niryuu/sni-each-converted huggingface dataset:
greater { hop { filter_eq { all_rows ; scientific name ; chamaeleo calyptratus } ; length ( female ) } ; hop { filter_eq { all_rows ; scientific name ; rhampholeon spectrum } ; length ( female ) } } = true
Output: select the rows whose scientific name record fuzzily matches to chamaeleo calyptratus . take the length  female  record of this row . select the rows whose scientific name record fuzzily matches to rhampholeon spectrum . take the length  female  record of this row . the first record is greater than the second record .
round_eq { avg { all_rows ; apparent magnitude } ; 12.01 } = true
Output: the average of the apparent magnitude record of all rows is 12.01 .
and { eq { nth_min { all_rows ; iso range ; 1 } ; 25 - 400 } ; eq { hop { nth_argmin { all_rows ; iso range ; 1 } ; model } ; aptus - ii 5 } } = true
Output: the 1st minimum iso range record of all rows is 25  400 . the model record of the row with 1st minimum iso range record is aptus  ii 5 .
less { hop { filter_eq { all_rows ; opponent ; mississippi state } ; date } ; hop { filter_eq { all_rows ; opponent ; vanderbilt } ; date } } = true
Output: select the rows whose opponent record fuzzily matches to mississippi state . take the date record of this row . select the rows whose opponent record fuzzily matches to vanderbilt . take the date record of this row . the first record is less than the second record .
eq { hop { nth_argmax { all_rows ; speed ( km / h ) ; 2 } ; vehicle } ; lockheed sr - 71 blackbird } = true
Output: select the row whose speed  km  h  record of all rows is 2nd maximum . the vehicle record of this row is lockheed sr  71 blackbird .
and { only { filter_eq { all_rows ; age at inauguration ; 64years , 67days } } ; eq { hop { filter_eq { all_rows ; age at inauguration ; 64years , 67days } ; date of inauguration } ; 25 july 1977 } } = true
Output: select the rows whose age at inauguration record fuzzily matches to 64years , 67days . there is only one such row in the table . the date of inauguration record of this unqiue row is 25 july 1977 .
eq { hop { argmax { all_rows ; tonnage } ; name } ; northern eagle } = true
Output: select the row whose tonnage record of all rows is maximum . the name record of this row is northern eagle .
eq { hop { nth_argmin { all_rows ; rank ; 3 } ; name } ; matuzalém } = true
Output: select the row whose rank record of all rows is 3rd minimum . the name record of this row is matuzalém .
eq { count { filter_eq { all_rows ; written by ; adam barr } } ; 2 } = true
Output: select the rows whose written by record fuzzily matches to adam barr . the number of such rows is 2 .
greater { hop { filter_eq { all_rows ; missouri vs ; washington u of stl } ; current streak } ; hop { filter_eq { all_rows ; missouri vs ; saint louis } ; current streak } } = true
Output: select the rows whose missouri vs record fuzzily matches to washington u of stl . take the current streak record of this row . select the rows whose missouri vs record fuzzily matches to saint louis . take the current streak record of this row . the first record is greater than the second record .
less { hop { filter_eq { all_rows ; player ; zandro limpot , jr } ; pick } ; hop { filter_eq { all_rows ; player ; richard bachmann } ; pick } } = true
Output: select the rows whose player record fuzzily matches to zandro limpot , jr . take the pick record of this row . select the rows whose player record fuzzily matches to richard bachmann . take the pick record of this row . the first record is less than the second record .
eq { hop { argmax { all_rows ; score } ; opponent } ; boston bruins } = true
Output: select the row whose score record of all rows is maximum . the opponent record of this row is boston bruins .
eq { hop { argmax { all_rows ; agg } ; team 1 } ; canon yaoundé } = true
Output: select the row whose agg record of all rows is maximum . the team 1 record of this row is canon yaoundé .
eq { count { filter_eq { filter_eq { all_rows ; outcome ; runner - up } ; surface ; clay } } ; 5 } = true
Output: select the rows whose outcome record fuzzily matches to runner  up . among these rows , select the rows whose surface record fuzzily matches to clay . the number of such rows is 5 .
round_eq { sum { all_rows ; population } ; 17660 } = true
Output: the sum of the population record of all rows is 17660 .
most_not_eq { all_rows ; kitmaker ; n / a } = true
Output: for the kitmaker records of all rows , most of them do not match to n  a .
eq { hop { nth_argmax { all_rows ; win % ; 2 } ; coach } ; jim larranaga } = true
Output: select the row whose win  record of all rows is 2nd maximum . the coach record of this row is jim larranaga .
eq { hop { argmax { all_rows ; location attendance } ; high assists } ; mike james ( 7 ) } = true
Output: select the row whose location attendance record of all rows is maximum . the high assists record of this row is mike james  7  .
less { hop { filter_eq { all_rows ; name ; mike logan } ; round } ; hop { filter_eq { all_rows ; name ; jon hesse } ; round } } = true
Output: select the rows whose name record fuzzily matches to mike logan . take the round record of this row . select the rows whose name record fuzzily matches to jon hesse . take the round record of this row . the first record is less than the second record .
and { eq { min { all_rows ; closed } ; 1983 } ; eq { hop { argmin { all_rows ; closed } ; station } ; fairmount avenue } } = true
Output: the minimum closed record of all rows is 1983 . the station record of the row with superlative closed record is fairmount avenue .
most_greater_eq { all_rows ; to par ; 9 } = true
Output: for the to par records of all rows , most of them are greater than or equal to 9 .
eq { count { filter_eq { all_rows ; margin of victory ; 1 stroke } } ; 2 } = true
Output: select the rows whose margin of victory record fuzzily matches to 1 stroke . the number of such rows is 2 .
