fr', 'pontiac , mi ( pontiac northern )'], ['keith benson', 'c', "6 ' 11", '210', 'fr - r', 'farmington hills , mi ( country day )'], ['patrick mccloskey', 'f', "6 ' 8", '229', 'sr', 'marshall , mi ( marshall )'], ['dan waterstradt', 'c', "6 ' 10", '240', 'jr', 'dearborn heights , mi ( rutgers )']] |
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', '2 january', 'cardiff city', 'bbc sport'], ['owusu - abeyie', 'ghana', 'spartak moscow', '31 january', '30 june', 'bbc sport', 'south wales echo'], ['chopra', 'eng', 'sunderland', '2 february', '30 june', 'bbc sport', 'south wales echo'], ['konstantopoulos', 'gre', 'coventry city', '9 february', '30 june', 'bbc sport', 'south wales echo'], ['taylor', 'eng', 'aston villa', '13 march', '30 june', 'bbc sport', 'south wales echo']] |
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 ( ceremony ) } ; film title used in nomination }'}, 'the child of man'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; year ( ceremony ) } ; film title used in nomination } ; the child of man } = true', 'tointer': '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 .'} | 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', 'golfa straume zem ledus kalna', 'yevgeni pashkevich', 'not nominated'], ['2013 ( 86th )', 'mother , i love you', 'mammu , es tevi mīlu', 'jānis nords', 'tbd']] |
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 record of all rows is 17.5 .'} | 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', '18', '27.4 km'], ['brown', 'jakarta - tangerang', 'duri to tangerang', '9', '18.9 km'], ['pink', 'tanjung priok line', 'jakarta kota to tanjung priok', '4', '7.9 km ( total ) 1.6 km ( operated )']] |
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 ( cubs )'], ['michael barrett', 'infielder', 'pace academy', 'atlanta , ga', '1st round - 28th pick of 1995 draft ( expos )'], ['chad hermansen', 'infielder', 'green valley high school', 'henderson , nv', '1st round - 10th pick of 1995 draft ( pirates )'], ['jay hood', 'infielder', 'germantown high school', 'germantown , tn', 'attended georgia tech'], ['nate rolison', 'infielder', 'petal high school', 'petal , ms', '2nd round - 36th pick of 1995 draft ( marlins )'], ['shion newton', 'outfielder', 'boys and girls high school', 'brooklyn , ny', '9th round - 6th pick of 1995 draft ( pirates )'], ['reggie taylor', 'outfielder', 'newberry high school', 'newberry , sc', '1st round - 14th pick of 1995 draft ( phillies )'], ['eric valent', 'outfielder', 'canyon high school', 'anaheim , ca', 'attended ucla']] |
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 liga mx } ; club }'}, 'américa'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; number of seasons in liga mx } ; club } ; américa } = true', 'tointer': 'select the row whose number of seasons in liga mx record of all rows is maximum . the club record of this row is américa .'} | 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', '1943 - 44', '89', '11'], ['león', '1944 - 45', '65', '2012 - 13', '2', '5'], ['monterrey', '1945 - 46', '74', '1960 - 61', '72', '4'], ['morelia', '1957 - 58', '61', '1981 - 82', '50', '1'], ['pachuca', '1967 - 68', '40', '1998 - 99', '30', '5'], ['puebla', '1944 - 45', '69', '2007 - 08', '12', '2'], ['querétaro', '1990 - 91', '18', '2009 - 10', '8', '0'], ['santos laguna', '1988 - 89', '42', '1988 - 89', '42', '4'], ['tijuana', '2011 - 12', '4', '2011 - 12', '4', '1'], ['toluca', '1953 - 54', '79', '1953 - 54', '79', '10'], ['uanl', '1974 - 75', '55', '1997 - 98', '32', '3'], ['unam', '1962 - 63', '70', '1962 - 63', '70', '7'], ['veracruz', '1943 - 44', '49', '2013 - 14', '0', '2']] |
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 { all_rows ; date ; 16 } ; december 20 , 1981 } = true', 'tointer': 'the 16th minimum date record of all rows is december 20 , 1981 .'} | 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 redskins', 'w 30 - 17', '51843'], ['6', 'october 11 , 1981', 'dallas cowboys', 'w 45 - 14', '57574'], ['7', 'october 18 , 1981', 'green bay packers', 'w 13 - 3', '50171'], ['8', 'october 25 , 1981', 'los angeles rams', 'w 20 - 17', '59190'], ['9', 'november 1 , 1981', 'pittsburgh steelers', 'w 17 - 14', '52878'], ['10', 'november 8 , 1981', 'atlanta falcons', 'w 17 - 14', '59127'], ['11', 'november 15 , 1981', 'cleveland browns', 'l 12 - 15', '52455'], ['12', 'november 22 , 1981', 'los angeles rams', 'w 33 - 31', '63456'], ['13', 'november 29 , 1981', 'new york giants', 'w 17 - 10', '57186'], ['14', 'december 6 , 1981', 'cincinnati bengals', 'w 21 - 3', '56796'], ['15', 'december 13 , 1981', 'houston oilers', 'w 28 - 6', '55707'], ['16', 'december 20 , 1981', 'new orleans saints', 'w 21 - 17', '43639']] |
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 }'}, 'margin of victory'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 20 nov 2005 } ; margin of victory }', 'tointer': 'select the rows whose date record fuzzily matches to 20 nov 2005 . take the margin of victory record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '10 sep 2006'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 10 sep 2006 .', 'tostr': 'filter_eq { all_rows ; date ; 10 sep 2006 }'}, 'margin of victory'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 10 sep 2006 } ; margin of victory }', 'tointer': 'select the rows whose date record fuzzily matches to 10 sep 2006 . take the margin of victory record of this row .'}], 'result': '2 strokes', 'ind': 4, 'tostr': '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'], 'result': True, 'ind': 5, 'tostr': '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', 'tointer': '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 .'} | 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': 'all_rows', 'date_12': 'date', '10 sep 2006_13': '10 sep 2006', 'margin of victory_14': 'margin of victory', '2 strokes_15': '2 strokes'} | {'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': [5]} | ['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 = 277', '- 11', '6 strokes', 'hiroko yamaguchi toshimi kimura'], ['4', '20 jun 2004', 'apita circle k sunkus ladies', '69 + 69 + 72 = 210', '- 6', '1 stroke', 'yuri fudoh'], ['5', '24 oct 2004', 'masters gc ladies', '69 + 68 + 68 = 205', '- 11', '1 stroke', 'miho koga'], ['6', '21 nov 2004', 'daio paper elleair ladies open', '66 + 67 + 69 = 202', '- 14', '3 strokes', 'chieko amanuma rui kitada'], ['7', '15 may 2005', 'vernal ladies', '69 + 64 + 70 = 203', '- 13', '8 strokes', 'akiko fukushima'], ['8', '22 may 2005', 'chukyo tv bridgestone ladies open', '65 + 74 + 70 = 209', '- 7', 'playoff', 'nikki campbell'], ['9', '21 aug 2005', 'new catapillar mitsubishi ladies', '66 + 75 + 68 = 209', '- 10', '3 strokes', 'mi - jeong jeon hiromi mogi'], ['10', '2 oct 2005', "japan women 's open golf championship", '69 + 69 + 72 + 73 = 283', '- 5', '5 strokes', 'akiko fukushima'], ['12', '20 nov 2005', 'daio paper elleair ladies open', '69 + 70 + 65 = 204', '- 12', '5 strokes', 'shiho oyama woo - soon ko kasumi fujii'], ['13', '10 sep 2006', 'jlpga championship konica minolta cup', '70 + 68 + 74 + 70 = 282', '- 6', '3 strokes', 'hyun - ju shin'], ['14', '24 sep 2006', 'miyagi tv cup dunlop ladies open', '70 + 73 + 71 = 214', '- 2', '3 strokes', 'shiho oyama']] |
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 neville', 'united states', '48.18', '0.294'], ['2', '4', 'chris brown', 'bahamas', '46.68', '0.254'], ['2', '5', 'nery brenes', 'costa rica', '46.85', '0.298'], ['2', '6', 'maksim dyldin', 'russia', '46.92', '0.257'], ['2', '3', 'chris lloyd', 'dominica', '46.92', '0.189'], ['2', '2', 'richard buck', 'united kingdom', '47.60', '0.232'], ['2', '1', 'dewayne barrett', 'jamaica', '48.41', '0.242']] |
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': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; manufacturer ; oldsmobile } }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to oldsmobile . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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 }'}, 'driver'], 'result': 'steve grissom', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; manufacturer ; oldsmobile } ; driver }'}, 'steve grissom'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; manufacturer ; oldsmobile } ; driver } ; steve grissom }', 'tointer': 'the driver record of this unqiue row is steve grissom .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; manufacturer ; oldsmobile } } ; eq { hop { filter_eq { all_rows ; manufacturer ; oldsmobile } ; driver } ; steve grissom } } = true', 'tointer': '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 .'} | 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', 'october 24', 'morgan shepherd', 'buick', '197', '200.349 ( 322.43 )', '1:52:29', '106.396'], ['1988', 'october 22', 'harry gant', 'buick', '197', '200.349 ( 322.43 )', '1:50:09', '109.132'], ['1989', 'october 21', 'harry gant', 'buick', '197', '200.349 ( 322.43 )', '1:47:32', '111.788'], ['1990', 'october 20', 'steve grissom', 'oldsmobile', '197', '200.349 ( 322.43 )', '1:53:31', '105.896'], ['1991', 'october 19', 'ernie irvan', 'chevrolet', '197', '200.349 ( 322.43 )', '1:55:13', '104.333'], ['1992', 'october 24', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:41:30', '118.433'], ['1993', 'october 23', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:42:37', '117.144'], ['1994', 'october 22', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:49:15', '110.032'], ['1995', 'october 21', 'todd bodine', 'chevrolet', '197', '200.349 ( 322.43 )', '2:01:48', '98.694'], ['1996', 'october 19', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:36:38', '124.397'], ['1997', 'october 25', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:59:42', '100.426'], ['1998', 'october 31', 'elliott sadler', 'chevrolet', '197', '200.349 ( 322.43 )', '1:43:31', '116.126'], ['1999', 'october 23', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:45:36', '113.835'], ['2000', 'october 21', 'jeff green', 'chevrolet', '197', '200.349 ( 322.43 )', '1:46:15', '113.138'], ['2001', 'november 3', 'kenny wallace', 'chevrolet', '197', '200.349 ( 322.43 )', '1:36:56', '124.012'], ['2002', 'november 2', 'jamie mcmurray', 'chevrolet', '197', '200.349 ( 322.43 )', '1:41:18', '118.667']] |
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', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; rio de janeiro } }', 'tointer': 'select the rows whose location record fuzzily matches to rio de janeiro . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; rio de janeiro } } ; 2 } = true', 'tointer': 'select the rows whose location record fuzzily matches to rio de janeiro . the number of such rows is 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 %'], ['7', 'porto alegre', '3215545', '11.6 %', '52.7 %'], ['8', 'belo horizonte', '3194715', '7.5 %', '213.0 %'], ['9', 'recife', '3173672', '16.1 %', '63.5 %'], ['10', 'curitiba', '2840349', '13.0 %', '81.2 %'], ['11', 'fortaleza', '2317869', '24.0 %', '77.3 %'], ['12', 'florianópolis', '1382577', '7.8 %', '125.7 %'], ['13', 'manaus', '1368968', '10.3 %', '75.4 %'], ['14', 'belém', '1330965', '13.5 %', '49.3 %'], ['15', 'vitória', '1246222', '6.1 %', '222.5 %']] |
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': 'select the rows whose broadcast record fuzzily matches to espn . for the attendance records of these rows , most of them are less than 100000 .', 'tostr': 'most_less { filter_eq { all_rows ; broadcast ; espn } ; attendance ; 100000 } = true'} | 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 florida', 'ben hill griffin stadium gainesville , fl', 'sec network', 'w 38 - 14', '90612'], ['september 11', '7:00 pm', '19 lsu', 'vanderbilt', 'vanderbilt stadium nashville , tn', 'espnu', 'lsu 27 - 3', '36940'], ['september 11', '7:00 pm', '19 penn state', '1 alabama', 'bryant - denny stadium tuscaloosa , al', 'espn', 'w 24 - 3', '101821'], ['september 11', '7:00 pm', 'louisiana - monroe', '14 arkansas', 'war memorial stadium little rock , ar', 'fsn', 'w 31 - 7', '55705'], ['september 11', '7:00 pm', '7 oregon', 'tennessee', 'neyland stadium knoxville , tn', 'espn2', 'l 48 - 13', '102035'], ['september 11', '7:30 pm', 'western kentucky', 'kentucky', 'commonwealth stadium lexington , ky', 'css', 'w 63 - 28', '66584']] |
