niryuu/sni-each-converted huggingface dataset:
for the average attendance home records of all rows , most of them are less than 3200 .
Output: most_less { all_rows ; average attendance home ; 3200 }
for the charleston southerns head coach records of all rows , most of them fuzzily match to jay mills .
Output: most_eq { all_rows ; charleston southerns head coach ; jay mills }
the sum of the points record of all rows is 5 .
Output: round_eq { sum { all_rows ; points } ; 5 }
select the rows whose surface record fuzzily matches to clay . there is only one such row in the table . the tournament record of this unqiue row is trivandrum .
Output: and { only { filter_eq { all_rows ; surface ; clay } } ; eq { hop { filter_eq { all_rows ; surface ; clay } ; tournament } ; trivandrum } }
select the rows whose year record is less than 1990 . among these rows , select the rows whose 250 cc record fuzzily matches to sito pons . the number of such rows is 3 .
Output: eq { count { filter_eq { filter_less { all_rows ; year ; 1990 } ; 250 cc ; sito pons } } ; 3 }
select the rows whose surface record fuzzily matches to hard . the number of such rows is 7 .
Output: eq { count { filter_eq { all_rows ; surface ; hard } } ; 7 }
select the rows whose train no record fuzzily matches to 5037 . take the arrival record of this row . select the rows whose train no record fuzzily matches to 4723 . take the arrival record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; train no ; 5037 } ; arrival } ; hop { filter_eq { all_rows ; train no ; 4723 } ; arrival } }
the 1st minimum date record of all rows is 03 oct . the time record of the row with 1st minimum date record is 12:00 .
Output: and { eq { nth_min { all_rows ; date ; 1 } ; 03 oct } ; eq { hop { nth_argmin { all_rows ; date ; 1 } ; time } ; 12:00 } }
select the rows whose outcome record fuzzily matches to runner - up . the number of such rows is 3 .
Output: eq { count { filter_eq { all_rows ; outcome ; runner - up } } ; 3 }
select the row whose overall record of all rows is 2nd maximum . the name record of this row is wayne millner .
Output: eq { hop { nth_argmax { all_rows ; overall ; 2 } ; name } ; wayne millner }
for the party records of all rows , most of them fuzzily match to democratic - republican .
Output: most_eq { all_rows ; party ; democratic - republican }
for the country records of all rows , most of them fuzzily match to south korea .
Output: most_eq { all_rows ; country ; south korea }
select the rows whose average annual rainfall ( mm ) record is less than 100 . among these rows , select the rows whose average annual runoff ( mm ) record is less than 1 . the number of such rows is 2 .
Output: eq { count { filter_less { filter_less { all_rows ; average annual rainfall ( mm ) ; 100 } ; average annual runoff ( mm ) ; 1 } } ; 2 }
select the row whose issue date ( s ) record of all rows is minimum . the artist record of this row is eiffel 65 .
Output: eq { hop { argmin { all_rows ; issue date ( s ) } ; artist } ; eiffel 65 }
select the rows whose surface record fuzzily matches to grass . the number of such rows is 2 .
Output: eq { count { filter_eq { all_rows ; surface ; grass } } ; 2 }
select the rows whose date record fuzzily matches to 6 june 2010 ( round 13 ) . take the total record of this row . select the rows whose date record fuzzily matches to 5 april 2008 ( round 4 ) . take the total record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; date ; 6 june 2010 ( round 13 ) } ; total } ; hop { filter_eq { all_rows ; date ; 5 april 2008 ( round 4 ) } ; total } }
select the rows whose date record fuzzily matches to december 30 , 2007 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 23 , 2007 . take the attendance record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; date ; december 30 , 2007 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 23 , 2007 } ; attendance } }
select the row whose result record of all rows is maximum . the venue record of this row is estádio campo desportivo , macau .
Output: eq { hop { argmax { all_rows ; result } ; venue } ; estádio campo desportivo , macau }
select the row whose price ( usd ) record of all rows is 1st maximum . the model number record of this row is itanium 2 9040 .
Output: eq { hop { nth_argmax { all_rows ; price ( usd ) ; 1 } ; model number } ; itanium 2 9040 }
the average of the mintage record of all rows is 22800 .
Output: round_eq { avg { all_rows ; mintage } ; 22800 }
the average of the candidates record of all rows is 13 .
Output: round_eq { avg { all_rows ; candidates } ; 13 }
select the rows whose name record fuzzily matches to amy van dyken . take the time record of this row . select the rows whose name record fuzzily matches to vivienne rignall . take the time record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; name ; amy van dyken } ; time } ; hop { filter_eq { all_rows ; name ; vivienne rignall } ; time } }
select the rows whose artist record fuzzily matches to the playtones . take the total record of this row . select the rows whose artist record fuzzily matches to brolle . take the total record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; artist ; the playtones } ; total } ; hop { filter_eq { all_rows ; artist ; brolle } ; total } }
select the rows whose region record fuzzily matches to east . among these rows , select the rows whose state record fuzzily matches to virginia . the number of such rows is 2 .
Output: eq { count { filter_eq { filter_eq { all_rows ; region ; east } ; state ; virginia } } ; 2 }
select the row whose distance ( ly ) record of all rows is 1st minimum . the constellation record of this row is ursa major .
Output: eq { hop { nth_argmin { all_rows ; distance ( ly ) ; 1 } ; constellation } ; ursa major }
select the rows whose partial thromboplastin time record fuzzily matches to shortened . there is only one such row in the table . the condition record of this unqiue row is c1inh deficiency .