eq { hop { nth_argmax { all_rows ; jerseys ; 4 } ; country } ; italy } = true
Output: select the row whose jerseys record of all rows is 4th maximum . the country record of this row is italy .
greater { hop { filter_eq { all_rows ; settlement ; gardinovci } ; population ( 2011 ) } ; hop { filter_eq { all_rows ; settlement ; lok } ; population ( 2011 ) } } = true
Output: select the rows whose settlement record fuzzily matches to gardinovci . take the population  2011  record of this row . select the rows whose settlement record fuzzily matches to lok . take the population  2011  record of this row . the first record is greater than the second record .
round_eq { avg { all_rows ; react } ; 0.161 } = true
Output: the average of the react record of all rows is 0.161 .
eq { hop { nth_argmax { all_rows ; total ; 2 } ; province } ; chonburi } = true
Output: select the row whose total record of all rows is 2nd maximum . the province record of this row is chonburi .
greater { hop { filter_eq { all_rows ; romaji title ; yama onna kabe onna } ; episodes } ; hop { filter_eq { all_rows ; romaji title ; jotei } ; episodes } } = true
Output: select the rows whose romaji title record fuzzily matches to yama onna kabe onna . take the episodes record of this row . select the rows whose romaji title record fuzzily matches to jotei . take the episodes record of this row . the first record is greater than the second record .
eq { hop { argmax { all_rows ; vuelta wins } ; country } ; spain } = true
Output: select the row whose vuelta wins record of all rows is maximum . the country record of this row is spain .
eq { count { filter_eq { filter_eq { all_rows ; axle arrangement ; 2 ′ b n2v } ; axle arrangement ; 2 ′ b n2v } } ; 3 } = true
Output: select the rows whose axle arrangement record fuzzily matches to 2 ′ b n2v . among these rows , select the rows whose axle arrangement record fuzzily matches to 2 ′ b n2v . the number of such rows is 3 .
round_eq { avg { all_rows ; population ( 2005 ) } ; 801.29 } = true
Output: the average of the population  2005  record of all rows is 801.29 .
round_eq { avg { all_rows ; games } ; 70 } = true
Output: the average of the games record of all rows is 70 .
and { only { filter_eq { all_rows ; 2002 - 03 ; 5849 } } ; eq { hop { filter_eq { all_rows ; 2002 - 03 ; 5849 } ; commodity } ; cattle and calves } } = true
Output: select the rows whose 2002  03 record is equal to 5849 . there is only one such row in the table . the commodity record of this unqiue row is cattle and calves .
eq { hop { nth_argmax { all_rows ; runs ; 2 } ; player } ; dene hills } = true
Output: select the row whose runs record of all rows is 2nd maximum . the player record of this row is dene hills .
round_eq { avg { all_rows ; total } ; 3 } = true
Output: the average of the total record of all rows is 3 .
most_eq { all_rows ; surface ; dirt } = true
Output: for the surface records of all rows , most of them fuzzily match to dirt .
eq { hop { nth_argmax { filter_eq { all_rows ; junctions ; sh 359 us 59 } ; route name ; 1 } ; termini } ; aguilares , texas us 59 } = true
Output: select the rows whose junctions record fuzzily matches to sh 359 us 59 . select the row whose route name record of these rows is 1st maximum . the termini record of this row is aguilares , texas us 59 .
and { only { filter_eq { all_rows ; position ; fb } } ; eq { hop { filter_eq { all_rows ; position ; fb } ; name } ; bob briggs } } = true
Output: select the rows whose position record fuzzily matches to fb . there is only one such row in the table . the name record of this unqiue row is bob briggs .
round_eq { sum { filter_eq { all_rows ; location attendance ; arizona veterans memorial coliseum } ; score } ; 200 } = true
Output: select the rows whose location attendance record fuzzily matches to arizona veterans memorial coliseum . the sum of the score record of these rows is 200 .
eq { count { filter_all { all_rows ; performer 2 } } ; 6 } = true
Output: select the rows whose performer 2 record is arbitrary . the number of such rows is 6 .
and { only { filter_eq { all_rows ; ceased to be queen ; divorced } } ; eq { hop { filter_eq { all_rows ; ceased to be queen ; divorced } ; father } ; leopold vi , duke of austria } } = true
Output: select the rows whose ceased to be queen record fuzzily matches to divorced . there is only one such row in the table . the father record of this unqiue row is leopold vi , duke of austria .
round_eq { avg { all_rows ; p1 diameter ( mm ) } ; 13.425 } = true
Output: the average of the p1 diameter  mm  record of all rows is 13.425 .
and { only { filter_greater { all_rows ; score ; 1 } } ; eq { hop { filter_greater { all_rows ; score ; 1 } ; venue } ; hong kong , china } } = true
Output: select the rows whose score record is greater than 1 . there is only one such row in the table . the venue record of this unqiue row is hong kong , china .
round_eq { avg { filter_less { all_rows ; home team score ; 10 } ; crowd } ; 16600 } = true
Output: select the rows whose home team score record is less than 10 . the average of the crowd record of these rows is 16600 .
and { only { filter_eq { all_rows ; gp - gs ; 14 } } ; eq { hop { filter_eq { all_rows ; gp - gs ; 14 } ; season } ; 2009 } } = true
Output: select the rows whose gp  gs record is equal to 14 . there is only one such row in the table . the season record of this unqiue row is 2009 .
eq { count { filter_eq { all_rows ; date ; december } } ; 3 } = true
Output: select the rows whose date record fuzzily matches to december . the number of such rows is 3 .