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, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; jason gore } ; to par }', 'tointer': 'select the rows whose player record fuzzily matches to jason gore . take the to par record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'mark hensby'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to mark hensby .', 'tostr': 'filter_eq { all_rows ; player ; mark hensby }'}, 'to par'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; mark hensby } ; to par }', 'tointer': 'select the rows whose player record fuzzily matches to mark hensby . take the to par record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; jason gore } ; to par } ; hop { filter_eq { all_rows ; player ; mark hensby } ; to par } } = true', 'tointer': '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 .'} | 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 hensby_12': 'mark hensby', 'to par_13': 'to par'} | {'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', 'michael campbell', 'new zealand', '71 + 69 = 140', 'e'], ['t6', 'sergio garcía', 'spain', '71 + 69 = 140', 'e'], ['t6', 'vijay singh', 'fiji', '70 + 70 = 140', 'e'], ['t6', 'lee westwood', 'england', '68 + 72 = 140', 'e'], ['t10', 'stephen allan', 'australia', '72 - 69 - 141', '+ 1'], ['t10', 'keiichiro fukabori', 'japan', '74 + 67 = 141', '+ 1'], ['t10', 'jim furyk', 'united states', '71 + 70 = 141', '+ 1'], ['t10', 'brandt jobe', 'united states', '68 + 73 = 141', '+ 1'], ['t10', 'rocco mediate', 'united states', '67 + 74 = 141', '+ 1'], ['t10', 'adam scott', 'australia', '70 + 71 = 141', '+ 1'], ['t10', 'tiger woods', 'united states', '70 + 71 = 141', '+ 1']] |
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 }', 'tointer': 'select the rows whose international tourist arrivals ( 2012 ) record is greater than 40 million .'}, 'change ( 2011 to 2012 )', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_greater { all_rows ; international tourist arrivals ( 2012 ) ; 40 million } ; change ( 2011 to 2012 ) ; 1 }'}, 'country'], 'result': 'spain', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_greater { all_rows ; international tourist arrivals ( 2012 ) ; 40 million } ; change ( 2011 to 2012 ) ; 1 } ; country }'}, 'spain'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_greater { all_rows ; international tourist arrivals ( 2012 ) ; 40 million } ; change ( 2011 to 2012 ) ; 1 } ; country } ; spain } = true', 'tointer': '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 .'} | 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 to 2012 )', '1_9': '1', 'country_10': 'country', 'spain_11': 'spain'} | {'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', '28.4 million', '+ 7.3 %', '+ 5.5 %'], ['6', 'united kingdom', '29.3 million', '29.3 million', '- 0.1 %', '+ 3.6 %'], ['7', 'russia', '25.7 million', '22.7 million', '+ 13.4 %', '+ 11.9 %'], ['8', 'austria', '24.1 million', '23.0 million', '+ 4.6 %', '+ 4.9 %'], ['9', 'ukraine', '23.0 million', '21.4 million', '+ 7.5 %', '+ 1.0 %']] |
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', '3', '0', '1', 'ho - pin tung ( 2009 )', 'ho - pin tung'], ['czech republic', '1', '0', '1', 'filip salaquarda ( 2011 )', 'filip salaquarda'], ['denmark', '1', '0', '0', 'kasper andersen ( 2008 )', 'kasper andersen ( 2009 )'], ['france', '7', '0', '1', 'tristan gommendy , nelson philippe ( 2008 )', 'tristan gommendy'], ['germany', '1', '0', '0', 'max wissel ( 2008 )', 'max wissel ( 2010 )'], ['greece', '1', '0', '0', 'stamatis katsimis ( 2008 )', 'stamatis katsimis ( 2008 )'], ['india', '1', '0', '0', 'narain karthikeyan ( 2010 )', 'narain karthikeyan ( 2010 )'], ['netherlands', '6', '0', '2', 'yelmer buurman , robert doornbos ( 2008 )', 'yelmer buurman , robert doornbos'], ['new zealand', '2', '0', '1', 'chris van der drift ( 2010 )', 'earl bamber'], ['portugal', '2', '0', '0', 'pedro petiz ( 2009 )', 'álvaro parente ( 2010 )'], ['switzerland', '1', '0', '1', 'neel jani ( 2010 )', 'neel jani'], ['united arab emirates', '1', '0', '0', 'andreas zuber ( 2008 )', 'andreas zuber ( 2008 )']] |
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': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; competition ; 1 } ; goal } ; 1 } = true', 'tointer': 'select the row whose competition record of all rows is 1st minimum . the goal record of this row is 1 .'} | 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', '2006 fifa world cup qualification'], ['4', 'november 17 , 2004', 'estadio tecnológico , monterrey , mexico', '8 - 0', '8 - 0', '2006 fifa world cup qualification'], ['5', 'june 8 , 2005', 'estadio universitario , san nicolás , mexico', '2 - 0', '2 - 0', '2006 fifa world cup qualification'], ['6', 'september 7 , 2005', 'estadio azteca , mexico city , mexico', '1 - 0', '5 - 0', '2006 fifa world cup qualification'], ['7', 'october 26 , 2005', 'estadio jalisco , guadalajara , mexico', '3 - 1', '3 - 1', 'friendly'], ['8', 'january 26 , 2006', 'monster park , san francisco , united states', '2 - 1', '2 - 1', 'friendly']] |
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 { filter_eq { all_rows ; hometown ; brampton , on } } = true', 'tointer': 'select the rows whose hometown record fuzzily matches to brampton , on . there is only one such row in the table .'} | 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', 'has not yet declared for the nba draft'], ['anthony bennett', "6 ' 8", 'findlay prep', 'brampton , on', 'unlv', '1st round - 1st pick of 2013 draft ( cavaliers )'], ['perry ellis', "6 ' 8", 'wichita heights high school', 'wichita , ks', 'kansas', 'has not yet declared for the nba draft']] |
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', 'downhill', '18th'], ['2012', '3 feb 2012', 'chamonix , france', 'downhill', '12th'], ['2012', '4 feb 2012', 'chamonix , france', 'downhill', '12th']] |
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'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; position ; ol } ; pick }'}, 'cfl team'], 'result': 'montreal alouettes', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; position ; ol } ; pick } ; cfl team }'}, 'montreal alouettes'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; position ; ol } ; pick } ; cfl team } ; montreal alouettes } = true', 'tointer': '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 .'} | 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 leblanc', 'sb', 'mcgill'], ['41', 'hamilton tiger - cats', 'iain fleming', 'sb', "queen 's"], ['42', 'montreal alouettes', 'curt hundeby', 'ol', 'saskatchewan'], ['43', 'bc lions', 'nuvraj bassi', 'dt', 'oregon'], ['44', 'toronto argonauts', 'bryan crawford', 'rb', "queen 's"]] |
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': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; greg merson } ; wsop cashes }', 'tointer': 'select the rows whose name record fuzzily matches to greg merson . take the wsop cashes record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'michael esposito'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to michael esposito .', 'tostr': 'filter_eq { all_rows ; name ; michael esposito }'}, 'wsop cashes'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; michael esposito } ; wsop cashes }', 'tointer': 'select the rows whose name record fuzzily matches to michael esposito . take the wsop cashes record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; greg merson } ; wsop cashes } ; hop { filter_eq { all_rows ; name ; michael esposito } ; wsop cashes } } = true', 'tointer': '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 .'} | 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', 'michael esposito_12': 'michael esposito', 'wsop cashes_13': 'wsop cashes'} | {'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', '9th', '754798'], ['michael esposito', '16260000', '0', '3', '27311', '7th', '1257790'], ['robert salaburu', '15155000', '0', '0', '0', '8th', '971252'], ['jacob balsiger', '13115000', '0', '1', '3531', '3rd', '3797558']] |
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 ; primary conference when joining the msfa ; whac }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; primary conference when joining the msfa ; whac } }', 'tointer': 'select the rows whose primary conference when joining the msfa record fuzzily matches to whac . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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 ; primary conference when joining the msfa ; whac }'}, 'institution'], 'result': 'trine university', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; primary conference when joining the msfa ; whac } ; institution }'}, 'trine university'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; primary conference when joining the msfa ; whac } ; institution } ; trine university }', 'tointer': 'the institution record of this unqiue row is trine university .'}], 'result': True, 'ind': 4, 'tostr': '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', 'tointer': '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 .'} | 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_10': '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 ' ( pac ) ( ncaa division iii )"], ['iowa wesleyan college', 'mount pleasant , iowa', '1842', 'private', '850', '1996 - 97', '2011 - 12', 'tigers', 'mcc', 'ncaa d - iii independent'], ['lindenwood university', 'st charles , missouri', '1827', 'private', '17351', '1994 - 95', '1995 - 96', 'lions', 'american midwest', 'miaa ( ncaa division ii )'], ['malone university', 'canton , ohio', '1892', 'private', '2559', '1994 - 95', '2010 - 11', 'pioneers', 'american mideast', 'gliac ( ncaa division ii )'], ['mckendree university', 'lebanon , illinois', '1828', 'private', '3220', '1998 - 99', '2010 - 11', 'bearcats', 'american midwest', 'glvc ( ncaa division ii )'], ['ohio dominican university', 'columbus , ohio', '1911', 'private', '3052', '2004 - 05', '2008 - 09', 'panthers', 'american mideast', 'gliac ( ncaa division ii )'], ['quincy university', 'quincy , illinois', '1860', 'private', '1169', '2003 - 04', '2011 - 12', 'hawks', 'glvc ( ncaa division ii )', 'glvc ( ncaa division ii )'], ['tiffin university', 'tiffin , ohio', '1888', 'private', '6816', '1994 - 95', '2001 - 02', 'dragons', 'american mideast', 'gliac ( ncaa division ii )'], ['trine university', 'angola , indiana', '1884', 'private', '1779', '1996 - 97', '2002 - 03', 'thunder', 'whac', 'miaa ( ncaa division iii )'], ['urbana university', 'urbana , ohio', '1850', 'private', '1505', '1994 - 95', '2007 - 08', 'blue knights', 'american mideast', 'g - mac ( ncaa division ii )'], ['walsh university', 'north canton , ohio', '1960', 'private', '2500', '1996 - 97', '2010 - 11', 'cavaliers', 'american mideast', 'gliac ( ncaa division ii )']] |
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 , 1982 , 1983', '148', '+ 4']] |