Output: and { only { filter_eq { all_rows ; partial thromboplastin time ; shortened } } ; eq { hop { filter_eq { all_rows ; partial thromboplastin time ; shortened } ; condition } ; c1inh deficiency } }
select the rows whose venue record fuzzily matches to venezuela . the number of such rows is 5 .
Output: eq { count { filter_eq { all_rows ; venue ; venezuela } } ; 5 }
select the rows whose name record fuzzily matches to franck esposito . take the time record of this row . select the rows whose name record fuzzily matches to andrew livingston . take the time record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; name ; franck esposito } ; time } ; hop { filter_eq { all_rows ; name ; andrew livingston } ; time } }
select the row whose average ratings record of all rows is maximum . the romaji title record of this row is karei - naru ichizoku .
Output: eq { hop { argmax { all_rows ; average ratings } ; romaji title } ; karei - naru ichizoku }
the average of the seats record of all rows is 55 .
Output: round_eq { avg { all_rows ; seats } ; 55 }
select the row whose qual 1 record of all rows is minimum . the name record of this row is paul tracy .
Output: eq { hop { argmin { all_rows ; qual 1 } ; name } ; paul tracy }
the average of the best score record of all rows is 37 .
Output: round_eq { avg { all_rows ; best score } ; 37 }
for the type records of all rows , most of them fuzzily match to sovereign .
Output: most_eq { all_rows ; type ; sovereign }
the sum of the crowd record of all rows is 79,000 .
Output: round_eq { sum { all_rows ; crowd } ; 79,000 }
select the rows whose gold record is equal to 2 . among these rows , select the rows whose total record is equal to 4 . the number of such rows is 2 .
Output: eq { count { filter_eq { filter_eq { all_rows ; gold ; 2 } ; total ; 4 } } ; 2 }
for the best score records of all rows , most of them are greater than or equal to 29 .
Output: most_greater_eq { all_rows ; best score ; 29 }
select the rows whose island record fuzzily matches to north island . the maximum elevation ( m ) record of these rows is 2797 .
Output: eq { max { filter_eq { all_rows ; island ; north island } ; elevation ( m ) } ; 2797 }
select the rows whose winner record fuzzily matches to billy casper . the number of such rows is 3 .
Output: eq { count { filter_eq { all_rows ; winner ; billy casper } } ; 3 }
select the rows whose engine record fuzzily matches to lamborghini v12 . the sum of the points record of these rows is 10 .
Output: round_eq { sum { filter_eq { all_rows ; engine ; lamborghini v12 } ; points } ; 10 }
select the rows whose away team record fuzzily matches to melbourne . the sum of the crowd record of these rows is 25000 .
Output: round_eq { sum { filter_eq { all_rows ; away team ; melbourne } ; crowd } ; 25000 }
select the rows whose method record fuzzily matches to submission ( triangle choke ) . there is only one such row in the table . the res record of this unqiue row is loss .
Output: and { only { filter_eq { all_rows ; method ; submission ( triangle choke ) } } ; eq { hop { filter_eq { all_rows ; method ; submission ( triangle choke ) } ; res } ; loss } }
select the rows whose nationality record fuzzily matches to greece . there is only one such row in the table . the name record of this unqiue row is anastasios gousis .
Output: and { only { filter_eq { all_rows ; nationality ; greece } } ; eq { hop { filter_eq { all_rows ; nationality ; greece } ; name } ; anastasios gousis } }
select the rows whose goals record is equal to 0 . the number of such rows is 2 .
Output: eq { count { filter_eq { all_rows ; goals ; 0 } } ; 2 }
select the rows whose status record fuzzily matches to village . the number of such rows is 4 .
Output: eq { count { filter_eq { all_rows ; status ; village } } ; 4 }
select the row whose closed record of all rows is 2nd minimum . the venue record of this row is jim crockett park .
Output: eq { hop { nth_argmin { all_rows ; closed ; 2 } ; venue } ; jim crockett park }
select the rows whose time record is less than 2:01 . among these rows , select the rows whose nationality record fuzzily matches to australia . the number of such rows is 2 .
Output: eq { count { filter_eq { filter_less { all_rows ; time ; 2:01 } ; nationality ; australia } } ; 2 }
select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the date record of this unqiue row is 28 october 2007 .
Output: and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; 28 october 2007 } }
the average of the speed record of all rows is 92.14 .
Output: round_eq { avg { all_rows ; speed } ; 92.14 }
select the rows whose venue record fuzzily matches to kuwait . there is only one such row in the table . the date record of this unqiue row is 26 jan 2005 .
Output: and { only { filter_eq { all_rows ; venue ; kuwait } } ; eq { hop { filter_eq { all_rows ; venue ; kuwait } ; date } ; 26 jan 2005 } }
select the rows whose extinct record is equal to 1924 . the number of such rows is 4 .
Output: eq { count { filter_eq { all_rows ; extinct ; 1924 } } ; 4 }
the sum of the gold record of all rows is 14 .
Output: round_eq { sum { all_rows ; gold } ; 14 }
select the row whose year established record of all rows is minimum . the members record of this row is university of tübingen .
Output: eq { hop { argmin { all_rows ; year established } ; members } ; university of tübingen }
select the rows whose mascot record fuzzily matches to scorpion . there is only one such row in the table . the elementary schools record of this unqiue row is san tan ( home ) .
Output: and { only { filter_eq { all_rows ; mascot ; scorpion } } ; eq { hop { filter_eq { all_rows ; mascot ; scorpion } ; elementary schools } ; san tan ( home ) } }
select the rows whose venue record fuzzily matches to colombo . there is only one such row in the table . the date record of this unqiue row is 6 june 2008 .