less { hop { filter_eq { all_rows ; name ; dave farmer } ; round } ; hop { filter_eq { all_rows ; name ; don parrish } ; round } } = true
Output: select the rows whose name record fuzzily matches to dave farmer . take the round record of this row . select the rows whose name record fuzzily matches to don parrish . take the round record of this row . the first record is less than the second record .
and { only { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } } ; eq { hop { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } ; country } ; algeria } } = true
Output: select the rows whose region record fuzzily matches to africa . among these rows , select the rows whose joined opec record is equal to 1969 . there is only one such row in the table . the country record of this unqiue row is algeria .
eq { count { filter_eq { all_rows ; position ; wide receiver } } ; 2 } = true
Output: select the rows whose position record fuzzily matches to wide receiver . the number of such rows is 2 .
round_eq { sum { all_rows ; points } ; 612 } = true
Output: the sum of the points record of all rows is 612 .
round_eq { avg { all_rows ; crowd } ; 15760 } = true
Output: the average of the crowd record of all rows is 15760 .
and { only { filter_eq { all_rows ; score ; 1-1 } } ; eq { hop { filter_eq { all_rows ; score ; 1-1 } ; date } ; march 21 , 2007 } } = true
Output: select the rows whose score record fuzzily matches to 11 . there is only one such row in the table . the date record of this unqiue row is march 21 , 2007 .
eq { count { filter_eq { all_rows ; president ; josiah bartlet } } ; 5 } = true
Output: select the rows whose president record fuzzily matches to josiah bartlet . the number of such rows is 5 .
most_eq { all_rows ; start datum ; wgs84 } = true
Output: for the start datum records of all rows , most of them fuzzily match to wgs84 .
most_eq { all_rows ; mens singles ; lee chong wei } = true
Output: for the mens singles records of all rows , most of them fuzzily match to lee chong wei .
and { only { filter_eq { all_rows ; segment b ; canned tomatoes } } ; eq { hop { filter_eq { all_rows ; segment b ; canned tomatoes } ; episode } ; 238 } } = true
Output: select the rows whose segment b record fuzzily matches to canned tomatoes . there is only one such row in the table . the episode record of this unqiue row is 238 .
round_eq { sum { all_rows ; winner 's share } ; 147500 } = true
Output: the sum of the winner s share record of all rows is 147500 .
and { only { filter_eq { all_rows ; director ; neema barnette } } ; eq { hop { filter_eq { all_rows ; director ; neema barnette } ; original air date } ; october 21 , 2003 } } = true
Output: select the rows whose director record fuzzily matches to neema barnette . there is only one such row in the table . the original air date record of this unqiue row is october 21 , 2003 .
round_eq { avg { all_rows ; 1 - year peak } ; 2869 } = true
Output: the average of the 1  year peak record of all rows is 2869 .
and { only { filter_eq { all_rows ; ladder position ; 9 / 16 } } ; eq { hop { filter_eq { all_rows ; ladder position ; 9 / 16 } ; competition } ; 2013 nrl season } } = true
Output: select the rows whose ladder position record fuzzily matches to 9  16 . there is only one such row in the table . the competition record of this unqiue row is 2013 nrl season .
round_eq { avg { all_rows ; gold } ; 0.4375 } = true
Output: the average of the gold record of all rows is 0.4375 .
eq { count { filter_greater_eq { all_rows ; year ; 1990 } } ; 4 } = true
Output: select the rows whose year record is greater than or equal to 1990 . the number of such rows is 4 .
eq { hop { nth_argmin { all_rows ; date ; 2 } ; score } ; 3 - 6 , 2 - 6 } = true
Output: select the row whose date record of all rows is 2nd minimum . the score record of this row is 3  6 , 2  6 .
most_eq { all_rows ; tyres ; g } = true
Output: for the tyres records of all rows , most of them fuzzily match to g .
and { only { filter_not_eq { all_rows ; nationality ; united states } } ; eq { hop { filter_not_eq { all_rows ; nationality ; united states } ; player } ; aleksandar radojeviä ‡ } } = true
Output: select the rows whose nationality record does not match to united states . there is only one such row in the table . the player record of this unqiue row is aleksandar radojeviä ‡ .
less { hop { filter_eq { all_rows ; city of license ; lyons falls , ny } ; frequency mhz } ; hop { filter_eq { all_rows ; city of license ; norwich , ny } ; frequency mhz } } = true
Output: select the rows whose city of license record fuzzily matches to lyons falls , ny . take the frequency mhz record of this row . select the rows whose city of license record fuzzily matches to norwich , ny . take the frequency mhz record of this row . the first record is less than the second record .
eq { count { filter_eq { all_rows ; position ; m } } ; 4 } = true
Output: select the rows whose position record fuzzily matches to m . the number of such rows is 4 .
round_eq { sum { all_rows ; ends won } ; 516 } = true
Output: the sum of the ends won record of all rows is 516 .
eq { hop { nth_argmax { all_rows ; goals against ; 2 } ; club } ; baracaldo ah } = true
Output: select the row whose goals against record of all rows is 2nd maximum . the club record of this row is baracaldo ah .
eq { count { filter_all { all_rows ; school } } ; 8 } = true
Output: select the rows whose school record is arbitrary . the number of such rows is 8 .
greater { hop { filter_eq { all_rows ; song title ; he thinks i still care } ; length } ; hop { filter_eq { all_rows ; song title ; the pain of loving you } ; length } } = true
Output: select the rows whose song title record fuzzily matches to he thinks i still care . take the length record of this row . select the rows whose song title record fuzzily matches to the pain of loving you . take the length record of this row . the first record is greater than the second record .