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': 'only { filter_eq { all_rows ; nationality ; usa } }', 'tointer': 'select the rows whose nationality record fuzzily matches to usa . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', '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 }'}, 'pick'], 'result': '12', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; usa } ; pick }'}, '12'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; usa } ; pick } ; 12 }', 'tointer': 'the pick record of this unqiue row is 12 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; usa } } ; eq { hop { filter_eq { all_rows ; nationality ; usa } ; pick } ; 12 } } = true', 'tointer': '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 .'} | 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'], ['1969', '3', '29', "don o'donoghue", 'canada'], ['1969', '4', '41', 'pierre farmer', 'canada'], ['1969', '5', '53', 'warren harrison', 'canada'], ['1969', '6', '65', 'neil nicholson', 'canada'], ['1969', '7', '76', 'pete vipond', 'canada'], ['1970', '1', '10', 'chris oddleifson', 'canada'], ['1970', '2', '19', 'pete laframboise', 'canada'], ['1970', '3', '33', 'randy rota', '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 corporation', '5', '1600000000', 'crown , hamech', 'new bremen , ohio', 'usa'], ['5', 'nacco industries , inc', '4', '1500000000', 'hyster , yale', 'cleveland , ohio', 'usa'], ['6', 'mitsubishi caterpillar forklift america inc', '6', '920000000', 'mitsubishi , cat', 'sagamihara', 'japan'], ['7', 'komatsu utility co', '8', '750000000', 'komatsu , tusk', 'tokyo', 'japan'], ['8', 'anhui forklift group', '9', '668000000', 'heli', 'hefei , anhui', 'china'], ['9', 'nissan forklift corp', '7', '624000000', 'nissan , barrett , atlet', 'tokyo', 'japan'], ['10', 'tcm corp', '10', '593000000', 'tcm', 'osaka', 'japan'], ['11', 'nippon yusoki co', '11', '559000000', 'not available in n a', 'nagaokakyo , kyoto', 'japan'], ['12', 'doosan infracore', '15', '418000000', 'doosan', 'seoul', 'south korea'], ['13', 'clark material handling company', '12', '405000000', 'clark', 'seoul', 'south korea'], ['14', 'manitou', '13', '296000000', 'manitou', 'ancenis', 'france'], ['15', 'zhejiang hangcha engineering machinery co', '14', '251000000', 'hc', 'hangzhou', 'china'], ['16', 'hyundai heavy industries', '16', '237000000', 'hyundai', 'ulsan', 'south korea'], ['17', 'tailift', '18', '100000000', 'tailift , worldlift', 'taichung', 'taiwan'], ['18', 'combilift', '19', '98000000', 'combilift', 'monaghan', 'ireland'], ['19', 'hytsu', 'n / a', '86000000', 'hytsu', 'shanghai', 'china']] |
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 { all_rows ; laps ; 96 } ; points }'}, '20.5'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; laps ; 96 } ; points } ; 20.5 } = true', 'tointer': 'select the rows whose laps record is equal to 96 . the average of the points record of these rows is 20.5 .'} | 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', '+ 28.1 secs', '14', '22'], ['oriol servia', 'forsythe racing', '96', '+ 30.0 secs', '13', '19'], ['bruno junqueira', 'dale coyne racing', '96', '+ 30.7 secs', '6', '17'], ['dan clarke', 'minardi team usa', '96', '+ 35.3 secs', '10', '15'], ['neel jani ( r )', 'pkv racing', '96', '+ 37.8 secs', '5', '13'], ['jan heylen', 'conquest racing', '96', '+ 58.7 secs', '12', '11'], ['robert doornbos ( r )', 'minardi team usa', '95', '+ 1 lap', '11', '10'], ['ryan dalziel', 'pacific coast motorsports', '95', '+ 1 lap', '8', '9'], ['alex figge ( r )', 'pacific coast motorsports', '95', '+ 1 lap', '16', '8'], ['alex tagliani', 'rsports', '69', 'contact', '9', '7'], ['will power', 'team australia', '69', 'mechanical', '1', '7'], ['katherine legge', 'dale coyne racing', '36', 'mechanical', '15', '5'], ['mario dominguez', 'pkv racing', '32', 'mechanical', '17', '4']] |
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 } ; home team }'}, 'fitzroy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; home team score ; 2 } ; home team } ; fitzroy } = true', 'tointer': 'select the row whose home team score record of all rows is 2nd minimum . the home team record of this row is fitzroy .'} | 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'], ['south melbourne', '16.13 ( 109 )', 'st kilda', '7.11 ( 53 )', 'lake oval', '29500', '15 june 1959'], ['melbourne', '19.15 ( 129 )', 'essendon', '8.8 ( 56 )', 'mcg', '52880', '15 june 1959'], ['geelong', '11.13 ( 79 )', 'carlton', '12.16 ( 88 )', 'kardinia park', '11533', '15 june 1959']] |
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 ( millions ) } ; title }'}, 'bea stays in the picture'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( millions ) } ; title } ; bea stays in the picture } = true', 'tointer': '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 .'} | 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 ( story ) carl faruolo ( storyboards )', 'october 22 , 2010', '2.6'], ['9', 'queen bea', 'ch greenblatt', 'tim mckeon ( story ) derek evanick ( storyboards )', 'october 29 , 2010', 'n / a'], ['10', 'fail fish', 'willam reiss', 'tim mckeon ( story ) ian wasseluk ( storyboards )', 'november 5 , 2010', 'n / a'], ['12', 'baldwin the super fish', 'william reiss', 'tim mckeon ( story ) carl faruolo ( storyboards )', 'december 3 , 2010', '2.8'], ['13', 'dances with wolf fish', 'william reiss', 'jackie buscarino ( story ) niki yang ( storyboards )', 'december 10 , 2010', '2.5'], ['14', 'the tale of sir oscar fish', 'william reiss', 'tim mckeon ( story ) ian wasseluk ( storyboards )', 'december 17 , 2010', 'n / a'], ['18', 'fishing for compliments : the albert glass story', 'ch greenblatt', 'justin roiland ( story ) carl faruolo ( storyboards )', 'january 29 , 2011', 'n / a'], ['19', 'big fish', 'ch greenblatt', 'ryan ridley ( story ) derek evanick ( storyboards )', 'february 4 , 2011', 'n / a'], ['23', 'flying fish', 'ch greenblatt & william reiss', 'tim mckeon ( story ) carl faruolo ( storyboards )', 'march 4 , 2011', '2.9'], ['24', 'two clams in love', 'ch greenblatt & william reiss', 'tim mckeon ( story ) alex hirsch ( storyboards )', 'march 11 , 2011', '3.0'], ['25', 'peopleing', 'maxwell atoms', 'justin roiland ( story ) maxwell atoms ( storyboards )', 'april 1 , 2011', '2.4'], ['29', 'riding in cars with fish', 'ch greenblatt & william reiss', 'tim mckeon ( story ) derek evanick ( storyboards )', 'june 18 , 2011', 'n / a'], ['30', "milo 's big idea", 'ch greenblatt & william reiss', 'jackie buscarino ( story ) neil graf ( storyboards )', 'june 18 , 2011', 'n / a'], ['32', 'good morning , freshwater', 'ch greenblatt & william reiss', 'tim mckeon ( story ) diana lafyatis ( storyboards )', 'july 2 , 2011', 'n / a'], ['35', 'run , oscar , run', 'ch greenblatt & william reiss', 'jessica gao ( story ) blake lemons ( storyboards )', 'august 12 , 2011', '3.5'], ['36', 'good times at pupu goodtimes', 'ch greenblatt & william reiss', 'tim mckeon ( story ) derek evanick ( storyboards )', 'august 19 , 2011', '3.3']] |
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 }'}, 'cumberland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; median family income } ; county } ; cumberland } = true', 'tointer': 'select the row whose median family income record of all rows is maximum . the county record of this row is cumberland .'} | 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', '26876', '47533', '60092', '54418', '24221'], ['maine', '25385', '46933', '58185', '1328361', '557219'], ['knox', '25291', '45264', '55830', '39736', '17258'], ['kennebec', '24656', '45973', '56853', '122151', '51128'], ['penobscot', '22977', '42658', '54271', '153923', '62966'], ['androscoggin', '22752', '44470', '55045', '107702', '44315'], ['waldo', '22213', '41312', '50222', '38786', '16431'], ['oxford', '21254', '39748', '48000', '57833', '24300'], ['franklin', '20838', '39831', '48634', '30768', '13000'], ['somerset', '20709', '36647', '47177', '52228', '21927'], ['aroostook', '20251', '36574', '47114', '71870', '30961'], ['piscataquis', '19870', '34016', '43821', '17535', '7825'], ['washington', '19401', '34859', '43612', '32856', '14302']] |
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 30'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; location attendance } ; date } ; april 30 } = true', 'tointer': 'select the row whose location attendance record of all rows is maximum . the date record of this row is april 30 .'} | 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 center 23067', '2 - 2'], ['5', 'april 28', 'boston', 'l 104 - 106 ( ot )', 'td banknorth garden 18624', '2 - 3'], ['6', 'april 30', 'boston', 'w 128 - 127 ( 3ot )', 'united center 23430', '3 - 3'], ['7', 'may 2', 'boston', 'l 99 - 109 ( ot )', 'td banknorth garden 18624', '3 - 4']] |
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, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; arnhem } ; date ( from ) }', 'tointer': 'select the rows whose location record fuzzily matches to arnhem . take the date ( from ) record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'nijmegen'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to nijmegen .', 'tostr': 'filter_eq { all_rows ; location ; nijmegen }'}, 'date ( from )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; location ; nijmegen } ; date ( from ) }', 'tointer': 'select the rows whose location record fuzzily matches to nijmegen . take the date ( from ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; location ; arnhem } ; date ( from ) } ; hop { filter_eq { all_rows ; location ; nijmegen } ; date ( from ) } } = true', 'tointer': '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 .'} | 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', 'nijmegen_12': 'nijmegen', 'date (from)_13': 'date ( from )'} | {'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 ( 1880 - 1911 ) geta ( 1911 - 1944 )', 'arnhem', 'electric', '21 may 1911', '17 september 1944'], ['hsm ( 1883 - 1910 ) gt ( 1915 - 1922 )', 'groenlo', 'steam', '29 may 1883', '31 december 1910'], ['hsm ( 1883 - 1910 ) gt ( 1915 - 1922 )', 'groenlo', 'petrol ( gasoline )', '6 august 1915', 'oct 1922'], ['hsm ( 1883 - 1910 ) gt ( 1915 - 1922 )', 'groenlo', 'horse', '1917', '1919'], ['ntm ( 1889 - 1912 ) m & w ( 1912 - 1921 ) gtn ( 1911 - 1955 )', 'nijmegen', 'horse', '1889', '1911'], ['ntm ( 1889 - 1912 ) m & w ( 1912 - 1921 ) gtn ( 1911 - 1955 )', 'nijmegen', 'steam', '30 june 1889', '31 december 1921'], ['ntm ( 1889 - 1912 ) m & w ( 1912 - 1921 ) gtn ( 1911 - 1955 )', 'nijmegen', 'electric', '4 june 1911', '20 november 1955'], ['gtz', 'zaltbommel', 'horse', '14 march 1910', '31 august 1923'], ['ztm', 'zutphen', 'horse', '16 may 1889', '29 january 1904']] |
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 1920 .'} | 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', '43', '20 / 1', '4', '1', '2', '2:10.11', 'fergal lynch', 'michael stoute'], ['derby', '12', 'epsom', '1', '852', '6 / 1', '20', '1', '1', '2:33.35', 'kieren fallon', 'michael stoute'], ['king george vi & queen elizabeth stakes', '12', 'ascot', '1', '435', '7 / 2', '12', '3', '5.5', '2:33.26', 'kieren fallon', 'michael stoute'], ['prix niel', '12', 'longchamp', '2', '40', '11 / 4', '7', '3', '4', '2:27.60', 'kieren fallon', 'michael stoute'], ["prix de l'arc de triomphe", '12', 'longchamp', '1', '593', '11 / 1', '13', '11', '45', '2:32.30', 'kieren fallon', 'michael stoute']] |