Output: and { only { filter_eq { all_rows ; venue ; colombo } } ; eq { hop { filter_eq { all_rows ; venue ; colombo } ; date } ; 6 june 2008 } }
select the rows whose 2013 population ( july est ) record is greater than 7000000 . the number of such rows is 2 .
Output: eq { count { filter_greater { all_rows ; 2013 population ( july est ) ; 7000000 } } ; 2 }
select the rows whose nation record fuzzily matches to turkey . take the gold record of this row . select the rows whose nation record fuzzily matches to soviet union . take the gold record of this row . the first record is greater than the second record . the gold record of the first row is 4 . the gold record of the second row is 2 .
Output: and { greater { hop { filter_eq { all_rows ; nation ; turkey } ; gold } ; hop { filter_eq { all_rows ; nation ; soviet union } ; gold } } ; and { eq { hop { filter_eq { all_rows ; nation ; turkey } ; gold } ; 4 } ; eq { hop { filter_eq { all_rows ; nation ; soviet union } ; gold } ; 2 } } }
select the rows whose rank record fuzzily matches to 8th . there is only one such row in the table . the year record of this unqiue row is 1988 .
Output: and { only { filter_eq { all_rows ; rank ; 8th } } ; eq { hop { filter_eq { all_rows ; rank ; 8th } ; year } ; 1988 } }
the average of the avg attendance record of all rows is 6854 .
Output: round_eq { avg { all_rows ; avg attendance } ; 6854 }
select the rows whose team record fuzzily matches to rhein fire . the average of the capacity record of these rows is 56308 .
Output: round_eq { avg { filter_eq { all_rows ; team ; rhein fire } ; capacity } ; 56308 }
select the rows whose attendance record is greater than 59000 . there is only one such row in the table . the date record of this unqiue row is october 30 , 1977 .
Output: and { only { filter_greater { all_rows ; attendance ; 59000 } } ; eq { hop { filter_greater { all_rows ; attendance ; 59000 } ; date } ; october 30 , 1977 } }
select the row whose capacity record of all rows is maximum . the team record of this row is dinamo zagreb .
Output: eq { hop { argmax { all_rows ; capacity } ; team } ; dinamo zagreb }
select the rows whose crystal structure record fuzzily matches to orthorhombic . there is only one such row in the table . the formula record of this unqiue row is yba 2 cu 3 o 7 .
Output: and { only { filter_eq { all_rows ; crystal structure ; orthorhombic } } ; eq { hop { filter_eq { all_rows ; crystal structure ; orthorhombic } ; formula } ; yba 2 cu 3 o 7 } }
select the rows whose lost record is equal to 17 . there is only one such row in the table . the club record of this unqiue row is milford haven rfc .
Output: and { only { filter_eq { all_rows ; lost ; 17 } } ; eq { hop { filter_eq { all_rows ; lost ; 17 } ; club } ; milford haven rfc } }
for the location records of all rows , most of them fuzzily match to reno , nevada .
Output: most_eq { all_rows ; location ; reno , nevada }
select the rows whose date of vacancy record fuzzily matches to 1 april 2008 . there is only one such row in the table . the outgoing manager record of this unqiue row is andy ritchie .
Output: and { only { filter_eq { all_rows ; date of vacancy ; 1 april 2008 } } ; eq { hop { filter_eq { all_rows ; date of vacancy ; 1 april 2008 } ; outgoing manager } ; andy ritchie } }
select the rows whose show record fuzzily matches to dynamo : magician impossible . for the number of viewers records of these rows , most of them are greater than 1000000 .
Output: most_greater { filter_eq { all_rows ; show ; dynamo : magician impossible } ; number of viewers ; 1000000 }
the average of the stages won record of all rows is 1.6 .
Output: round_eq { avg { all_rows ; stages won } ; 1.6 }
select the row whose black knights points record of all rows is maximum . the date record of this row is oct 13 .
Output: eq { hop { argmax { all_rows ; black knights points } ; date } ; oct 13 }
select the rows whose team record fuzzily matches to det . among these rows , select the rows whose goal record fuzzily matches to jiri hudler . the number of such rows is 2 .
Output: eq { count { filter_eq { filter_eq { all_rows ; team ; det } ; goal ; jiri hudler } } ; 2 }
select the row whose barrel length record of all rows is minimum . the colt model no record of this row is le6921sp .
Output: eq { hop { argmin { all_rows ; barrel length } ; colt model no } ; le6921sp }
select the row whose join date record of all rows is 2nd maximum . the school record of this row is lake .
Output: eq { hop { nth_argmax { all_rows ; join date ; 2 } ; school } ; lake }
the sum of the worcs f - c matches record of all rows is 1239 .
Output: round_eq { sum { all_rows ; worcs f - c matches } ; 1239 }
the sum of the poles record of all rows is 20 .
Output: round_eq { sum { all_rows ; poles } ; 20 }
for the average records of all rows , most of them are greater than 1 .
Output: most_greater { all_rows ; average ; 1 }
select the rows whose score record fuzzily matches to 0 . there is only one such row in the table . the visitor record of this unqiue row is los angeles .
Output: and { only { filter_eq { all_rows ; score ; 0 } } ; eq { hop { filter_eq { all_rows ; score ; 0 } ; visitor } ; los angeles } }
select the rows whose competition record fuzzily matches to friendly . the number of such rows is 2 .