less { hop { filter_eq { all_rows ; team ; aermacchi } ; year } ; hop { filter_eq { all_rows ; team ; harley davidson } ; year } } = true
Output: select the rows whose team record fuzzily matches to aermacchi . take the year record of this row . select the rows whose team record fuzzily matches to harley davidson . take the year record of this row . the first record is less than the second record .
eq { count { filter_less_eq { all_rows ; start ; 20 } } ; 5 } = true
Output: select the rows whose start record is less than or equal to 20 . the number of such rows is 5 .
round_eq { sum { all_rows ; attendance } ; 741290 } = true
Output: the sum of the attendance record of all rows is 741290 .
round_eq { avg { all_rows ; gold } ; 15 } = true
Output: the average of the gold record of all rows is 15 .
round_eq { avg { all_rows ; crowd } ; 14000 } = true
Output: the average of the crowd record of all rows is 14000 .
greater { hop { filter_eq { all_rows ; ride ; flight deck } ; rating } ; hop { filter_eq { all_rows ; ride ; woodstock express } ; rating } } = true
Output: select the rows whose ride record fuzzily matches to flight deck . take the rating record of this row . select the rows whose ride record fuzzily matches to woodstock express . take the rating record of this row . the first record is greater than the second record .
eq { count { filter_eq { all_rows ; first elected ; 1944 } } ; 2 } = true
Output: select the rows whose first elected record is equal to 1944 . the number of such rows is 2 .
eq { hop { argmax { all_rows ; total points } ; player } ; carlos yates } = true
Output: select the row whose total points record of all rows is maximum . the player record of this row is carlos yates .
eq { hop { argmax { all_rows ; votes } ; election } ; 1990 } = true
Output: select the row whose votes record of all rows is maximum . the election record of this row is 1990 .
less { hop { filter_eq { all_rows ; name ; nicola cassio } ; 100 m } ; hop { filter_eq { all_rows ; name ; amaury leveaux } ; 100 m } } = true
Output: select the rows whose name record fuzzily matches to nicola cassio . take the 100 m record of this row . select the rows whose name record fuzzily matches to amaury leveaux . take the 100 m record of this row . the first record is less than the second record .
all_eq { all_rows ; date ; 9 june 1928 } = true
Output: for the date records of all rows , all of them fuzzily match to 9 june 1928 .
eq { count { filter_greater { filter_greater { all_rows ; place ; 1 } ; points jury ; 30 } } ; 4 } = true
Output: select the rows whose place record is greater than 1 . among these rows , select the rows whose points jury record is greater than 30 . the number of such rows is 4 .
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
Output: 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 .
round_eq { avg { all_rows ; gold } ; 2.67 } = true
Output: the average of the gold record of all rows is 2.67 .
and { only { filter_eq { all_rows ; result ; 35-34 } } ; eq { hop { filter_eq { all_rows ; result ; 35-34 } ; date } ; november 15 } } = true
Output: select the rows whose result record fuzzily matches to 3534 . there is only one such row in the table . the date record of this unqiue row is november 15 .
most_eq { all_rows ; date ; may } = true
Output: for the date records of all rows , most of them fuzzily match to may .
round_eq { avg { all_rows ; try bonus } ; 5 } = true
Output: the average of the try bonus record of all rows is 5 .
eq { count { filter_less { filter_less { all_rows ; area ( km square ) ; 100 } ; population 2000 census ; 100000 } } ; 2 } = true
Output: select the rows whose area  km square  record is less than 100 . among these rows , select the rows whose population 2000 census record is less than 100000 . the number of such rows is 2 .
less { hop { filter_eq { all_rows ; track ; mono 45upm - romance adieu ( weltklang remix ) } ; year } ; hop { filter_eq { all_rows ; track ; kinder aus asbest - hey engel ( weltklang remix ) } ; year } } = true
Output: select the rows whose track record fuzzily matches to mono 45upm  romance adieu  weltklang remix  . take the year record of this row . select the rows whose track record fuzzily matches to kinder aus asbest  hey engel  weltklang remix  . take the year record of this row . the first record is less than the second record .
eq { count { filter_eq { all_rows ; manner of departure ; sacked } } ; 4 } = true
Output: select the rows whose manner of departure record fuzzily matches to sacked . the number of such rows is 4 .
most_greater { all_rows ; population ( 2008 ) ; 100000 } = true
Output: for the population  2008  records of all rows , most of them are greater than 100000 .
eq { count { filter_eq { all_rows ; result ; w } } ; 2 } = true
Output: select the rows whose result record fuzzily matches to w . the number of such rows is 2 .
round_eq { avg { all_rows ; size } ; 408.4 } = true
Output: the average of the size record of all rows is 408.4 .
round_eq { avg { all_rows ; balls } ; 670 } = true
Output: the average of the balls record of all rows is 670 .
and { only { filter_eq { all_rows ; venue ; dairy farmers stadium } } ; eq { hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent } ; north queensland cowboys } } = true
Output: select the rows whose venue record fuzzily matches to dairy farmers stadium . there is only one such row in the table . the opponent record of this unqiue row is north queensland cowboys .
eq { hop { nth_argmin { all_rows ; attendance ; 2 } ; date } ; december 22 } = true
Output: select the row whose attendance record of all rows is 2nd minimum . the date record of this row is december 22 .
and { eq { max { all_rows ; margin } ; 9 strokes } ; and { eq { hop { argmax { all_rows ; margin } ; year } ; 4 . 1965 } ; eq { hop { argmax { all_rows ; margin } ; championship } ; masters tournament ( 2 ) } } } = true
Output: the maximum margin record of all rows is 9 strokes . the year record of the row with superlative margin record is 4 . 1965 . the championship record of the row with superlative margin record is masters tournament  2  .