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 to euro 2012 qualifying .'}, 'spectators', '40000'], 'result': None, 'ind': 1, 'tointer': '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 .', 'tostr': 'filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 } }', 'tointer': '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 .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', '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 to euro 2012 qualifying .'}, 'spectators', '40000'], 'result': None, 'ind': 1, 'tointer': '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 .', 'tostr': 'filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 }'}, 'date'], 'result': '11 october 2011', 'ind': 3, 'tostr': 'hop { filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 } ; date }'}, '11 october 2011'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 } ; date } ; 11 october 2011 }', 'tointer': 'the date record of this unqiue row is 11 october 2011 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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 to euro 2012 qualifying .'}, 'spectators', '40000'], 'result': None, 'ind': 1, 'tointer': '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 .', 'tostr': 'filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 }'}, 'team 2'], 'result': 'azerbaijan', 'ind': 5, 'tostr': 'hop { filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 } ; team 2 }'}, 'azerbaijan'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_less { filter_eq { all_rows ; round ; euro 2012 qualifying } ; spectators ; 40000 } ; team 2 } ; azerbaijan }', 'tointer': 'the team 2 record of this unqiue row is azerbaijan .'}], 'result': True, 'ind': 7, 'tostr': '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 qualifying } ; spectators ; 40000 } ; team 2 } ; azerbaijan } }', 'tointer': 'the date record of this unqiue row is 11 october 2011 . the team 2 record of this unqiue row is azerbaijan .'}], 'result': True, 'ind': 8, 'tostr': '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 qualifying } ; spectators ; 40000 } ; team 2 } ; azerbaijan } } } = true', 'tointer': '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 .'} | 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 qualifying } ; spectators ; 40000 } ; team 2 } ; azerbaijan } } } = true | 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, 'azerbaijan_18': 18} | {'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_3': 'str_hop', 'date_15': 'date', '11 october 2011_16': '11 october 2011', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'team 2_17': 'team 2', 'azerbaijan_18': 'azerbaijan'} | {'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_hop_5': [6], 'team 2_17': [5], 'azerbaijan_18': [6]} | ['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', 'azerbaijan', 'euro 2012 qualifying', '32174'], ['11 november 2011', '20.05', 'turkey', '0 - 3', 'croatia', 'euro 2012 qualifying', '42863'], ['14 november 2012', '20.30', 'turkey', '1 - 1', 'denmark', 'friendly', '30000']] |
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', '44'], ['6', 'newcastle town', '34', '10', '9', '53', '37', '+ 16', '40'], ['7', 'great harwood town', '34', '6', '12', '52', '40', '+ 12', '38'], ['8', 'maghull', '34', '13', '9', '46', '44', '+ 2', '35'], ['9', 'bacup borough', '34', '12', '11', '55', '57', '2', '34'], ['10', 'daisy hill', '34', '6', '16', '36', '49', '13', '30'], ['11', 'atherton collieries', '34', '11', '14', '52', '58', '6', '29'], ['12', 'padiham', '34', '10', '15', '39', '57', '18', '28'], ['13', 'glossop', '34', '7', '17', '42', '60', '18', '27'], ['14', 'cheadle town', '34', '7', '17', '46', '67', '21', '27'], ['15', 'oldham town', '34', '11', '17', '46', '66', '20', '23'], ['16', 'blackpool mechanics', '34', '5', '20', '46', '72', '26', '23'], ['17', 'ashton town', '34', '11', '19', '31', '68', '37', '19'], ['18', 'newton', '34', '5', '28', '23', '111', '88', '7']] |
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 owned by local tv'], ['fort collins , colorado', 'kfct ( satellite of kdvr )', '22 ( 21 )', '1995 - 2008', 'fox affiliate owned by local tv'], ['atlanta', 'watl - tv', '36 ( 25 )', '1993 - 1995', 'mynetworktv affiliate owned by gannett company'], ['boston', 'wcvb - tv 1', '5 ( 20 )', '1986', 'abc affiliate owned by hearst television'], ['kansas city , missouri', 'wdaf - tv + +', '4 ( 34 )', '1997 - 2008', 'fox affiliate owned by local tv'], ['saint louis', 'ktvi + +', '2 ( 43 )', '1997 - 2008', 'fox affiliate owned by local tv'], ['high point - greensboro - winston - salem', 'wghp', '8 ( 35 )', '1995 - 2008', 'fox affiliate owned by local tv'], ['cleveland - akron', 'wjw - tv + +', '8 ( 8 )', '1997 - 2008', 'fox affiliate owned by local tv'], ['portland , oregon', 'kptv ¤ ¤', '12 ( 12 )', '2001 - 2002', 'fox affiliate owned by meredith corporation'], ['dallas - fort worth', 'kdaf', '33 ( 32 )', '1986 - 1995', 'cw affiliate owned by tribune broadcasting'], ['san antonio', 'kmol - tv ¤ ¤ ( now woai - tv )', '4 ( 48 )', '2001', 'nbc affiliate owned by sinclair broadcast group'], ['salt lake city', 'kstu', '13 ( 28 )', '1990 - 2008', 'fox affiliate owned by local tv'], ['salt lake city', 'ktvx ¤ ¤', '4 ( 40 )', '2001', 'abc affiliate owned by nexstar broadcasting group']] |
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, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponents ; walsall } ; date }', 'tointer': 'select the rows whose opponents record fuzzily matches to walsall . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents', 'sheffield wednesday'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponents record fuzzily matches to sheffield wednesday .', 'tostr': 'filter_eq { all_rows ; opponents ; sheffield wednesday }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponents ; sheffield wednesday } ; date }', 'tointer': 'select the rows whose opponents record fuzzily matches to sheffield wednesday . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponents ; walsall } ; date } ; hop { filter_eq { all_rows ; opponents ; sheffield wednesday } ; date } } = true', 'tointer': '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 .'} | 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', 'sheffield wednesday_12': 'sheffield wednesday', 'date_13': 'date'} | {'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', 'sheffield wednesday', 'a', 'w', '3 - 0']] |
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', '12', '28 / 07 / 1990', 'vélez sársfield , buenos aires', 'first test'], ['argentina', '15', '04 / 08 / 1990', 'vélez sársfield , buenos aires', 'second test'], ['argentina', '0', '03 / 11 / 1990', 'twickenham , london', 'test match']] |
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, 'tostr': 'count { filter_eq { all_rows ; result ; re-elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re-elected } } ; 5 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . the number of such rows is 5 .'} | 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 ( d ) unopposed'], ['louisiana 5', 'otto passman', 'democratic', '1946', 're - elected', 'otto passman ( d ) unopposed'], ['louisiana 7', 't ashton thompson', 'democratic', '1952', 're - elected', 't ashton thompson ( d ) unopposed']] |
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, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; round } ; name } ; sean weatherspoon } = true', 'tointer': 'select the row whose round record of all rows is minimum . the name record of this row is sean weatherspoon .'} | 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', '165', 'kerry meier', 'wide receiver', 'kansas'], ['6', '2', '171', 'shann schillinger', 'safety', 'montana']] |
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': 1, 'tostr': 'only { filter_eq { all_rows ; engine ; maserati straight - 6 } } = true', 'tointer': 'select the rows whose engine record fuzzily matches to maserati straight - 6 . there is only one such row in the table .'} | 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', 'talbot straight - 6', '0'], ['1952', 'escuderia bandeirantes', 'maserati a6 gcm', 'maserati straight - 6', '0']] |
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 all rows is 6012 .'} | 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', '-', 'a']] |
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'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose played record is less than 114 . among these rows , select the rows whose average record is greater than 1.0 .', 'tostr': 'filter_greater { filter_less { all_rows ; played ; 114 } ; average ; 1.0 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_less { all_rows ; played ; 114 } ; average ; 1.0 } }', 'tointer': '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 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose played record is less than 114 . among these rows , select the rows whose average record is greater than 1.0 .', 'tostr': 'filter_greater { filter_less { all_rows ; played ; 114 } ; average ; 1.0 }'}, 'team'], 'result': 'huracán', 'ind': 3, 'tostr': 'hop { filter_greater { filter_less { all_rows ; played ; 114 } ; average ; 1.0 } ; team }'}, 'huracán'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_less { all_rows ; played ; 114 } ; average ; 1.0 } ; team } ; huracán }', 'tointer': 'the team record of this unqiue row is huracán .'}], 'result': True, 'ind': 5, 'tostr': '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', 'tointer': '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 .'} | 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', '120', '114', '33', '42', '45'], ['huracán', '1.053', '40', '38', 'n / a', 'n / a', '40'], ["newell 's old boys", '1.044', '119', '114', '35', '36', '48'], ['rosario central', '1.035', '118', '114', '36', '43', '39'], ['argentinos juniors', '1.018', '116', '114', '42', '38', '36'], ['estudiantes de la plata', '1.009', '115', '114', '42', '34', '39'], ['talleres de córdoba', '0.956', '109', '114', '44', '36', '29'], ['gimnasia de la plata', '0.947', '108', '114', '36', '39', '33'], ['ferro carril oeste', '0.939', '107', '114', '30', '39', '38'], ['deportivo mandiyú', '0.939', '107', '114', '33', '36', '38'], ['deportivo español', '0.921', '105', '114', '46', '31', '28'], ['platense', '0.912', '104', '114', '33', '36', '35'], ['unión de santa fe', '0.882', '67', '76', 'n / a', '36', '31'], ['chaco for ever', '0.789', '60', '76', 'n / a', '32', '28']] |
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 champions'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; purse } ; tournament } ; peter jackson champions } = true', 'tointer': 'select the row whose purse record of all rows is maximum . the tournament record of this row is peter jackson champions .'} | 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 ( - 6 )', '30000'], ['jun 28', 'marlboro classic', 'massachusetts', '150000', 'bob goalby ( 1 )', '208 ( - 2 )', '25000'], ['jul 12', 'us senior open', 'michigan', '149000', 'arnold palmer ( 2 )', '289 ( 9 )', '26000'], ['oct 18', 'suntree seniors classic', 'florida', '125000', 'miller barber ( 2 )', '204 ( - 12 )', '20000']] |
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': 1, 'tostr': 'count { filter_eq { all_rows ; opponent team ; canada } }', 'tointer': 'select the rows whose opponent team record fuzzily matches to canada . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent team ; canada } } ; 2 } = true', 'tointer': 'select the rows whose opponent team record fuzzily matches to canada . the number of such rows is 2 .'} | 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 , 7 - 5'], ['winner', '2011', 'world group ii', 'canada', 'hard ( i )', 'rebecca marino', '7 - 6 ( 7 - 3 ) , 6 - 3'], ['loser', '2011', 'world group playoffs', 'slovakia', 'clay ( i )', 'dominika cibulková', '6 - 4 , 3 - 6 , 1 - 6'], ['loser', '2012', 'world group', 'belgium', 'hard ( i )', 'yanina wickmayer', '4 - 6 , 4 - 6'], ['winner', '2012', 'world group', 'belgium', 'hard ( i )', 'kirsten flipkens', '6 - 2 , 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 } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'} | 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', '13.9 ( 87 )', 'geelong', '8.12 ( 60 )', 'victoria park', '14000', '10 august 1929'], ['carlton', '17.17 ( 119 )', 'south melbourne', '11.15 ( 81 )', 'princes park', '20000', '10 august 1929'], ['st kilda', '21.16 ( 142 )', 'fitzroy', '10.15 ( 75 )', 'junction oval', '14500', '10 august 1929']] |
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': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; ratings ( kanto ) } ; episode } ; 3 } = true', 'tointer': 'select the row whose ratings ( kanto ) record of all rows is maximum . the episode record of this row is 3 .'} | 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', 'nov 8 , 2010 22.00 - 22.54', '4.3'], ['6', 'gray man 33 years of false accusation ( 冤罪33年の白髪男 )', 'daisuke habara', 'munenobu yamauchi', 'nov 22 , 2010 22.00 - 22.54', '3.2'], ['8', 'visits last miracle ( 最期の面会の奇跡 )', 'shizuka oki', 'tomoyuki furumaya', 'dec 6 , 2010 22.00 - 22.54', '3.0']] |