Output: eq { count { filter_eq { all_rows ; competition ; friendly } } ; 2 }
select the rows whose place record fuzzily matches to 1st . there is only one such row in the table . the date record of this unqiue row is 7 dec 2008 .
Output: and { only { filter_eq { all_rows ; place ; 1st } } ; eq { hop { filter_eq { all_rows ; place ; 1st } ; date } ; 7 dec 2008 } }
select the rows whose wins record is equal to 0 . the number of such rows is 4 .
Output: eq { count { filter_eq { all_rows ; wins ; 0 } } ; 4 }
select the rows whose first elected record is equal to 1972 . there is only one such row in the table . the incumbent record of this unqiue row is gene taylor .
Output: and { only { filter_eq { all_rows ; first elected ; 1972 } } ; eq { hop { filter_eq { all_rows ; first elected ; 1972 } ; incumbent } ; gene taylor } }
select the rows whose played record is equal to 114 . for the points records of these rows , most of them are greater than 100 .
Output: most_greater { filter_eq { all_rows ; played ; 114 } ; points ; 100 }
select the rows whose team record fuzzily matches to portland trail blazers . take the date record of this row . select the rows whose team record fuzzily matches to detroit pistons . take the date record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; team ; portland trail blazers } ; date } ; hop { filter_eq { all_rows ; team ; detroit pistons } ; date } }
select the row whose points record of all rows is maximum . the name record of this row is natalia linichuk / gennadi karponosov .
Output: eq { hop { argmax { all_rows ; points } ; name } ; natalia linichuk / gennadi karponosov }
select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -6 . the number of such rows is 2 .
Output: eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -6 } } ; 2 }
select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is triton central .
Output: eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; triton central }
select the rows whose date record fuzzily matches to 2005 - 10 - 08 . take the scored record of this row . select the rows whose date record fuzzily matches to 2005 - 02 - 09 . take the scored record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; date ; 2005 - 10 - 08 } ; scored } ; hop { filter_eq { all_rows ; date ; 2005 - 02 - 09 } ; scored } }
select the rows whose points record is greater than 60 . among these rows , select the rows whose tries for record is less than 60 . there is only one such row in the table . the club record of this unqiue row is kidwelly rfc .
Output: and { only { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } } ; eq { hop { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } ; club } ; kidwelly rfc } }
select the rows whose venue record fuzzily matches to tsirion stadium , limassol . take the date record of this row . select the rows whose venue record fuzzily matches to king abdullah stadium , amman . take the date record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; venue ; tsirion stadium , limassol } ; date } ; hop { filter_eq { all_rows ; venue ; king abdullah stadium , amman } ; date } }
the average of the attendance record of all rows is 57797 .
Output: round_eq { avg { all_rows ; attendance } ; 57797 }
for the date made records of all rows , most of them are less than 1900 .
Output: most_less { all_rows ; date made ; 1900 }
for the soap opera records of all rows , most of them fuzzily match to un posto al sole .
Output: most_eq { all_rows ; soap opera ; un posto al sole }
for the shooter records of all rows , most of them do not match to usa .
Output: most_not_eq { all_rows ; shooter ; usa }
select the row whose events record of all rows is maximum . the player record of this row is mark o'meara .
Output: eq { hop { argmax { all_rows ; events } ; player } ; mark o'meara }
select the row whose date record of all rows is 2nd minimum . the home record of this row is warriors .
Output: eq { hop { nth_argmin { all_rows ; date ; 2 } ; home } ; warriors }
select the rows whose version record fuzzily matches to german radio edit . take the length record of this row . select the rows whose version record fuzzily matches to album version . take the length record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; version ; german radio edit } ; length } ; hop { filter_eq { all_rows ; version ; album version } ; length } }
select the row whose years record of all rows is minimum . the player record of this row is jake ford .
Output: eq { hop { argmin { all_rows ; years } ; player } ; jake ford }
the sum of the overall record record of all rows is 31-31 .
Output: round_eq { sum { all_rows ; overall record } ; 31-31 }
for the time records of all rows , most of them are less than 21.0 .
Output: most_less { all_rows ; time ; 21.0 }
select the row whose away team score record of all rows is maximum . the away team record of this row is south melbourne .
Output: eq { hop { argmax { all_rows ; away team score } ; away team } ; south melbourne }
select the rows whose runner - up record fuzzily matches to asc jeanne d'arc . the minimum season record of these rows is 1947 .
Output: eq { min { filter_eq { all_rows ; runner - up ; asc jeanne d'arc } ; season } ; 1947 }
for the high points records of all rows , most of them fuzzily match to r pierce .
Output: most_eq { all_rows ; high points ; r pierce }
select the row whose wins record of all rows is 2nd maximum . the year record of this row is 1994 .
Output: eq { hop { nth_argmax { all_rows ; wins ; 2 } ; year } ; 1994 }
select the row whose original air date ( uk ) record of all rows is 1st maximum . the episode title record of this row is loyalties ii .
Output: eq { hop { nth_argmax { all_rows ; original air date ( uk ) ; 1 } ; episode title } ; loyalties ii }
select the rows whose to par record is less than or equal to -1 . the average of the score record of these rows is 284.2 .
Output: round_eq { avg { filter_less_eq { all_rows ; to par ; -1 } ; score } ; 284.2 }
for the country records of all rows , all of them fuzzily match to italy .
Output: all_eq { all_rows ; country ; italy }
select the rows whose make record fuzzily matches to toyota . the number of such rows is 4 .
Output: eq { count { filter_eq { all_rows ; make ; toyota } } ; 4 }
the sum of the podiums record of all rows is 18 .