eq { hop { nth_argmin { all_rows ; date ; 1 } ; race name } ; datsun twin 200 } = true
Output: select the row whose date record of all rows is 1st minimum . the race name record of this row is datsun twin 200 .
most_eq { all_rows ; platelet count ; unaffected } = true
Output: for the platelet count records of all rows , most of them fuzzily match to unaffected .
greater { hop { filter_eq { all_rows ; artist ; guide } ; points } ; hop { filter_eq { all_rows ; artist ; balsam boys } ; points } } = true
Output: select the rows whose artist record fuzzily matches to guide . take the points record of this row . select the rows whose artist record fuzzily matches to balsam boys . take the points record of this row . the first record is greater than the second record .
greater { hop { filter_eq { all_rows ; date ; october 31 } ; score } ; hop { filter_eq { all_rows ; date ; october 29 } ; score } } = true
Output: select the rows whose date record fuzzily matches to october 31 . take the score record of this row . select the rows whose date record fuzzily matches to october 29 . take the score record of this row . the first record is greater than the second record .
and { only { filter_eq { all_rows ; time / retired ; accident } } ; eq { hop { filter_eq { all_rows ; time / retired ; accident } ; driver } ; nino farina } } = true
Output: select the rows whose time  retired record fuzzily matches to accident . there is only one such row in the table . the driver record of this unqiue row is nino farina .
and { only { filter_eq { all_rows ; location ( city , state ) ; michigan } } ; eq { hop { filter_eq { all_rows ; location ( city , state ) ; michigan } ; yard name } ; great lakes engineering co } } = true
Output: select the rows whose location  city , state  record fuzzily matches to michigan . there is only one such row in the table . the yard name record of this unqiue row is great lakes engineering co .
greater { hop { filter_eq { all_rows ; deceased spouse ; jessica mitford } ; length of marriage } ; hop { filter_eq { all_rows ; deceased spouse ; helen palmer geisel } ; length of marriage } } = true
Output: select the rows whose deceased spouse record fuzzily matches to jessica mitford . take the length of marriage record of this row . select the rows whose deceased spouse record fuzzily matches to helen palmer geisel . take the length of marriage record of this row . the first record is greater than the second record .
and { only { filter_eq { all_rows ; location attendance ; target center } } ; eq { hop { filter_eq { all_rows ; location attendance ; target center } ; date } ; march 3 } } = true
Output: select the rows whose location attendance record fuzzily matches to target center . there is only one such row in the table . the date record of this unqiue row is march 3 .
eq { hop { nth_argmax { all_rows ; goals for ; 2 } ; team } ; blackpool mechanics } = true
Output: select the row whose goals for record of all rows is 2nd maximum . the team record of this row is blackpool mechanics .
and { only { filter_eq { all_rows ; location ; bell centre } } ; eq { hop { filter_eq { all_rows ; location ; bell centre } ; date } ; january 2 } } = true
Output: select the rows whose location record fuzzily matches to bell centre . there is only one such row in the table . the date record of this unqiue row is january 2 .
eq { hop { argmax { all_rows ; wins } ; year } ; 1988 } = true
Output: select the row whose wins record of all rows is maximum . the year record of this row is 1988 .
round_eq { sum { all_rows ; attendance } ; 197707 } = true
Output: the sum of the attendance record of all rows is 197707 .
less { hop { filter_eq { all_rows ; opponent ; minnesota timberwolves } ; score } ; hop { filter_eq { all_rows ; opponent ; indiana pacers } ; score } } = true
Output: select the rows whose opponent record fuzzily matches to minnesota timberwolves . take the score record of this row . select the rows whose opponent record fuzzily matches to indiana pacers . take the score record of this row . the first record is less than the second record .
round_eq { avg { all_rows ; total } ; 147.4 } = true
Output: the average of the total record of all rows is 147.4 .
eq { hop { argmin { all_rows ; height } ; player } ; mithat demirel } = true
Output: select the row whose height record of all rows is minimum . the player record of this row is mithat demirel .
greater { hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 25 } ; hop { filter_eq { all_rows ; tournament ; pga championship } ; top - 25 } } = true
Output: select the rows whose tournament record fuzzily matches to masters tournament . take the top  25 record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the top  25 record of this row . the first record is greater than the second record .
most_less { all_rows ; total ; 10 } = true
Output: for the total records of all rows , most of them are less than 10 .
eq { count { filter_eq { filter_eq { all_rows ; venue ; amman } ; result ; win } } ; 6 } = true
Output: select the rows whose venue record fuzzily matches to amman . among these rows , select the rows whose result record fuzzily matches to win . the number of such rows is 6 .
eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; march 19 } = true
Output: select the row whose attendance record of all rows is 1st maximum . the date record of this row is march 19 .
only { filter_eq { all_rows ; method ; tko ( liver punch ) } } = true
Output: select the rows whose method record fuzzily matches to tko  liver punch  . there is only one such row in the table .
most_greater { all_rows ; score ; 350 } = true
Output: for the score records of all rows , most of them are greater than 350 .
eq { count { filter_eq { all_rows ; candidate ; kalevi kivistö } } ; 2 } = true
Output: select the rows whose candidate record fuzzily matches to kalevi kivistö . the number of such rows is 2 .
round_eq { avg { all_rows ; weeks at 1 } ; 4.8 } = true
Output: the average of the weeks at 1 record of all rows is 4.8 .
greater { hop { filter_eq { all_rows ; location ; cleveland , tennessee } ; enrollment } ; hop { filter_eq { all_rows ; location ; birmingham , alabama } ; enrollment } } = true
Output: select the rows whose location record fuzzily matches to cleveland , tennessee . take the enrollment record of this row . select the rows whose location record fuzzily matches to birmingham , alabama . take the enrollment record of this row . the first record is greater than the second record .