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 .'}, 'attendance'], 'result': '46450', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; opponent ; philadelphia eagles } ; attendance }'}, '46450'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; opponent ; philadelphia eagles } ; attendance } ; 46450 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles . the average of the attendance record of these rows is 46450 .'} | 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 louis cardinals', 't 17 - 17', '38264'], ['6', 'october 21 , 1962', 'philadelphia eagles', 'w 27 - 21', '60671'], ['7', 'october 28 , 1962', 'new york giants', 'l 49 - 34', '62844'], ['8', 'november 4 , 1962', 'dallas cowboys', 'l 38 - 10', '49888'], ['9', 'november 11 , 1962', 'cleveland browns', 'w 17 - 9', '48169'], ['10', 'november 18 , 1962', 'pittsburgh steelers', 'l 23 - 21', '21231'], ['11', 'november 25 , 1962', 'new york giants', 'l 42 - 24', '49219'], ['12', 'december 2 , 1962', 'philadelphia eagles', 'l 37 - 14', '32229'], ['13', 'december 8 , 1962', 'baltimore colts', 'l 34 - 21', '56964'], ['14', 'december 16 , 1962', 'pittsburgh steelers', 'l 27 - 24', '34508']] |
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', 'justin kurtz', 'defence', 'canada', 'brandon wheat kings ( whl )'], ['5', 'brian elder', 'goaltender', 'canada', 'brandon wheat kings ( whl )'], ['6', 'sylvain daigle', 'goaltender', 'canada', 'shawinigan cataractes ( qmjhl )'], ['7', 'paul traynor', 'defence', 'canada', 'kitchener rangers ( ohl )'], ['8', 'jaroslav obsut', 'right wing', 'slovakia', 'battlefords north stars ( sjhl )'], ['8', 'fredrik loven', 'defence', 'sweden', 'djurgardens if ( sel )'], ['9', 'robert deciantis', 'centre', 'canada', 'kitchener rangers ( ohl )']] |
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'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; jack kemp ( la ) } ; yards }', 'tointer': 'select the rows whose player record fuzzily matches to jack kemp ( la ) . take the yards record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'tom flores ( oak )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to tom flores ( oak ) .', 'tostr': 'filter_eq { all_rows ; player ; tom flores ( oak ) }'}, 'yards'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; tom flores ( oak ) } ; yards }', 'tointer': 'select the rows whose player record fuzzily matches to tom flores ( oak ) . take the yards record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; jack kemp ( la ) } ; yards } ; hop { filter_eq { all_rows ; player ; tom flores ( oak ) } ; yards } } = true', 'tointer': '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 .'} | 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', 'tom flores (oak)_12': 'tom flores ( oak )', 'yards_13': 'yards'} | {'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', '15', '16'], ['george blanda ( hou )', '169', '363', '46.6', '2413', '24', '22'], ['tom flores ( oak )', '136', '252', '54', '1738', '12', '12'], ['johnny green ( buf )', '89', '228', '39', '1267', '10', '10'], ['babe parilli ( oak )', '87', '187', '46.5', '1003', '5', '11'], ["tommy o'connell ( buf )", '65', '145', '44.8', '1033', '7', '13'], ['dick jamieson ( nyt )', '35', '70', '50', '586', '6', '2']] |
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 }'}, 'december 13'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 4 } ; date } ; december 13 } = true', 'tointer': 'select the row whose attendance record of all rows is 4th maximum . the date record of this row is december 13 .'} | 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', 'biron', '19037', '14 - 7 - 6'], ['december 11', 'carolina', '5 - 6', 'philadelphia', 'niittymaki', '19057', '15 - 7 - 6'], ['december 13', 'pittsburgh', '3 - 6', 'philadelphia', 'biron', '19811', '16 - 7 - 6'], ['december 16', 'colorado', '2 - 5', 'philadelphia', 'niittymaki', '19219', '17 - 7 - 6'], ['december 18', 'philadelphia', '2 - 5', 'montreal', 'niittymaki', '21273', '17 - 8 - 6'], ['december 20', 'washington', '1 - 7', 'philadelphia', 'niittymaki', '19897', '18 - 8 - 6'], ['december 21', 'philadelphia', '2 - 3', 'new jersey', 'niittymaki', '14426', '18 - 8 - 7'], ['december 23', 'ottawa', '4 - 6', 'philadelphia', 'nittymaki', '19578', '19 - 8 - 7'], ['december 26', 'philadelphia', '1 - 5', 'chicago', 'biron', '22712', '19 - 9 - 7'], ['december 27', 'philadelphia', '0 - 3', 'columbus', 'niittymaki', '18402', '19 - 10 - 7'], ['december 30', 'philadelphia', '3 - 2', 'vancouver', 'biron', '18630', '20 - 10 - 7']] |
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'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; average ; 2 } ; team } ; river plate } = true', 'tointer': 'select the row whose average record of all rows is 2nd maximum . the team record of this row is 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', '117', '114', '40', '36', '41'], ["newell 's old boys", '1.026', '117', '114', '48', '44', '25'], ['racing club', '1.009', '115', '114', '40', '39', '36'], ['deportivo español', '1.000', '114', '114', '28', '45', '41'], ['ferro carril oeste', '0.991', '113', '114', '38', '37', '38'], ['rosario central', '0.982', '112', '114', '39', '34', '39'], ['lanús', '0.974', '37', '38', 'n / a', 'n / a', '37'], ['belgrano de córdoba', '0.961', '73', '76', 'n / a', '35', '38'], ['textil mandiyú', '0.947', '108', '114', '38', '33', '37'], ['gimnasia de la plata', '0.947', '108', '114', '33', '41', '34'], ['estudiantes de la plata', '0.930', '106', '114', '39', '29', '38'], ['platense', '0.921', '105', '114', '35', '42', '28'], ['argentinos juniors', '0.912', '104', '114', '36', '35', '33'], ['talleres de córdoba', '0.851', '97', '114', '29', '37', '31']] |
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 { filter_eq { all_rows ; country ; india } }', 'tointer': 'select the rows whose country record fuzzily matches to india . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; india } } ; 4 } = true', 'tointer': 'select the rows whose country record fuzzily matches to india . the number of such rows is 4 .'} | 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', 'freedomfilmfestkomasorg'], ['vibgyor international film festival', '2006', 'thrissur', 'india', '2009 . vibgyorfilmcom'], ['yogyakarta documentary film festival', '2002', 'yogyakarta', 'indonesia', 'wwwfestivalfilmdokumenterorg'], ['yamagata international documentary film festival', '1989', 'yamagata', 'japan', 'wwwyidffjp'], ['jeevika : asia livelihood documentary festival', '2003', 'new delhi', 'india', 'wwwjeevikaorg']] |
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': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record does not match to united states . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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 }'}, 'player'], 'result': 'david graham', 'ind': 2, 'tostr': 'hop { filter_not_eq { all_rows ; country ; united states } ; player }'}, 'david graham'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; david graham }', 'tointer': 'the player record of this unqiue row is david graham .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_not_eq { all_rows ; country ; united states } } ; eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; david graham } } = true', 'tointer': '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 .'} | 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', '286', '+ 2', 't21'], ['hubert green', 'united states', '1985', '290', '+ 6', 't41'], ['dave stockton', 'united states', '1970 , 1976', '292', '+ 8', 't53']] |
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': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; still standing } ; launched }', 'tointer': 'select the rows whose name record fuzzily matches to still standing . take the launched record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'falling angel'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to falling angel .', 'tostr': 'filter_eq { all_rows ; name ; falling angel }'}, 'launched'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; falling angel } ; launched }', 'tointer': 'select the rows whose name record fuzzily matches to falling angel . take the launched record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; still standing } ; launched } ; hop { filter_eq { all_rows ; name ; falling angel } ; launched } } = true', 'tointer': '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 .'} | 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', 'falling angel_12': 'falling angel', 'launched_13': 'launched'} | {'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 )', '68', '50 minutes', '9 feb 2013', 'saturday to wednesday', '22:00 - 23:00'], ['4', 'the queen of the south', 'united states', 'telemundo ( 2011 )', '62', '45 minutes', '1 oct 2012', 'saturday to wednesday', '12:00 - 13:00'], ['5', 'aurora', 'united states', 'telemundo ( 2010 )', '135', '45 minutes', '5 may 2012', 'saturday to wednesday', '13:00 - 14:00'], ['6', 'still standing', 'united states', 'cbs ( 2002 )', '88', '21 minutes', '9 feb 2013', 'saturday to wednesday', '17:00 - 17:30'], ['7', 'project runway', 'united states', 'bravo ( 2004 )', '58', '45 minutes', '14 feb 2013', 'thursday & friday', '20:00 - 21:00'], ['8', 'a matter of respect', 'italy', 'canale 5 ( 2006 )', '24', '50 minutes', '25 oct 2012', 'thursday & friday', '21:00 - 22:00']] |
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 record of all rows is 6854 .'} | 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 , western', 'quarterfinals', '4th round', '5628'], ['2005', '2', 'usl first division', '5th', 'quarterfinals', '4th round', '6028'], ['2006', '2', 'usl first division', '11th', 'did not qualify', '3rd round', '5575'], ['2007', '2', 'usl first division', '2nd', 'semifinals', '2nd round', '6851'], ['2008', '2', 'usl first division', '11th', 'did not qualify', '1st round', '8567'], ['2009', '2', 'usl first division', '1st', 'semifinals', '3rd round', '9734']] |
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 summer olympics }'}, 'class'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; 2000 summer olympics } ; class }', 'tointer': 'select the rows whose competition record fuzzily matches to 2000 summer olympics . take the class record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '1996 summer olympics'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose competition record fuzzily matches to 1996 summer olympics .', 'tostr': 'filter_eq { all_rows ; competition ; 1996 summer olympics }'}, 'class'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; competition ; 1996 summer olympics } ; class }', 'tointer': 'select the rows whose competition record fuzzily matches to 1996 summer olympics . take the class record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; competition ; 2000 summer olympics } ; class } ; hop { filter_eq { all_rows ; competition ; 1996 summer olympics } ; class } } = true', 'tointer': '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 .'} | 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', 'competition_11': 'competition', '1996 summer olympics_12': '1996 summer olympics', 'class_13': 'class'} | {'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 - 13', '1998 asian games', 'won second asian games gold medal'], ['win', 'marian sandu', '54 kg', '5:3', '1998 - 08 - 30', '1998 world championships', 'won second world championship gold medal'], ['win', 'aleksandr pavlov', '48 kg', '4:0', '1996 - 07 - 21', '1996 summer olympics', 'won first olympic gold medal'], ['win', 'kang yong - gyun', '48 kg', '11:0', '1996 - 04 - 06', '1996 asian championships', 'won second asian championship gold medal'], ['win', 'hiroshi kado', '48 kg', '6:0', '1995 - 10 - 14', '1995 world championships', 'won first world championship gold medal'], ['win', 'dmitri korshunov', '48 kg', '12:0', '1995 - 06 - 28', '1995 asian championships', 'won first asian championship gold medal'], ['win', 'reza simkhah', '48 kg', '7:0', '1994 - 10 - 05', '1994 asian games', 'won first asian games gold medal']] |