Output: round_eq { sum { all_rows ; podiums } ; 18 }
select the row whose points record of all rows is maximum . the game record of this row is 10 .
Output: eq { hop { argmax { all_rows ; points } ; game } ; 10 }
for the award ceremony records of all rows , most of them fuzzily match to drama desk award .
Output: most_eq { all_rows ; award ceremony ; drama desk award }
select the rows whose player record fuzzily matches to jason doig . take the round record of this row . select the rows whose player record fuzzily matches to robert deciantis . take the round record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; player ; jason doig } ; round } ; hop { filter_eq { all_rows ; player ; robert deciantis } ; round } }
select the row whose points record of all rows is maximum . the team 1 record of this row is san lorenzo .
Output: eq { hop { argmax { all_rows ; points } ; team 1 } ; san lorenzo }
select the rows whose country of origin record fuzzily matches to united kingdom . the number of such rows is 4 .
Output: eq { count { filter_eq { all_rows ; country of origin ; united kingdom } } ; 4 }
select the row whose attendance record of all rows is maximum . the date record of this row is september 30 , 1990 .
Output: eq { hop { argmax { all_rows ; attendance } ; date } ; september 30 , 1990 }
for the date records of all rows , most of them fuzzily match to may .
Output: most_eq { all_rows ; date ; may }
select the rows whose result record fuzzily matches to runs . there is only one such row in the table .
Output: only { filter_eq { all_rows ; result ; runs } }
the average of the top - 10 record of all rows is 3.75 .
Output: round_eq { avg { all_rows ; top - 10 } ; 3.75 }
select the rows whose tournament record fuzzily matches to spain . there is only one such row in the table . the date record of this unqiue row is 11 february 2008 .
Output: and { only { filter_eq { all_rows ; tournament ; spain } } ; eq { hop { filter_eq { all_rows ; tournament ; spain } ; date } ; 11 february 2008 } }
select the rows whose attendance record fuzzily matches to gund arena . the sum of the attendance record of these rows is 123371 .
Output: round_eq { sum { filter_eq { all_rows ; attendance ; gund arena } ; attendance } ; 123371 }
for the class records of all rows , most of them fuzzily match to d .
Output: most_eq { all_rows ; class ; d }
select the rows whose nationality record fuzzily matches to united states . there is only one such row in the table . the player record of this unqiue row is ed hospodar .
Output: and { only { filter_eq { all_rows ; nationality ; united states } } ; eq { hop { filter_eq { all_rows ; nationality ; united states } ; player } ; ed hospodar } }
select the rows whose score record fuzzily matches to 8 - . there is only one such row in the table . the date record of this unqiue row is february 22 .
Output: and { only { filter_eq { all_rows ; score ; 8 - } } ; eq { hop { filter_eq { all_rows ; score ; 8 - } ; date } ; february 22 } }
select the rows whose first elected record fuzzily matches to 1878 . the number of such rows is 3 .
Output: eq { count { filter_eq { all_rows ; first elected ; 1878 } } ; 3 }
select the rows whose host city record fuzzily matches to buffalo , new york . take the year record of this row . select the rows whose host city record fuzzily matches to orlando , florida . take the year record of this row . the second record is 1 larger than the first record .
Output: eq { diff { hop { filter_eq { all_rows ; host city ; buffalo , new york } ; year } ; hop { filter_eq { all_rows ; host city ; orlando , florida } ; year } } ; -1 }
select the rows whose planet type record fuzzily matches to ice giant . there is only one such row in the table . the planet record of this unqiue row is neptune .
Output: and { only { filter_eq { all_rows ; planet type ; ice giant } } ; eq { hop { filter_eq { all_rows ; planet type ; ice giant } ; planet } ; neptune } }
select the row whose agg score record of all rows is 7th maximum . the team 1 record of this row is ilisiakos .
Output: eq { hop { nth_argmax { all_rows ; agg score ; 7 } ; team 1 } ; ilisiakos }
the average of the away team score record of all rows is 11.94 .
Output: round_eq { avg { all_rows ; away team score } ; 11.94 }
select the row whose length record of all rows is maximum . the line color record of this row is orange .
Output: eq { hop { argmax { all_rows ; length } ; line color } ; orange }
select the row whose total record of all rows is 2nd maximum . the party record of this row is conservative .
Output: eq { hop { nth_argmax { all_rows ; total ; 2 } ; party } ; conservative }
select the row whose total trade record of all rows is 1st minimum . the country record of this row is iran .
Output: eq { hop { nth_argmin { all_rows ; total trade ; 1 } ; country } ; iran }
the average of the weight ( kg ) record of all rows is 55.625 .
Output: round_eq { avg { all_rows ; weight ( kg ) } ; 55.625 }
select the rows whose jersey number ( s ) record fuzzily matches to , . there is only one such row in the table . the player record of this unqiue row is reggie evans .
Output: and { only { filter_eq { all_rows ; jersey number ( s ) ; , } } ; eq { hop { filter_eq { all_rows ; jersey number ( s ) ; , } ; player } ; reggie evans } }
the average of the points record of all rows is 265 .
Output: round_eq { avg { all_rows ; points } ; 265 }
select the rows whose tournament record fuzzily matches to toronto , canada . take the date record of this row . select the rows whose tournament record fuzzily matches to paris , france . take the date record of this row . the first record is less than the second record . the date record of the first row is 11 august 1997 . the date record of the second row is 22 february 1999 .