round_eq { sum { all_rows ; in service } ; 35 } = true
Output: the sum of the in service record of all rows is 35 .
most_eq { all_rows ; original air date ; july } = true
Output: for the original air date records of all rows , most of them fuzzily match to july .
eq { hop { nth_argmax { filter_eq { all_rows ; original air date ; june } ; us viewers ( million ) ; 1 } ; title } ; begin the begin } = true
Output: select the rows whose original air date record fuzzily matches to june . select the row whose us viewers  million  record of these rows is 1st maximum . the title record of this row is begin the begin .
eq { hop { argmax { all_rows ; margin } ; year } ; 1980 } = true
Output: select the row whose margin record of all rows is maximum . the year record of this row is 1980 .
and { eq { diff { hop { filter_eq { all_rows ; player ; linden rowat ( g ) } ; round } ; hop { filter_eq { all_rows ; player ; dwight king ( c ) } ; round } } ; 1 } ; and { eq { hop { filter_eq { all_rows ; player ; linden rowat ( g ) } ; round } ; 5 } ; eq { hop { filter_eq { all_rows ; player ; dwight king ( c ) } ; round } ; 4 } } } = true
Output: select the rows whose player record fuzzily matches to linden rowat  g  . take the round record of this row . select the rows whose player record fuzzily matches to dwight king  c  . take the round record of this row . the first record is 1 larger than the second record . the round record of the first row is 5 . the round record of the second row is 4 .
eq { hop { nth_argmax { all_rows ; home team score ; 2 } ; home team } ; hawthorn } = true
Output: select the row whose home team score record of all rows is 2nd maximum . the home team record of this row is hawthorn .
eq { hop { nth_argmin { filter_eq { all_rows ; builder ; denny , dunbarton } ; laid down ; 1 } ; name } ; sutlej } = true
Output: select the rows whose builder record fuzzily matches to denny , dunbarton . select the row whose laid down record of these rows is 1st minimum . the name record of this row is sutlej .
greater { hop { filter_eq { all_rows ; game ; 63 } ; points } ; hop { filter_eq { all_rows ; game ; 57 } ; points } } = true
Output: select the rows whose game record fuzzily matches to 63 . take the points record of this row . select the rows whose game record fuzzily matches to 57 . take the points record of this row . the first record is greater than the second record .
eq { count { filter_eq { all_rows ; traction type ; petrol } } ; 2 } = true
Output: select the rows whose traction type record fuzzily matches to petrol . the number of such rows is 2 .
round_eq { avg { all_rows ; score } ; 97.3 } = true
Output: the average of the score record of all rows is 97.3 .
eq { count { filter_eq { all_rows ; drawn ; 1 } } ; 4 } = true
Output: select the rows whose drawn record is equal to 1 . the number of such rows is 4 .
most_greater { all_rows ; us viewers ( million ) ; 7 } = true
Output: for the us viewers  million  records of all rows , most of them are greater than 7 .
all_eq { filter_eq { all_rows ; game site ; rheinenergiestadion } ; kickoff ; 6:00 pm } = true
Output: select the rows whose game site record fuzzily matches to rheinenergiestadion . for the kickoff records of these rows , all of them fuzzily match to 6:00 pm .
eq { hop { nth_argmax { all_rows ; against ; 2 } ; opposing team } ; litoral region xv } = true
Output: select the row whose against record of all rows is 2nd maximum . the opposing team record of this row is litoral region xv .
most_eq { filter_eq { all_rows ; position ; left wing } ; nationality ; canada } = true
Output: select the rows whose position record fuzzily matches to left wing . for the nationality records of these rows , most of them fuzzily match to canada .
most_eq { all_rows ; lineup ; 90 . start } = true
Output: for the lineup records of all rows , most of them fuzzily match to 90 . start .
all_eq { all_rows ; date ; 31 july 1954 } = true
Output: for the date records of all rows , all of them fuzzily match to 31 july 1954 .
eq { hop { nth_argmin { all_rows ; year ; 1 } ; opponent } ; south sydney rabbitohs } = true
Output: select the row whose year record of all rows is 1st minimum . the opponent record of this row is south sydney rabbitohs .
round_eq { avg { all_rows ; lost } ; 9.7 } = true
Output: the average of the lost record of all rows is 9.7 .
eq { diff { hop { filter_eq { all_rows ; outgoing manager ; mesut bakkal } ; date of vacancy } ; hop { filter_eq { all_rows ; outgoing manager ; samet aybaba } ; date of vacancy } } ; -1 day } = true
Output: select the rows whose outgoing manager record fuzzily matches to mesut bakkal . take the date of vacancy record of this row . select the rows whose outgoing manager record fuzzily matches to samet aybaba . take the date of vacancy record of this row . the second record is 1 day larger than the first record .
eq { count { filter_eq { filter_eq { all_rows ; competition ; uefa cup } ; result ; draw } } ; 2 } = true
Output: select the rows whose competition record fuzzily matches to uefa cup . among these rows , select the rows whose result record fuzzily matches to draw . the number of such rows is 2 .
eq { min { filter_eq { all_rows ; featuring ; tractators } ; released } ; february 2010 } = true
Output: select the rows whose featuring record fuzzily matches to tractators . the minimum released record of these rows is february 2010 .
greater { hop { filter_eq { all_rows ; administrative district ; mullaitivu } ; land area ( km 2 ) } ; hop { filter_eq { all_rows ; administrative district ; mannar } ; land area ( km 2 ) } } = true
Output: select the rows whose administrative district record fuzzily matches to mullaitivu . take the land area  km 2  record of this row . select the rows whose administrative district record fuzzily matches to mannar . take the land area  km 2  record of this row . the first record is greater than the second record .