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 } ; 1 }', 'tointer': 'the 1st minimum round record of all rows is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'round', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; round ; 1 }'}, 'player'], 'result': 'john hummer', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; round ; 1 } ; player }'}, 'john hummer'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; round ; 1 } ; player } ; john hummer }', 'tointer': 'the player record of the row with 1st minimum round record is john hummer .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; round ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; round ; 1 } ; player } ; john hummer } } = true', 'tointer': 'the 1st minimum round record of all rows is 1 . the player record of the row with 1st minimum round record is john hummer .'} | 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_15': 'john hummer'} | {'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', 'doug hess', 'united states', 'toledo'], ['7', '111', 'cliff shegogg', 'united states', 'colorado state'], ['8', '126', 'larry woods', 'united states', 'west virginia'], ['9', '145', 'larry duckworth', 'united states', 'henderson state'], ['10', '160', 'joe taylor', 'united states', 'dillard'], ['11', '177', 'dick walker', 'united states', 'wake forest']] |
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 }', 'tointer': 'the 6th minimum rank record of all rows is 6 .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'rank', '6'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; rank ; 6 }'}, 'team'], 'result': 'college of saint benilde', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 6 } ; team }'}, 'college of saint benilde'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 6 } ; team } ; college of saint benilde }', 'tointer': 'the team record of the row with 6th minimum rank record is college of saint benilde .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'rank', '6'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; rank ; 6 }'}, 'loss'], 'result': '4', 'ind': 5, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 6 } ; loss }'}, '4'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 6 } ; loss } ; 4 }', 'tointer': 'the loss record of the row with 6th minimum rank record is 4 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { nth_argmin { all_rows ; rank ; 6 } ; team } ; college of saint benilde } ; eq { hop { nth_argmin { all_rows ; rank ; 6 } ; loss } ; 4 } }', 'tointer': '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 .'}], 'result': True, 'ind': 8, 'tostr': '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', 'tointer': '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 .'} | 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': 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', 'college of saint benilde_18': 'college of saint benilde', 'eq_6': 'eq', 'num_hop_5': 'num_hop', 'loss_19': 'loss', '4_20': '4'} | {'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_5': [6], 'loss_19': [5], '4_20': [6]} | ['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 %'], ['6', 'college of saint benilde', '4', '3', '12', '20 %']] |
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': 'avg { filter_greater { all_rows ; total ; 13 } ; fighting spirit }'}, '5'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_greater { all_rows ; total ; 13 } ; fighting spirit } ; 5 } = true', 'tointer': 'select the rows whose total record is greater than 13 . the average of the fighting spirit record of these rows is 5 .'} | 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', '14', '3', '10', '1', '1990 - 2000', 'sekiwake'], ['musōyama', '13', '5', '4', '4', '1994 - 2000', 'ōzeki'], ['tosanoumi', '13', '7', '5', '1', '1995 - 2003', 'sekiwake'], ['kotomitsuki', '13', '2', '4', '7', '2000 - 07', 'ōzeki'], ['tochiazuma ii', '12', '3', '2', '7', '1996 - 2001', 'ōzeki'], ['takamiyama', '11', '6', '5', '0', '1968 - 81', 'sekiwake'], ['daiju', '11', '4', '1', '6', '1970 - 73', 'ōzeki'], ['kirinji', '11', '4', '4', '3', '1975 - 88', 'sekiwake'], ['hoshi', '11', '3', '3', '5', '1983 - 86', 'yokozuna']] |
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'], ['49', 'february 5', 'orlando', 'w 92 - 91 ( ot )', 'caron butler ( 31 )', 'brendan haywood ( 10 )', 'randy foye ( 7 )', 'amway arena 17461', '17 - 32'], ['50', 'february 9', 'charlotte', 'l 92 - 94 ( ot )', 'caron butler ( 23 )', 'brendan haywood ( 11 )', 'caron butler ( 8 )', 'time warner cable arena 12376', '17 - 33'], ['51', 'february 17', 'minnesota', 'w 108 - 99 ( ot )', 'andray blatche ( 33 )', 'andray blatche ( 13 )', 'earl boykins ( 8 )', 'verizon center 13143', '18 - 33'], ['52', 'february 19', 'denver', 'w 107 - 97 ( ot )', 'al thornton ( 21 )', 'andray blatche ( 11 )', 'mike miller ( 7 )', 'verizon center 17212', '19 - 33'], ['53', 'february 20', 'toronto', 'l 104 - 109 ( ot )', 'andray blatche ( 24 )', 'miller & howard ( 7 )', 'earl boykins ( 6 )', 'air canada centre 19149', '19 - 34'], ['54', 'february 22', 'chicago', 'w 101 - 95 ( ot )', 'andray blatche ( 25 )', 'james singleton ( 12 )', 'randy foye ( 9 )', 'verizon center 14113', '20 - 34'], ['55', 'february 24', 'memphis', 'l 94 - 99 ( ot )', 'andray blatche ( 24 )', 'al thornton ( 11 )', 'foye & miller ( 7 )', 'verizon center 11875', '20 - 35'], ['56', 'february 26', 'new york', 'l 116 - 118 ( ot ) ot', 'andray blatche ( 26 )', 'andray blatche ( 18 )', 'randy foye ( 10 )', 'verizon center 17408', '20 - 36']] |
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 time trap }'}, 'us air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; the tale of the time trap } ; us air date }', 'tointer': 'select the rows whose title record fuzzily matches to the tale of the time trap . take the us air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'the tale of the last dance'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to the tale of the last dance .', 'tostr': 'filter_eq { all_rows ; title ; the tale of the last dance }'}, 'us air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; the tale of the last dance } ; us air date }', 'tointer': 'select the rows whose title record fuzzily matches to the tale of the last dance . take the us air date record of this row .'}], 'result': True, 'ind': 4, 'tostr': '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', 'tointer': '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 .'} | 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_rows', 'title_11': 'title', 'the tale of the last dance_12': 'the tale of the last dance', 'us air date_13': 'us air date'} | {'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', 'mark soulard', 'd j machale', 'april 2 , 2000', "gary and tucker 's grandfather , gene", 'the evil spirit'], ['82', '4', 'the tale of the lunar locusts', 'jim donovan', 'michael koegel', 'april 9 , 2000', 'megan', 'the unborn alien babies'], ['83', '5', 'the tale of the stone maiden', 'adam weissman', 'mark d perry', 'april 16 , 2000', 'megan', 'the maiden statue'], ['84', '6', 'the tale of highway 13', 'jim donovan', 'ted elrick', 'april 23 , 2000', 'quinn', 'none'], ['85', '7', 'the tale of the reanimator', 'adam weissman', 'kenny davis', 'april 30 , 2000', 'quinn', 'reanimated zombie'], ['86', '8', 'the tale of the time trap', 'jim donovan', 'jim morris', 'may 7 , 2000', 'tucker', 'bell the genie'], ['87', '9', 'the tale of the photo finish', 'mark soulard', 'alan kingsberg', 'may 14 , 2000', 'andy', 'jasper davis'], ['88', '10', 'the tale of the last dance', 'jim donovan', 'mark d perry', 'may 21 , 2000', 'andy', 'none'], ['89', '11', 'the tale of the laser maze', 'mark soulard', 'peggy sarlin', 'may 28 , 2000', 'tucker', 'drake'], ['90', '12', 'the tale of many faces', 'lorette leblanc', 'alan kingsberg', 'june 4 , 2000', 'vange', 'madame visage']] |
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 than 12 .'}, 'crowd', '20000'], 'result': None, 'ind': 1, 'tointer': '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 .', 'tostr': 'filter_greater { filter_greater { all_rows ; home team score ; 12 } ; crowd ; 20000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_greater { all_rows ; home team score ; 12 } ; crowd ; 20000 } }', 'tointer': '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 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_greater { all_rows ; home team score ; 12 } ; crowd ; 20000 } } ; 2 } = true', 'tointer': '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 .'} | 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 1962'], ['collingwood', '12.10 ( 82 )', 'footscray', '7.11 ( 53 )', 'victoria park', '23936', '25 august 1962'], ['st kilda', '14.16 ( 100 )', 'hawthorn', '9.11 ( 65 )', 'junction oval', '17450', '25 august 1962'], ['melbourne', '11.9 ( 75 )', 'carlton', '5.10 ( 40 )', 'mcg', '54264', '25 august 1962']] |
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, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; length over all } ; model } ; n20 } = true', 'tointer': 'select the row whose length over all record of all rows is maximum . the model record of this row is n20 .'} | 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', '1', 'daggerboards'], ['5.0', '5.0 m', '2.44 m', '19 m square', '2', 'skegs design : roy seaman'], ['500', '5.0 m', '2.44 m', '17.6 m square', '1 - 2', 'skegs'], ['5.2', '5.2 m', '2.44 m', '20.43 m square', '2', 'daggerboards'], ['f17', '5.20 m', '2.44 m', '15.25 m square', '1', 'daggerboards'], ['nacra 17', '5.25 m', '2.59 m', '18.25 m square', '2', 'curved daggerboards design : morelli und melvin'], ['18sq', '5.48 m', '3.35 m', '18 m square', '1', 'daggerboards'], ['f18 inter 18', '5.52 m', '2.6 m', '20.45 / 21.15 m square', '2', 'f18 class boat design : morelli und melvin'], ['f18 inter 2', '5.52 m', '2.6 m', '20.45 / 21.15 m square', '2', 'f18 class boat design : alain comyn'], ['f18 infusion', '5.52 m', '2.6 m', '20.45 / 21.15 m square', '2', 'f18 class boat design : morelli und melvin'], ['5.7', '5.67 m', '2.44 m', '21.3 m square', '2', 'skegs'], ['570', '5.65 m', '2.44 m', '21.1 m square', '2', 'skegs'], ['5.8', '5.8 m', '2.5 m', '22.8 m square', '2', 'daggerboards design : roy seaman'], ['580', '5.8 m', '2.44 m', '22.1 m square', '2', 'daggerboards'], ['6.0', '6.10 m', '2.59 m', '24.5 m square', '2', 'daggerboards'], ['n20', '6.12 m', '2.6 m', '20.45 / 24.9 m square', '2', 'formula 20 class boat']] |
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 } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'} | 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 melbourne', '13.14 ( 92 )', 'footscray', '12.15 ( 87 )', 'lake oval', '15000', '8 august 1925'], ['melbourne', '7.10 ( 52 )', 'collingwood', '9.11 ( 65 )', 'mcg', '33642', '8 august 1925'], ['essendon', '15.11 ( 101 )', 'carlton', '8.14 ( 62 )', 'windy hill', '10000', '8 august 1925']] |