Output: and { less { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; hop { filter_eq { all_rows ; tournament ; paris , france } ; date } } ; and { eq { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; 11 august 1997 } ; eq { hop { filter_eq { all_rows ; tournament ; paris , france } ; date } ; 22 february 1999 } } }
for the uk broadcast date records of all rows , all of them are equal to 1996 .
Output: all_eq { all_rows ; uk broadcast date ; 1996 }
select the row whose overall record of all rows is minimum . the name record of this row is art monk .
Output: eq { hop { argmin { all_rows ; overall } ; name } ; art monk }
for the country records of all rows , all of them fuzzily match to soviet union .
Output: all_eq { all_rows ; country ; soviet union }
for the founded records of all rows , most of them are greater than 1950 .
Output: most_greater { all_rows ; founded ; 1950 }
select the rows whose 1st leg record fuzzily matches to 1 - 0 . among these rows , select the rows whose 2nd leg record fuzzily matches to 0-0 . there is only one such row in the table . the team 2 record of this unqiue row is jeunesse esch .
Output: and { only { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } ; team 2 } ; jeunesse esch } }
select the rows whose college record fuzzily matches to north carolina . select the row whose height record of these rows is maximum . the player record of this row is jeff lebo .
Output: eq { hop { argmax { filter_eq { all_rows ; college ; north carolina } ; height } ; player } ; jeff lebo }
select the rows whose dominant religion ( 2002 ) record fuzzily matches to orthodox christianity . the number of such rows is 3 .
Output: eq { count { filter_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity } } ; 3 }
select the rows whose livery record fuzzily matches to br rail blue . the number of such rows is 4 .
Output: eq { count { filter_eq { all_rows ; livery ; br rail blue } } ; 4 }
select the rows whose location attendance record fuzzily matches to wachovia center . there is only one such row in the table . the game record of this unqiue row is 10 .
Output: and { only { filter_eq { all_rows ; location attendance ; wachovia center } } ; eq { hop { filter_eq { all_rows ; location attendance ; wachovia center } ; game } ; 10 } }
select the row whose apparent magnitude record of all rows is maximum . the ngc number record of this row is 5003 .
Output: eq { hop { argmax { all_rows ; apparent magnitude } ; ngc number } ; 5003 }
select the row whose first elected record of all rows is minimum . the incumbent record of this row is jim kolbe .
Output: eq { hop { argmin { all_rows ; first elected } ; incumbent } ; jim kolbe }
the 1st minimum place record of all rows is 1 . the player record of the row with 1st minimum place record is vijay singh .
Output: and { eq { nth_min { all_rows ; place ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; place ; 1 } ; player } ; vijay singh } }
select the rows whose opponent record fuzzily matches to chicago . the number of such rows is 2 .
Output: eq { count { filter_eq { all_rows ; opponent ; chicago } } ; 2 }
for the date records of all rows , all of them fuzzily match to 14 may 1949 .
Output: all_eq { all_rows ; date ; 14 may 1949 }
select the row whose year record of all rows is 1st minimum . the opponent record of this row is south sydney rabbitohs .
Output: eq { hop { nth_argmin { all_rows ; year ; 1 } ; opponent } ; south sydney rabbitohs }
select the row whose total record of all rows is 1st maximum . the nation record of this row is united states ( usa ) .
Output: eq { hop { nth_argmax { all_rows ; total ; 1 } ; nation } ; united states ( usa ) }
select the rows whose ihsaa class record fuzzily matches to aaa . there is only one such row in the table . the school record of this unqiue row is indian creek .
Output: and { only { filter_eq { all_rows ; ihsaa class ; aaa } } ; eq { hop { filter_eq { all_rows ; ihsaa class ; aaa } ; school } ; indian creek } }
for the year records of all rows , most of them are equal to 1986 .
Output: most_eq { all_rows ; year ; 1986 }
for the competition records of all rows , most of them fuzzily match to world cross country championships .
Output: most_eq { all_rows ; competition ; world cross country championships }
select the rows whose club record fuzzily matches to terang . take the wins record of this row . select the rows whose club record fuzzily matches to terang mortlake . take the wins record of this row . the first record is 501 larger than the second record .
Output: eq { diff { hop { filter_eq { all_rows ; club ; terang } ; wins } ; hop { filter_eq { all_rows ; club ; terang mortlake } ; wins } } ; 501 }
select the row whose gore % record of all rows is maximum . the county record of this row is clark .
Output: eq { hop { argmax { all_rows ; gore % } ; county } ; clark }
the average of the pop record of all rows is 38009 .
Output: round_eq { avg { all_rows ; pop } ; 38009 }
select the rows whose points - record is greater than 1200 . for the points + records of these rows , most of them are greater than 1000 .
Output: most_greater { filter_greater { all_rows ; points - ; 1200 } ; points + ; 1000 }
select the rows whose artist record fuzzily matches to bun b . take the number of reviews record of this row . select the rows whose artist record fuzzily matches to black milk . take the number of reviews record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; artist ; bun b } ; number of reviews } ; hop { filter_eq { all_rows ; artist ; black milk } ; number of reviews } }
for the colors records of all rows , most of them fuzzily match to black .
Output: most_eq { all_rows ; colors ; black }
select the rows whose incumbent record fuzzily matches to wilbur mills . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to james william trimble . take the first elected record of this row . the second record is 6 years larger than the first record .
Output: eq { diff { hop { filter_eq { all_rows ; incumbent ; wilbur mills } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; james william trimble } ; first elected } } ; -6 years }
select the rows whose season record fuzzily matches to 2012 . take the podiums record of this row . select the rows whose season record fuzzily matches to 2011 . take the podiums record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; season ; 2012 } ; podiums } ; hop { filter_eq { all_rows ; season ; 2011 } ; podiums } }
select the rows whose location record fuzzily matches to china . the number of such rows is 3 .