most_eq { all_rows ; score ; 68 } = true
Output: for the score records of all rows , most of them are equal to 68 .
and { only { filter_eq { all_rows ; ignition timing ; 180 - 540 } } ; eq { hop { filter_eq { all_rows ; ignition timing ; 180 - 540 } ; engine } ; i4 ' long bang ' } } = true
Output: select the rows whose ignition timing record fuzzily matches to 180  540 . there is only one such row in the table . the engine record of this unqiue row is i4  long bang  .
eq { hop { nth_argmax { all_rows ; year ; 2 } ; year } ; 2012 } = true
Output: select the row whose year record of all rows is 2nd maximum . the year record of this row is 2012 .
eq { hop { argmax { filter_eq { all_rows ; season ; 2002 } ; points } ; series } ; british formula three } = true
Output: select the rows whose season record is equal to 2002 . select the row whose points record of these rows is maximum . the series record of this row is british formula three .
and { only { filter_eq { all_rows ; team ; walker racing } } ; eq { hop { filter_eq { all_rows ; team ; walker racing } ; driver } ; mario haberfeld } } = true
Output: select the rows whose team record fuzzily matches to walker racing . there is only one such row in the table . the driver record of this unqiue row is mario haberfeld .
eq { count { filter_eq { all_rows ; power ( kw ) ; 5 kw } } ; 12 } = true
Output: select the rows whose power  kw  record fuzzily matches to 5 kw . the number of such rows is 12 .
all_eq { all_rows ; score ; 1 } = true
Output: for the score records of all rows , all of them fuzzily match to 1 .
eq { hop { argmin { all_rows ; built } ; name } ; humpback } = true
Output: select the row whose built record of all rows is minimum . the name record of this row is humpback .
round_eq { avg { all_rows ; attendance } ; 19119 } = true
Output: the average of the attendance record of all rows is 19119 .
most_eq { all_rows ; extra ; 4x400 m relay } = true
Output: for the extra records of all rows , most of them fuzzily match to 4x400 m relay .
greater { hop { filter_eq { all_rows ; team 1 ; kastoria } ; agg score } ; hop { filter_eq { all_rows ; team 1 ; ilisiakos } ; agg score } } = true
Output: select the rows whose team 1 record fuzzily matches to kastoria . take the agg score record of this row . select the rows whose team 1 record fuzzily matches to ilisiakos . take the agg score record of this row . the first record is greater than the second record .
most_eq { all_rows ; country ; united kingdom } = true
Output: for the country records of all rows , most of them fuzzily match to united kingdom .
and { only { filter_eq { all_rows ; order ; cardinal - bishop } } ; eq { hop { filter_eq { all_rows ; order ; cardinal - bishop } ; elector } ; francesco moricotti prignani } } = true
Output: select the rows whose order record fuzzily matches to cardinal  bishop . there is only one such row in the table . the elector record of this unqiue row is francesco moricotti prignani .
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
Output: 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 .
most_less { all_rows ; 2nd run ; 40 } = true
Output: for the 2nd run records of all rows , most of them are less than 40 .
and { only { filter_eq { all_rows ; method ; draw } } ; eq { hop { filter_eq { all_rows ; method ; draw } ; opponent } ; cj fernandes } } = true
Output: select the rows whose method record fuzzily matches to draw . there is only one such row in the table . the opponent record of this unqiue row is cj fernandes .
eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; d wyatt aiken } = true
Output: select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is d wyatt aiken .
eq { hop { nth_argmax { all_rows ; quantity ; 2 } ; class } ; pt 2 / 3 } = true
Output: select the row whose quantity record of all rows is 2nd maximum . the class record of this row is pt 2  3 .
greater { hop { filter_eq { all_rows ; municipality ; tecate } ; area ( km2 ) } ; hop { filter_eq { all_rows ; municipality ; tijuana } ; area ( km2 ) } } = true
Output: select the rows whose municipality record fuzzily matches to tecate . take the area  km2  record of this row . select the rows whose municipality record fuzzily matches to tijuana . take the area  km2  record of this row . the first record is greater than the second record .
round_eq { avg { all_rows ; runs } ; 5390 } = true
Output: the average of the runs record of all rows is 5390 .
eq { hop { argmax { all_rows ; isolation } ; mountain peak } ; mount rainier } = true
Output: select the row whose isolation record of all rows is maximum . the mountain peak record of this row is mount rainier .
round_eq { sum { filter_eq { all_rows ; opponent ; notre dame } ; total offense } ; 948 } = true
Output: select the rows whose opponent record fuzzily matches to notre dame . the sum of the total offense record of these rows is 948 .
eq { hop { argmax { all_rows ; points } ; driver / passenger } ; daniãl willemsen / sven verbrugge 1 } = true
Output: select the row whose points record of all rows is maximum . the driver  passenger record of this row is daniãl willemsen  sven verbrugge 1 .
eq { hop { nth_argmax { all_rows ; total ; 1 } ; player } ; hal sutton } = true
Output: select the row whose total record of all rows is 1st maximum . the player record of this row is hal sutton .
most_less_eq { all_rows ; result ; 20th } = true
Output: for the result records of all rows , most of them are less than or equal to 20th .
and { eq { hop { argmin { all_rows ; distance } ; city 1 } ; são paulo } ; eq { hop { argmin { all_rows ; distance } ; city 2 } ; rio de janeiro } } = true
Output: select the row whose distance record of all rows is minimum . the city 1 record of this row is são paulo . the city 2 record of this row is rio de janeiro .