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', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 3 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 3 .'} | 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'], ['t5', 'luke donald', 'england', '71 + 72 + 70 + 67 = 280', 'e', '157000'], ['t5', 'mathew goggin', 'australia', '66 + 72 + 69 + 73 = 280', 'e', '157000'], ['t5', 'retief goosen', 'south africa', '67 + 70 + 71 + 72 = 280', 'e', '157000'], ['t8', 'thomas aiken', 'south africa', '71 + 72 + 69 + 69 = 281', '+ 1', '90400'], ['t8', 'ernie els', 'south africa', '69 + 72 + 72 + 68 = 281', '+ 1', '90400'], ['t8', 'søren hansen', 'denmark', '68 + 72 + 74 + 67 = 281', '+ 1', '90400'], ['t8', 'richard s johnson', 'sweden', '70 + 72 + 69 + 70 = 281', '+ 1', '90400'], ['t8', 'justin leonard', 'united states', '70 + 70 + 73 + 68 = 281', '+ 1', '90400']] |
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 2013', 'tórsvøllur , tórshavn , faroe islands', '2 - 0', '3 - 0', '2014 fifa world cup qualification']] |
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, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; east germany } ; lost }', 'tointer': 'select the rows whose team record fuzzily matches to east germany . take the lost record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'poland'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to poland .', 'tostr': 'filter_eq { all_rows ; team ; poland }'}, 'lost'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; poland } ; lost }', 'tointer': 'select the rows whose team record fuzzily matches to poland . take the lost record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; east germany } ; lost } ; hop { filter_eq { all_rows ; team ; poland } ; lost } } = true', 'tointer': '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 .'} | 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': 'poland', 'lost_13': 'lost'} | {'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': 2, 'tostr': 'hop { filter_eq { all_rows ; county ; eureka } ; mccain % }', 'tointer': 'select the rows whose county record fuzzily matches to eureka . take the mccain % record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'mineral'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose county record fuzzily matches to mineral .', 'tostr': 'filter_eq { all_rows ; county ; mineral }'}, 'mccain %'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; county ; mineral } ; mccain % }', 'tointer': 'select the rows whose county record fuzzily matches to mineral . take the mccain % record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; county ; eureka } ; mccain % } ; hop { filter_eq { all_rows ; county ; mineral } ; mccain % } } = true', 'tointer': '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 .'} | 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_12': 'mineral', 'mccain %_13': 'mccain %'} | {'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', '75.7 %', '144', '19.3 %'], ['humboldt', '3586', '63.3 %', '1909', '33.7 %'], ['lander', '1466', '69.7 %', '577', '27.5 %'], ['lincoln', '1498', '71.1 %', '518', '24.6 %'], ['lyon', '12154', '57.6 %', '8405', '39.8 %'], ['mineral', '1131', '49.0 %', '1082', '46.9 %'], ['nye', '9537', '54.5 %', '7226', '41.3 %'], ['pershing', '1075', '58.6 %', '673', '36.7 %'], ['storey', '1247', '51.6 %', '1102', '45.6 %'], ['washoe', '76880', '42.6 %', '99671', '55.3 %']] |
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 ( cubs )'], ['michael barrett', 'infielder', 'pace academy', 'atlanta , ga', '1st round - 28th pick of 1995 draft ( expos )'], ['chad hermansen', 'infielder', 'green valley high school', 'henderson , nv', '1st round - 10th pick of 1995 draft ( pirates )'], ['jay hood', 'infielder', 'germantown high school', 'germantown , tn', 'attended georgia tech'], ['nate rolison', 'infielder', 'petal high school', 'petal , ms', '2nd round - 36th pick of 1995 draft ( marlins )'], ['shion newton', 'outfielder', 'boys and girls high school', 'brooklyn , ny', '9th round - 6th pick of 1995 draft ( pirates )'], ['reggie taylor', 'outfielder', 'newberry high school', 'newberry , sc', '1st round - 14th pick of 1995 draft ( phillies )']] |
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, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; cores ; 2 } ; model } ; l3c } = true', 'tointer': 'select the row whose cores record of all rows is 2nd maximum . the model record of this row is l3c .'} | 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', '450', 'mips - iii 64 - bit', '1', '180'], ['godson - 2 ( singlecore )', 'stls2e', '1000', 'mips - iii 64 - bit', '1', '90'], ['godson - 2 ( singlecore )', 'stls2f', '1200', 'mips - iii 64 - bit', '1', '90'], ['godson - 2 ( singlecore )', 'l2 g', '9001000', 'mips64', '1', '65'], ['godson - 2 ( singlecore )', 'l2h', '1000', 'mips64', '1', '65'], ['godson - 3 ( multicore )', 'l3a / l2 gq', '1000', 'mips64', '4', '65'], ['godson - 3 ( multicore )', 'l3b', '1050', 'mips64', '8', '65'], ['godson - 3 ( multicore )', 'l3c', '1500 +', 'mips64', '16', '28'], ['godson - t ( manycore )', 'godson - t', '1000', 'mips32', '64', '28'], ['name / generation', 'model', 'frequency', 'architecture version', 'cores', 'process']] |
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 2 .'} | 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', 'nwsl', 'starfire sports', '2012', '0'], ['seattle thunderbirds', 'ice hockey', 'whl', 'showare center', '1977', '0'], ['seattle rainmakers', 'ultimate', 'mlu', 'renton memorial stadium', '2012', '0']] |
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 { all_rows ; weeks on top ; 2 } }', 'tointer': 'select the rows whose weeks on top record is equal to 2 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; weeks on top ; 2 } } ; 4 } = true', 'tointer': 'select the rows whose weeks on top record is equal to 2 . the number of such rows is 4 .'} | 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 - 11 april', '3', 'celebration', 'kool & the gang'], ['34:19 - 20', '18 - 25 april', '2', '9 to 5', 'dolly parton'], ['34:21 - 22', '2 - 9 may', '2', 'morning train', 'sheena easton'], ['34:23 - 25', '16 - 30 may', '3', 'angel of the morning', 'juice newton'], ['34:26 - 35:4', '6 june - 22 august', '12', 'stars on 45 medley', 'stars on 45'], ['35:5 §', '29 august', '1', 'gemini dream', 'moody blues'], ['35:6', '5 september', '1', 'sausalito summernight', 'diesel'], ['35:7 - 8', '12 - 19 september', '2', 'urgent', 'foreigner'], ['35:9 - 14', '26 september - 31 october', '6', 'endless love', 'diana ross and lionel richie'], ['35:15', '7 november', '1', 'every little thing she does is magic', 'the police'], ['35:16 - 20', '14 november - 12 december', '5', 'the friends of mr cairo', 'jon & vangelis'], ['35:21 - 24', '19 december - 23 january 1982', '6', 'physical', 'olivia newton - john']] |
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 ; hampden park , glasgow , scotland }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; hampden park , glasgow , scotland } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to hampden park , glasgow , scotland . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'varsity stadium , toronto , canada'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to varsity stadium , toronto , canada .', 'tostr': 'filter_eq { all_rows ; venue ; varsity stadium , toronto , canada }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; varsity stadium , toronto , canada } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to varsity stadium , toronto , canada . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; venue ; hampden park , glasgow , scotland } ; date } ; hop { filter_eq { all_rows ; venue ; varsity stadium , toronto , canada } ; date } } = true', 'tointer': '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 .'} | 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_rows', 'venue_11': 'venue', 'varsity stadium , toronto , canada_12': 'varsity stadium , toronto , canada', 'date_13': 'date'} | {'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 , belarus', '0 - 1', 'win', '1998 world cup qualification']] |
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 } ; incumbent }'}, 'dale alford'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; first elected ; 1 } ; incumbent } ; dale alford } = true', 'tointer': 'select the row whose first elected record of all rows is 1st maximum . the incumbent record of this row is dale alford .'} | 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 ( d ) unopposed'], ['arkansas 4', 'oren harris', 'democratic', '1940', 're - elected', 'oren harris ( d ) unopposed'], ['arkansas 5', 'dale alford', 'democratic', '1958', 're - elected', 'dale alford ( d ) 82.7 % l j churchill ( r ) 17.3 %']] |
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 , state )', 'california'], 'result': True, 'ind': 1, 'tointer': '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 .', 'tostr': 'most_eq { filter_eq { all_rows ; 1st ship delivery date ; 1942 } ; location ( city , state ) ; california } = true'} | 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', 'tacoma , washington', 'april 1941', 'c1 type , c3 type , t1 type', '8 ways', '__ ships for usmc ( remainder for usn )'], ['western pipe & steel corp', 'south san francisco , california', 'april 1941', 'c1 type , c3 type', '4 ways', '__ ships for usmc'], ['kaiser permanente ( richmond yard 1 )', 'richmond , california', 'august 1941', 'british ocean type , ec2 type , vc2 type', '7 ways', '30 ships for uk , __ ships for usmc'], ['kaiser permanente ( richmond yard 2 )', 'richmond , california', 'september 1941', 'ec2 type , vc2 type', '12 ways', '__ ships for usmc'], ['oregon shipbuilding co', 'portland , oregon', 'january 1942', 'ec2 type , vc2 type', '11 ways', '__ ships for usmc'], ['california shipbuilding corp ( calship )', 'terminal island , los angeles , california', 'february 1942', 'ec2 type , vc2 type', '14 ways', '__ ships for usmc'], ['marinship corp', 'sausalito , california', 'october 1942', 'ec2 type , t2 type', '6 ways', '__ ships for usmc'], ['pacific bridge co', 'alameda , california', 'december 1942', 'n3 type', '2 ways ( basins )', '9 ships for usmc ( remainder for usn )'], ['kaiser company , inc', 'swan island , portland , oregon', 'december 1942', 't2 type', '8 ways', '__ ships for usmc'], ['kaiser cargo ( richmond yard 4 )', 'richmond , california', 'april 1943', 's2 ( lst ) type , s2 ( frigate ) type , c1 - m type', '3 ways', '__ ships for usmc'], ['kaiser shipbuilding ( richmond yard 3 )', 'richmond , california', 'august 1943', 'c4 type', '5 ways ( basins )', '__ ships for usmc']] |
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_rows ; date ; 1 } ; october 24 , 2008 } = true', 'tointer': 'the 1st minimum date record of all rows is october 24 , 2008 .'} | 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', 'columbia', '2cd', '88697374522'], ['australia', 'july 11 , 2011', 'legacy recordings', '2cd', '88697936772'], ['europe', 'july 15 , 2011', 'legacy recordings', '2cd', '88697936772'], ['north america', 'august 29 , 2011', 'legacy recordings', '3cd', '886979487321'], ['north america', 'september 13 , 2011', 'legacy recordings', '2cd', '886979487222']] |
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'], ['winner', '25 july 2006', "monteroni d'arbia , italy", 'clay', 'edina gallovits - hall', '6 - 2 , 6 - 1'], ['runner - up', '31 july 2006', 'martina franca , italy', 'clay', 'margalita chakhnashvili', '6 - 3 , 7 - 5'], ['runner - up', '13 march 2007', 'orange , usa', 'hard', 'naomi cavaday', '6 - 1 , 6 - 1'], ['runner - up', '3 april 2007', 'dinan , france', 'clay ( i )', 'maša zec peškirič', '6 - 4 , 6 - 2'], ['runner - up', '9 april 2007', 'civitavecchia , italy', 'clay', 'darya kustova', '3 - 6 , 6 - 4 , 6 - 4'], ['runner - up', '9 july 2007', 'biella , italy', 'clay', 'agnieszka radwańska', '6 - 3 , 6 - 3'], ['runner - up', '11 october 2010', 'settimo san pietro , italy', 'clay', 'anastasia grymalska', '4 - 6 , 6 - 2 , 7 - 5'], ['winner', '18 october 2010', 'seville , spain', 'clay', 'andrea gámiz', '6 - 0 , 6 - 1'], ['runner - up', '16 november 2010', 'mallorca , spain', 'clay', 'diana enache', '6 - 4 , 6 - 2'], ['winner', '7 june 2011', 'campobasso , italy', 'clay', 'alizé lim', '6 - 2 , 6 - 4'], ['runner - up', '14 june 2011', 'padova , italy', 'clay', 'kristina mladenovic', '3 - 6 , 6 - 4 , 6 - 0'], ['winner', '20 june 2011', 'rome , italy', 'clay', 'laura thorpe', '6 - 3 , 6 - 0'], ['runner - up', '27 august 2012', 'bagnatica , italy', 'clay', 'maria - elena camerin', '7 - 6 ( 5 ) , 6 - 4'], ['winner', '4 september 2012', 'mestre , italy', 'clay', 'estrella cabeza candela', '6 - 1 , 3 - 6 , 6 - 1'], ['runner - up', '12 may 2013', 'trnava , slovakia', 'clay', 'barbora záhlavová - strýcová', '6 - 2 , 6 - 4']] |