Output: eq { count { filter_eq { all_rows ; location ; china } } ; 3 }
for the wins records of all rows , most of them are equal to 0 .
Output: most_eq { all_rows ; wins ; 0 }
select the rows whose opponent record fuzzily matches to yukiya naito . take the round record of this row . select the rows whose opponent record fuzzily matches to maxim tarasov . take the round record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; opponent ; yukiya naito } ; round } ; hop { filter_eq { all_rows ; opponent ; maxim tarasov } ; round } }
select the row whose hosted 4 teams since record of all rows is minimum . the metropolitan area record of this row is detroit , michigan .
Output: eq { hop { argmin { all_rows ; hosted 4 teams since } ; metropolitan area } ; detroit , michigan }
select the rows whose result record fuzzily matches to lost re - election . there is only one such row in the table . the incumbent record of this unqiue row is ralph r eltse .
Output: and { only { filter_eq { all_rows ; result ; lost re - election } } ; eq { hop { filter_eq { all_rows ; result ; lost re - election } ; incumbent } ; ralph r eltse } }
for the high points records of all rows , most of them fuzzily match to j johnson .
Output: most_eq { all_rows ; high points ; j johnson }
select the row whose time record of all rows is 2nd minimum . the athlete record of this row is peter hardcastle .
Output: eq { hop { nth_argmin { all_rows ; time ; 2 } ; athlete } ; peter hardcastle }
select the rows whose date record fuzzily matches to september 8 , 2002 . take the attendance record of this row . select the rows whose date record fuzzily matches to september 15 , 2002 . take the attendance record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; date ; september 8 , 2002 } ; attendance } ; hop { filter_eq { all_rows ; date ; september 15 , 2002 } ; attendance } }
select the rows whose original air date record fuzzily matches to august . among these rows , select the rows whose written by record fuzzily matches to dana calvo . there is only one such row in the table . the title record of this unqiue row is houses of the holy .
Output: and { only { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } } ; eq { hop { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } ; title } ; houses of the holy } }
for the margin of victory records of all rows , most of them are less than 2 .
Output: most_less { all_rows ; margin of victory ; 2 }
the average of the crowd record of all rows is 18729 .
Output: round_eq { avg { all_rows ; crowd } ; 18729 }
select the rows whose tournaments played record is less than 20 . there is only one such row in the table . the year record of this unqiue row is 2002 .
Output: and { only { filter_less { all_rows ; tournaments played ; 20 } } ; eq { hop { filter_less { all_rows ; tournaments played ; 20 } ; year } ; 2002 } }
select the row whose peak record of all rows is 2nd maximum . the english title record of this row is la femme desperado .
Output: eq { hop { nth_argmax { all_rows ; peak ; 2 } ; english title } ; la femme desperado }
for the series records of all rows , most of them fuzzily match to iowa .
Output: most_eq { all_rows ; series ; iowa }
the average of the barrel length record of all rows is 16.5 inches .
Output: round_eq { avg { all_rows ; barrel length } ; 16.5 inches }
for the year records of all rows , all of them fuzzily match to 199 .
Output: all_eq { all_rows ; year ; 199 }
select the rows whose match points record fuzzily matches to 4 - 0 . for the points margin records of these rows , most of them are greater than 30 .
Output: most_greater { filter_eq { all_rows ; match points ; 4 - 0 } ; points margin ; 30 }
the average of the losses record of all rows is 13 .
Output: round_eq { avg { all_rows ; losses } ; 13 }
the average of the capacity record of all rows is 14950 .
Output: round_eq { avg { all_rows ; capacity } ; 14950 }
the average of the finish record of all rows is 4th .
Output: round_eq { avg { all_rows ; finish } ; 4th }
the sum of the capacity ( mw ) record of all rows is 815.6 .
Output: round_eq { sum { all_rows ; capacity ( mw ) } ; 815.6 }
select the row whose length ( m ) record of all rows is 2nd maximum . the name record of this row is berg ter stene .
Output: eq { hop { nth_argmax { all_rows ; length ( m ) ; 2 } ; name } ; berg ter stene }
for the speed records of all rows , most of them are greater than 93 .
Output: most_greater { all_rows ; speed ; 93 }
select the rows whose points record is equal to 67 . the number of such rows is 2 .
Output: eq { count { filter_eq { all_rows ; points ; 67 } } ; 2 }
select the rows whose manufacturer record fuzzily matches to alco - schenectady . the minimum year made record of these rows is 1904 - 1907 .
Output: eq { min { filter_eq { all_rows ; manufacturer ; alco - schenectady } ; year made } ; 1904 - 1907 }
select the rows whose first elected record is equal to 1941 . there is only one such row in the table . the incumbent record of this unqiue row is thomas j lane .
Output: and { only { filter_eq { all_rows ; first elected ; 1941 } } ; eq { hop { filter_eq { all_rows ; first elected ; 1941 } ; incumbent } ; thomas j lane } }
for the score records of all rows , most of them are greater than or equal to 5 .
Output: most_greater_eq { all_rows ; score ; 5 }
select the rows whose height record fuzzily matches to 6 - 4 . the number of such rows is 2 .
Output: eq { count { filter_eq { all_rows ; height ; 6 - 4 } } ; 2 }
select the rows whose location record fuzzily matches to hermanos rodriguez . among these rows , select the rows whose constructor record fuzzily matches to williams - renault . the number of such rows is 2 .
