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Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; written by ; david wolkove } } ; 2 }, interpretation: select the rows whose type record fuzzily matches to private . the number of such rows is 12 . Output:
[ "no" ]
task211-bf29fe14b81f4ea4ad4385361b4b903f
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: all_eq { all_rows ; date ; 21 july 1951 }, interpretation: for the date records of all rows , all of them fuzzily match to 21 july 1951 . Output:
[ "yes" ]
task211-933a6f451efb4a94bfa8e28b153445c2
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: greater { hop { filter_eq { all_rows ; away team ; south melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; north melbourne } ; away team score } }, interpretation: select the rows whose home team score record is greater than 12 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 2 . Output:
[ "no" ]
task211-1d298f62abdd42178aac4bf1a01ef870
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_greater { filter_eq { all_rows ; date ; november } ; attendance ; 60000 } } ; 1 }, interpretation: select the rows whose team record fuzzily matches to bms scuderia italia . take the laps record of this row . select the rows whose team record fuzzily matches to jb racing . take the laps record of this row . the first record is greater than the second record . Output:
[ "no" ]
task211-7c04eabd6f474854a7e4fccbde39a3c5
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: only { filter_less { all_rows ; running time ; 30 minutes } }, interpretation: select the rows whose running time record is less than 30 minutes . there is only one such row in the table . Output:
[ "yes" ]
task211-a847c938869c4b99ad9cb4f3dd9aa436
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_eq { all_rows ; mascot ; tigers } } ; eq { hop { filter_eq { all_rows ; mascot ; tigers } ; school } ; yorktown } }, interpretation: select the rows whose mascot record fuzzily matches to tigers . there is only one such row in the table . the school record of this unqiue row is yorktown . Output:
[ "yes" ]
task211-654d54eaacaf4dd994669d070fe614e7
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { filter_eq { all_rows ; director ; pamela fryman } ; original air date ; april } } ; 3 }, interpretation: select the rows whose director record fuzzily matches to pamela fryman . among these rows , select the rows whose original air date record fuzzily matches to april . the number of such rows is 3 . Output:
[ "yes" ]
task211-fb32e276760b4c9d9bec04afa79d1f4a
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_less { filter_eq { all_rows ; ground ; football park } ; crowd ; 16000 } } ; 1 }, interpretation: select the rows whose ground record fuzzily matches to football park . among these rows , select the rows whose crowd record is less than 16000 . the number of such rows is 1 . Output:
[ "yes" ]
task211-50af27df82614914a55d2ee5b77ad6b4
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { nth_min { filter_eq { all_rows ; competition ; world championships } ; year ; 2 } ; 2001 }, interpretation: select the rows whose l3 cache record fuzzily matches to 8 mb . the maximum frequency record of these rows is 3 ghz . the model number record of the row with superlative frequency record is core i7 - 3940xm . Output:
[ "no" ]
task211-ca494341e2dc493f81f85aa5bdb3dad4
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmin { all_rows ; place } ; player } ; gary hallberg }, interpretation: select the row whose place record of all rows is minimum . the player record of this row is gary hallberg . Output:
[ "yes" ]
task211-da098b088a42445781ddb9a50c735596
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; candidates ; david bard } } ; 2 }, interpretation: select the rows whose outcome record fuzzily matches to winner . the number of such rows is 4 . Output:
[ "no" ]
task211-c2e4de1220c54685b060a7995d3d7274
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; ties ; 1 } } ; 3 }, interpretation: select the rows whose ties record is equal to 1 . the number of such rows is 3 . Output:
[ "yes" ]
task211-aaab373d665f41a88ae48776829b7c6b
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: all_greater_eq { filter_eq { all_rows ; street address ; gold avenue sw } ; height ft / m ; 180 }, interpretation: select the rows whose us viewers ( in millions ) record is less than 8 . there is only one such row in the table . the no by series record of this unqiue row is 6 . Output:
[ "no" ]
task211-253464cb4a5440fb8dfa8ba58ae5cd07
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_less { all_rows ; crowd ; 30000 }, interpretation: for the crowd records of all rows , most of them are less than 30000 . Output:
[ "yes" ]
task211-1e9164b4be18456ebbc98dee5607ebac