eq { count { filter_eq { all_rows ; party ; democratic } } ; 4 } = true
Output: select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 .
and { only { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } } ; eq { hop { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } ; date } ; 15 october 2013 } } = true
Output: select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification . there is only one such row in the table . the date record of this unqiue row is 15 october 2013 .
eq { count { filter_eq { all_rows ; country ; philippines } } ; 6 } = true
Output: select the rows whose country record fuzzily matches to philippines . the number of such rows is 6 .
greater { hop { filter_eq { all_rows ; tv station ( operator ) ; modernine tv } ; 2005 } ; hop { filter_eq { all_rows ; tv station ( operator ) ; nbt } ; 2005 } } = true
Output: select the rows whose tv station  operator  record fuzzily matches to modernine tv . take the 2005 record of this row . select the rows whose tv station  operator  record fuzzily matches to nbt . take the 2005 record of this row . the first record is greater than the second record .
and { only { filter_eq { all_rows ; league ; aba } } ; eq { hop { filter_eq { all_rows ; league ; aba } ; season } ; 2004 - 05 } } = true
Output: select the rows whose league record fuzzily matches to aba . there is only one such row in the table . the season record of this unqiue row is 2004  05 .
round_eq { sum { filter_eq { all_rows ; place ; t3 } ; money } ; 752 } = true
Output: select the rows whose place record fuzzily matches to t3 . the sum of the money record of these rows is 752 .
and { only { filter_eq { all_rows ; result ; none } } ; eq { hop { filter_eq { all_rows ; result ; none } ; week } ; 3 } } = true
Output: select the rows whose result record fuzzily matches to none . there is only one such row in the table . the week record of this unqiue row is 3 .
and { only { filter_eq { all_rows ; episodes ; 17 } } ; eq { hop { filter_eq { all_rows ; episodes ; 17 } ; season } ; 2 } } = true
Output: select the rows whose episodes record is equal to 17 . there is only one such row in the table . the season record of this unqiue row is 2 .
round_eq { avg { all_rows ; elevation ( m ) } ; 4390 } = true
Output: the average of the elevation  m  record of all rows is 4390 .
most_eq { all_rows ; film or series ; eastenders } = true
Output: for the film or series records of all rows , most of them fuzzily match to eastenders .
and { only { filter_eq { all_rows ; elevation msl ; 3400 msl } } ; eq { hop { filter_eq { all_rows ; elevation msl ; 3400 msl } ; city district } ; santiago } } = true
Output: select the rows whose elevation msl record fuzzily matches to 3400 msl . there is only one such row in the table . the city district record of this unqiue row is santiago .
eq { count { filter_less { all_rows ; race time ; 3:00:00 } } ; 4 } = true
Output: select the rows whose race time record is less than 3:00:00 . the number of such rows is 4 .
round_eq { sum { filter_eq { all_rows ; player ; ( can ) } ; goals } ; 26 } = true
Output: select the rows whose player record fuzzily matches to  can  . the sum of the goals record of these rows is 26 .
eq { hop { argmax { all_rows ; attendance } ; date } ; 19th } = true
Output: select the row whose attendance record of all rows is maximum . the date record of this row is 19th .
eq { hop { nth_argmax { all_rows ; published ; 2 } ; title } ; hollywood } = true
Output: select the row whose published record of all rows is 2nd maximum . the title record of this row is hollywood .
eq { count { filter_eq { all_rows ; date ; 26 april 1947 } } ; 6 } = true
Output: select the rows whose date record fuzzily matches to 26 april 1947 . the number of such rows is 6 .
most_eq { all_rows ; position ; forward } = true
Output: for the position records of all rows , most of them fuzzily match to forward .
and { eq { nth_min { all_rows ; time ; 1 } ; 2:25.46 } ; and { eq { hop { nth_argmin { all_rows ; time ; 1 } ; rank } ; 1 } ; eq { hop { nth_argmin { all_rows ; time ; 1 } ; name } ; kristy kowal } } } = true
Output: the 1st minimum time record of all rows is 2:25.46 . the rank record of the row with 1st minimum time record is 1 . the name record of the row with 1st minimum time record is kristy kowal .
eq { count { filter_eq { all_rows ; penalty ; roughing } } ; 2 } = true
Output: select the rows whose penalty record fuzzily matches to roughing . the number of such rows is 2 .
and { only { filter_eq { all_rows ; mens singles ; andrew smith } } ; eq { hop { filter_eq { all_rows ; mens singles ; andrew smith } ; year } ; 2006 } } = true
Output: select the rows whose mens singles record fuzzily matches to andrew smith . there is only one such row in the table . the year record of this unqiue row is 2006 .
greater { hop { filter_eq { all_rows ; player ; patrick collins } ; pick } ; hop { filter_eq { all_rows ; player ; sterling sharpe } ; pick } } = true
Output: select the rows whose player record fuzzily matches to patrick collins . take the pick record of this row . select the rows whose player record fuzzily matches to sterling sharpe . take the pick record of this row . the first record is greater than the second record .
eq { hop { nth_argmin { all_rows ; discontinued ; 2 } ; model } ; lisa 2 } = true
Output: select the row whose discontinued record of all rows is 2nd minimum . the model record of this row is lisa 2 .
eq { count { filter_eq { all_rows ; time ; accident } } ; 4 } = true
Output: select the rows whose time record fuzzily matches to accident . the number of such rows is 4 .
eq { count { filter_eq { filter_eq { all_rows ; res ; win } ; round ; 1 } } ; 8 } = true
Output: select the rows whose res record fuzzily matches to win . among these rows , select the rows whose round record is equal to 1 . the number of such rows is 8 .