Output: eq { count { filter_eq { filter_eq { all_rows ; location ; hermanos rodriguez } ; constructor ; williams - renault } } ; 2 }
select the rows whose host record fuzzily matches to jack arute . there is only one such row in the table . the year record of this unqiue row is 2008 .
Output: and { only { filter_eq { all_rows ; host ; jack arute } } ; eq { hop { filter_eq { all_rows ; host ; jack arute } ; year } ; 2008 } }
the average of the total record of all rows is 284.5 .
Output: round_eq { avg { all_rows ; total } ; 284.5 }
select the rows whose score record fuzzily matches to 1-1 . there is only one such row in the table . the april record of this unqiue row is 1 .
Output: and { only { filter_eq { all_rows ; score ; 1-1 } } ; eq { hop { filter_eq { all_rows ; score ; 1-1 } ; april } ; 1 } }
select the rows whose team 1 record fuzzily matches to young africans . take the agg record of this row . select the rows whose team 1 record fuzzily matches to secteur 6 . take the agg record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; team 1 ; young africans } ; agg } ; hop { filter_eq { all_rows ; team 1 ; secteur 6 } ; agg } }
select the rows whose 14 july 1998 record fuzzily matches to 28 august 2005 . the number of such rows is 2 .
Output: eq { count { filter_eq { all_rows ; 14 july 1998 ; 28 august 2005 } } ; 2 }
select the rows whose points record is greater than or equal to 55 . among these rows , select the rows whose opponent record fuzzily matches to new york rangers . the number of such rows is 2 .
Output: eq { count { filter_eq { filter_greater_eq { all_rows ; points ; 55 } ; opponent ; new york rangers } } ; 2 }
for the city of license records of all rows , most of them fuzzily match to nuevo laredo .
Output: most_eq { all_rows ; city of license ; nuevo laredo }
select the rows whose date closed record does not match to open . the number of such rows is 6 .
Output: eq { count { filter_not_eq { all_rows ; date closed ; open } } ; 6 }
select the row whose nicky record of all rows is 2nd maximum . the couple record of this row is melinda & fred .
Output: eq { hop { nth_argmax { all_rows ; nicky ; 2 } ; couple } ; melinda & fred }
select the rows whose country record fuzzily matches to estonia . the minimum time record of these rows is 6:27.95 .
Output: eq { min { filter_eq { all_rows ; country ; estonia } ; time } ; 6:27.95 }
the average of the earnings record of all rows is 22046805 .
Output: round_eq { avg { all_rows ; earnings } ; 22046805 }
select the row whose sets lost record of all rows is 2nd maximum . the team record of this row is far eastern university .
Output: eq { hop { nth_argmax { all_rows ; sets lost ; 2 } ; team } ; far eastern university }
for the laps records of all rows , most of them are greater than or equal to 250 .
Output: most_greater_eq { all_rows ; laps ; 250 }
select the rows whose incumbent record fuzzily matches to otto passman . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to t ashton thompson . take the first elected record of this row . the first record is less than the second record .
Output: less { hop { filter_eq { all_rows ; incumbent ; otto passman } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; t ashton thompson } ; first elected } }
select the row whose attendance / g record of all rows is minimum . the season record of this row is 2007 .
Output: eq { hop { argmin { all_rows ; attendance / g } ; season } ; 2007 }
select the rows whose title record fuzzily matches to merchants of brooklyn . take the year record of this row . select the rows whose title record fuzzily matches to crysis warhead . take the year record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; title ; merchants of brooklyn } ; year } ; hop { filter_eq { all_rows ; title ; crysis warhead } ; year } }
the average of the lost record of all rows is 4 .
Output: round_eq { avg { all_rows ; lost } ; 4 }
select the rows whose venue record fuzzily matches to princes park . take the crowd record of this row . select the rows whose venue record fuzzily matches to victoria park . take the crowd record of this row . the first record is 1000 larger than the second record .
Output: eq { diff { hop { filter_eq { all_rows ; venue ; princes park } ; crowd } ; hop { filter_eq { all_rows ; venue ; victoria park } ; crowd } } ; 1000 }
the average of the attendance record of all rows is 17863 .
Output: round_eq { avg { all_rows ; attendance } ; 17863 }
select the row whose average record of all rows is 2nd maximum . the team record of this row is boca juniors .
Output: eq { hop { nth_argmax { all_rows ; average ; 2 } ; team } ; boca juniors }
select the rows whose opponent record fuzzily matches to cincinnati bengals . take the attendance record of this row . select the rows whose opponent record fuzzily matches to houston oilers . take the attendance record of this row . the first record is greater than the second record .
Output: greater { hop { filter_eq { all_rows ; opponent ; cincinnati bengals } ; attendance } ; hop { filter_eq { all_rows ; opponent ; houston oilers } ; attendance } }
the average of the speed record of all rows is 97.34 .
Output: round_eq { avg { all_rows ; speed } ; 97.34 }
select the rows whose age ( as of 1 february 2014 ) record is greater than or equal to 102 years 242 days . the average of the age ( as of 1 february 2014 ) record of these rows is 103 years 28 days .
Output: round_eq { avg { filter_greater_eq { all_rows ; age ( as of 1 february 2014 ) ; 102 years 242 days } ; age ( as of 1 february 2014 ) } ; 103 years 28 days }
the average of the frequency record of all rows is 95.9 mega hertz .
Output: round_eq { avg { all_rows ; frequency } ; 95.9 mega hertz }