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'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; houston , texas } ; date }', 'tointer': 'select the rows whose location record fuzzily matches to houston , texas . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'zapopan , jalisco'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to zapopan , jalisco .', 'tostr': 'filter_eq { all_rows ; location ; zapopan , jalisco }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; location ; zapopan , jalisco } ; date }', 'tointer': 'select the rows whose location record fuzzily matches to zapopan , jalisco . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; location ; houston , texas } ; date } ; hop { filter_eq { all_rows ; location ; zapopan , jalisco } ; date } } = true', 'tointer': '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 .'} | 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', 'zapopan , jalisco_12': 'zapopan , jalisco', 'date_13': 'date'} | {'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 , 1992'], ['hair', 'vampiro', 'sangre chicana', 'monterrey , nuevo león', 'december 10 , 1992'], ['hair', 'vampiro', 'pirata morgan', 'houston , texas', 'september 1 , 1998'], ['hair', 'vampiro', 'rey bucanero', 'mexico city', 'december 13 , 2002'], ['hair', 'shocker', 'vampiro', 'mexico city', 'april 4 , 2003'], ['hair', 'cien caras and máscara año 2000', 'vampiro and pierroth , jr', 'mexico city', 'december 17 , 2004'], ['hair', 'chessman', 'vampiro', 'zapopan , jalisco', 'december 2 , 2012']] |
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': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; satellite ; echo 2 } ; mass ( kg ) }', 'tointer': 'select the rows whose satellite record fuzzily matches to echo 2 . take the mass ( kg ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'satellite', 'mylar balloon'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose satellite record fuzzily matches to mylar balloon .', 'tostr': 'filter_eq { all_rows ; satellite ; mylar balloon }'}, 'mass ( kg )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; satellite ; mylar balloon } ; mass ( kg ) }', 'tointer': 'select the rows whose satellite record fuzzily matches to mylar balloon . take the mass ( kg ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; satellite ; echo 2 } ; mass ( kg ) } ; hop { filter_eq { all_rows ; satellite ; mylar balloon } ; mass ( kg ) } } = true', 'tointer': '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 .'} | 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': 'satellite', 'mylar balloon_12': 'mylar balloon', 'mass (kg)_13': 'mass ( kg )'} | {'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 - 053a', 'us', 'ado'], ['echo 2', '1964 - 01 - 25 13:55:00', '1969 - 06 - 07', '256', '41', '1964 - 004a', 'us', 'pcr , tri'], ['explorer 24 ( ad - b )', '1964 - 11 - 21 17:17:00', '1968 - 10 - 18', '8.6', '3.6', '1964 - 076a', 'us', 'ado'], ['pageos 1', '1966 - 06 - 24 00:14:00', '1975 - 07 - 12', '56.7', '30.48', '1966 - 056a', 'us', 'tri'], ['explorer 39 ( ad - c )', '1968 - 08 - 08 20:12:00', '1981 - 06 - 22', '9.4', '3.6', '1968 - 066a', 'us', 'ado'], ['mylar balloon', '1971 - 08 - 07 00:11:00', '1981 - 09 - 01', '0.8', '2.13', '1971 - 067f', 'us', 'ado'], ['qi qiu weixing 1', '1990 - 09 - 03 00:53:00', '1991 - 03 - 11', '4', '3', '1990 - 081b', 'prc', 'ado'], ['qi qiu weixing 2', '1990 - 09 - 03 00:53:00', '1991 - 07 - 24', '4', '2.5', '1990 - 081c', 'prc', 'ado']] |
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': '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 .', 'tostr': 'most_eq { filter_eq { all_rows ; player ; mike hercus } ; tries ; 0 } = true'} | 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 francisco', '06 / 07 / 1996'], ['matt alexander', '1', '4', '3', '0', 'san francisco', '29 / 06 / 1996'], ['mike hercus', '0', '5', '4', '0', 'madrid', '12 / 04 / 2003']] |
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 - elected .'}, 'first elected', '1990'], 'result': None, 'ind': 1, 'tointer': '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 .', 'tostr': 'filter_eq { filter_eq { all_rows ; results ; re - elected } ; first elected ; 1990 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; results ; re - elected } ; first elected ; 1990 } }', 'tointer': '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 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; results ; re - elected } ; first elected ; 1990 } } ; 2 } = true', 'tointer': '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 .'} | 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 ( d ) 30 %'], ['ohio 5', 'paul e gillmor', 'republican', '1988', 're - elected', 'paul e gillmor ( r ) 70 % dannie edmon ( d ) 26 %'], ['ohio 6', 'ted strickland', 'democratic', '1992', 're - elected', 'ted strickland ( d ) 58 % mike azinger ( r ) 41 %'], ['ohio 7', 'david l hobson', 'republican', '1990', 're - elected', 'david l hobson ( r ) 68 % donald minor ( d ) 25 %'], ['ohio 8', 'john a boehner', 'republican', '1990', 're - elected', 'john a boehner ( r ) 71 % john parks ( d ) 27 %'], ['ohio 9', 'marcia c kaptur', 'democratic', '1982', 're - elected', 'marcia c kaptur ( d ) 75 % dwight bryan ( r ) 23 %'], ['ohio 10', 'dennis j kucinich', 'democratic', '1996', 're - elected', 'dennis j kucinich ( d ) 76 % bill smith ( r ) 23 %'], ['ohio 11', 'stephanie tubbs jones', 'democratic', '1998', 're - elected', 'stephanie tubbs jones ( d ) 86 % james sykora ( r ) 12 %'], ['ohio 12', 'john kasich', 'republican', '1982', 'retired republican hold', "pat tiberi ( r ) 53 % maryellen o ' shaughnessy ( d ) 44 %"], ['ohio 13', 'sherrod brown', 'democratic', '1992', 're - elected', 'sherrod brown ( d ) 65 % rick jeric ( r ) 33 %'], ['ohio 14', 'tom sawyer', 'democratic', '1986', 're - elected', 'tom sawyer ( d ) 65 % rick wood ( r ) 32 %'], ['ohio 15', 'deborah d pryce', 'republican', '1992', 're - elected', 'deborah d pryce ( r ) 68 % bill buckel ( d ) 28 %'], ['ohio 16', 'ralph s regula', 'republican', '1972', 're - elected', 'ralph s regula ( r ) 70 % william smith ( d ) 27 %'], ['ohio 17', 'james traficant', 'democratic', '1984', 're - elected', 'james traficant ( d ) 50 % paul alberty ( r ) 23 %']] |
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_eq { all_rows ; year born ; 1979 } }', 'tointer': 'select the rows whose year born record is equal to 1979 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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 }'}, 'player'], 'result': 'konstantinos tsartsaris', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year born ; 1979 } ; player }'}, 'konstantinos tsartsaris'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; year born ; 1979 } ; player } ; konstantinos tsartsaris }', 'tointer': 'the player record of this unqiue row is konstantinos tsartsaris .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; year born ; 1979 } } ; eq { hop { filter_eq { all_rows ; year born ; 1979 } ; player } ; konstantinos tsartsaris } } = true', 'tointer': '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 .'} | 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', 'olympiacos'], ['michalis pelekanos', '1.98', 'forward', '1981', 'real madrid'], ['nikolaos chatzivrettas', '1.95', 'guard', '1977', 'panathinaikos'], ['dimosthenis dikoudis', '2.06', 'forward', '1977', 'panathinaikos'], ['konstantinos tsartsaris', '2.09', 'center', '1979', 'panathinaikos'], ['dimitris diamantidis', '1.96', 'guard', '1980', 'panathinaikos'], ['lazaros papadopoulos', '2.10', 'center', '1980', 'real madrid'], ['michail kakiouzis', '2.07', 'forward', '1976', 'cb sevilla']] |
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', 'naju', '500000000', 'kang kyung - nam', '6'], ['may 30 - jun 2', 'gunsan cc open', 'gunsan', '300000000', 'lee soo - min ( a )', '6'], ['aug 1 - 4', 'bosung cc classic', 'boseong', '300000000', 'kim tae - hoon', '6'], ['aug 8 - 11', 'solaseado - pine beach open', 'haenam', '300000000', 'hong soon - sang', '6'], ['aug 15 - 18', 'kpga championship', 'chungju', '500000000', 'kim hyung - tae', '6'], ['sep 12 - 15', 'dongbu promi open', 'hoengseong', '400000000', 'lee chang - woo ( a )', '6'], ['sep 26 - 29', 'shinhan donghae open', 'incheon', '1000000000', 'bae sang - moon', '6'], ['oct 4 - 6', 'munsingwear match play championship', 'pyeongchang', '600000000', 'kim do - hoon', '6'], ['oct 10 - 13', 'cj invitational', 'yeoju', 'us 750000', 'kang sung - hoon', '14'], ['oct 17 - 20', 'kolon korea open', 'cheonan', '1000000000', 'kang sung - hoon', '14'], ['oct 29 - nov 1', 'hearld kyj tour championship', 'seogwipo', '300000000', 'hur in - hoi', '6']] |
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'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; entry date } ; single } ; meet me halfway } = true', 'tointer': 'select the row whose entry date record of all rows is minimum . the single record of this row is meet me halfway .'} | 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'], ['26 december', 'the climb', 'joe mcelderry', '1', '26 december', '2'], ['26 december', 'killing in the name', 'rage against the machine', '2', '26 december', '2']] |
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', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; native american ; 0.0 % } }', 'tointer': 'select the rows whose native american record fuzzily matches to 0.0 % . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; native american ; 0.0 % } } ; 4 } = true', 'tointer': 'select the rows whose native american record fuzzily matches to 0.0 % . the number of such rows is 4 .'} | 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 %', '0.0 %', '0.0 %', '0.0 %', '0.0 %'], ['colombia', '45393050', '1.8 %', '20.0 %', '53.2 %', '21.0 %', '3.9 %', '0.1 %', '0.0 %'], ['costa rica', '4253897', '0.8 %', '82.0 %', '15.0 %', '0.0 %', '0.0 %', '2.0 %', '0.2 %'], ['cuba', '11236444', '0.0 %', '37.0 %', '0.0 %', '51.0 %', '11.0 %', '0.0 %', '1.0 %'], ['dominican republic', '8562541', '0.0 %', '14.6 %', '0.0 %', '75.0 %', '7.7 %', '2.3 %', '0.4 %'], ['ecuador', '13625000', '39.0 %', '9.9 %', '41.0 %', '5.0 %', '5.0 %', '0.0 %', '0.1 %'], ['el salvador', '6134000', '1.0 %', '12.0 %', '86.0 %', '0.0 %', '0.0 %', '0.0 %', '0.0 %'], ['guatemala', '13276517', '53.0 %', '4.0 %', '42.0 %', '0.0 %', '0.0 %', '0.2 %', '0.8 %'], ['honduras', '7810848', '7.7 %', '1.0 %', '85.6 %', '1.7 %', '0.0 %', '3.3 %', '0.7 %'], ['mexico', '112322757', '14 %', '15 %', '70 %', '0.5 %', '0.0 %', '0.0 %', '0.5 %'], ['nicaragua', '5891199', '6.9 %', '14.0 %', '78.3 %', '0.0 %', '0.0 %', '0.6 %', '0.2 %'], ['panama', '3322576', '8.0 %', '10.0 %', '32.0 %', '27.0 %', '5.0 %', '14.0 %', '4.0 %'], ['paraguay', '6349000', '1.5 %', '20.0 %', '74.5 %', '3.5 %', '0.0 %', '0.0 %', '0.5 %'], ['peru', '29461933', '45.5 %', '12.0 %', '32.0 %', '9.7 %', '0.0 %', '0.0 %', '0.8 %'], ['puerto rico', '3967179', '0.0 %', '74.8 %', '0.0 %', '10.0 %', '15.0 %', '0.0 %', '0.2 %'], ['uruguay', '3494382', '0.0 %', '88.0 %', '8.0 %', '4.0 %', '0.0 %', '0.0 %', '0.0 %'], ['venezuela', '26814843', '2.7 %', '42.2 %', '42.9 %', '0.7 %', '2.8 %', '0.0 %', '2.2 %']] |
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