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { avg { all_rows ; 1990 - 95 } ; 0.27 }, interpretation: the average of the 1990 - 95 record of all rows is 0.27 . Output:
[ "yes" ]
task211-93a2ae9b2ce041b69ffd1a32f102603f
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; film or series ; eastenders }, interpretation: for the film or series records of all rows , most of them fuzzily match to eastenders . Output:
[ "yes" ]
task211-da4d3d17fbde4f29b7b2e78421ae48af
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: less { hop { filter_eq { all_rows ; name ; over the deel } ; age } ; hop { filter_eq { all_rows ; name ; captain dibble } ; age } }, interpretation: select the rows whose location record fuzzily matches to sheffield , england . among these rows , select the rows whose type record fuzzily matches to club trophy . the number of such rows is 2 . Output:
[ "no" ]
task211-ee7a9ea22b304b8e8b30b8f98b746148
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { diff { hop { filter_eq { all_rows ; name ; phil karn } ; goals } ; hop { filter_eq { all_rows ; name ; michael apple } ; goals } } ; 2 }, interpretation: select the rows whose name record fuzzily matches to phil karn . take the goals record of this row . select the rows whose name record fuzzily matches to michael apple . take the goals record of this row . the first record is 2 larger than the second record . Output:
[ "yes" ]
task211-e156b04f29f54f25b0e33bc3fd0fdf76
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_greater { filter_eq { all_rows ; country ; united states } ; to par ; -8 }, interpretation: select the rows whose country record fuzzily matches to united states . for the to par records of these rows , most of them are greater than -8 . Output:
[ "yes" ]
task211-eedd497e2b494b73b67e7e6f6a6e2e8d
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_less { all_rows ; prone ; 200 }, interpretation: for the prone records of all rows , most of them are less than 200 . Output:
[ "yes" ]
task211-d086ee4537794152af52826077d86997
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; january 19 }, interpretation: select the rows whose school ( ihsaa id ) record fuzzily matches to knox community . take the enrollment record of this row . select the rows whose school ( ihsaa id ) record fuzzily matches to culver community . take the enrollment record of this row . the first record is greater than the second record . Output:
[ "no" ]
task211-e64747d5884d468faafeba3e456960e3
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_less { filter_eq { all_rows ; nation ; kenya } ; time ; 30:34 } } ; 2 }, interpretation: select the row whose quantity made record of all rows is maximum . the class record of this row is 2 . Output:
[ "no" ]
task211-6c62cdbcc69e4a9e88efd2ae9c9aee2e
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_greater_eq { all_rows ; score ; 70 }, interpretation: for the score records of all rows , most of them are greater than or equal to 70 . Output:
[ "yes" ]
task211-ebd2cb73a59b4defbaa54c73666d7b82
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { sum { all_rows ; crowd } ; 86100 }, interpretation: select the rows whose notes record fuzzily matches to 1500 m . the number of such rows is 4 . Output:
[ "no" ]
task211-618d5f47f3ad46ceaf43c76191f27aa8
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; clinical status ; fda - approved } } ; 6 }, interpretation: select the rows whose clinical status record fuzzily matches to fda - approved . the number of such rows is 6 . Output:
[ "yes" ]
task211-feb95a91cedc46c6aa1c2fdeb0db7887
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { nth_min { all_rows ; date ; 16 } ; december 20 , 1981 }, interpretation: select the row whose time record of all rows is 2nd maximum . the wrestler record of this row is chris masters . Output:
[ "no" ]
task211-540ddec0e7ee40858b7509a5f9d92174
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; eliminated by ; carlito }, interpretation: select the rows whose school record fuzzily matches to avon community . take the enrollment record of this row . select the rows whose school record fuzzily matches to brownsburg . take the enrollment record of this row . the first record is greater than the second record . Output:
[ "no" ]
task211-047061927c084cf6845834039328d234
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmin { all_rows ; date ; 13 } ; race } ; italian grand prix }, interpretation: select the rows whose year born record is equal to 1979 . there is only one such row in the table . the player record of this unqiue row is konstantinos tsartsaris . Output:
[ "no" ]
task211-a3f7addfc3704467b7400bafaaa550a3
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { avg { all_rows ; weight } ; 88 }, interpretation: select the row whose notes record of all rows is 3rd maximum . the year record of this row is 2004 . Output:
[ "no" ]
task211-d5417bd192154fc88537d193c12bdc1f
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: all_eq { all_rows ; pl gp ; 0 }, interpretation: select the rows whose yards record is greater than 1000 . the number of such rows is 2 . Output:
[ "no" ]
task211-f0b180c96c174afbbe018895a2f75837
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_all { all_rows ; player } } ; 5 }, interpretation: for the format records of all rows , most of them fuzzily match to cd . Output:
[ "no" ]
task211-e429914960724c65b83645692f3f6f68
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: greater { hop { filter_eq { all_rows ; english name ; hexi district } ; density } ; hop { filter_eq { all_rows ; english name ; fenghuang } ; density } }, interpretation: select the rows whose call sign record fuzzily matches to w269ax . take the frequency mhz record of this row . select the rows whose call sign record fuzzily matches to w230av . take the frequency mhz record of this row . the first record is greater than the second record . Output:
[ "no" ]
task211-55dd9a109cea400e81b0662d44330409
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: all_eq { all_rows ; ihsaa class ; aaaa }, interpretation: select the rows whose focal plane in ft ( m ) record fuzzily matches to n / a . there is only one such row in the table . the lighthouse record of this unqiue row is basco . Output:
[ "no" ]
task211-6459d324c5cf45c08a8bf4817aa98622
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: greater { hop { filter_eq { all_rows ; nation ; united kingdom } ; silver } ; hop { filter_eq { all_rows ; nation ; finland } ; silver } }, interpretation: select the rows whose nation record fuzzily matches to united kingdom . take the silver record of this row . select the rows whose nation record fuzzily matches to finland . take the silver record of this row . the first record is greater than the second record . Output:
[ "yes" ]
task211-5ccf4014aa6b46d5bd15d8dec9bcdb0c
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_all { all_rows ; meas num } } ; 11 }, interpretation: select the rows whose engine record fuzzily matches to ford cosworth dfr v8 . there is only one such row in the table . the year record of this unqiue row is 1989 . Output:
[ "no" ]
task211-52f34ff36b1a43e8af05c20ff5d83aa7
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; constructor ; toyota } } ; 2 }, interpretation: select the rows whose constructor record fuzzily matches to toyota . the number of such rows is 2 . Output:
[ "yes" ]
task211-335dbb0ee23e4a72b6fe99309737791b
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_eq { all_rows ; top - 25 ; 6 } } ; eq { hop { filter_eq { all_rows ; top - 25 ; 6 } ; tournament } ; masters tournament } }, interpretation: select the rows whose team record fuzzily matches to palmeiras . take the against record of this row . select the rows whose team record fuzzily matches to flamengo . take the against record of this row . the first record is less than the second record . Output:
[ "no" ]
task211-ae77e04979574a37bc5d6b0c87d70f2a
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { all_rows ; agg } ; team 1 } ; canon yaoundé }, interpretation: select the row whose agg record of all rows is maximum . the team 1 record of this row is canon yaoundé . Output:
[ "yes" ]
task211-2881eb90a0594867941a65c07e31b5de
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { filter_eq { all_rows ; drawn ; 0 } ; won } ; club } ; brynmawr rfc }, interpretation: select the rows whose format record fuzzily matches to christian . take the frequency record of this row . select the rows whose format record fuzzily matches to public broadcasting . take the frequency record of this row . the first record is less than the second record . Output:
[ "no" ]
task211-849f74b316ee405e8728bff00d14881e
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmax { all_rows ; date ; 2 } ; opponent } ; maša zec peškirič }, interpretation: select the row whose date record of all rows is 2nd maximum . the opponent record of this row is maša zec peškirič . Output:
[ "yes" ]
task211-d040a2ab6f2849949e644a32dd1ff5cd
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { avg { all_rows ; vertical } ; 720 }, interpretation: the average of the vertical record of all rows is 720 . Output:
[ "yes" ]
task211-115e396b8d7d4249a94ebc63da2e26a9
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { all_rows ; goals scored } ; club } ; fbk kaunas }, interpretation: for the label records of all rows , all of them fuzzily match to linfair records . Output:
[ "no" ]
task211-7ebbb5a9a66f462b93182d9ce5dfee78
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_greater { all_rows ; crowd ; 10000 }, interpretation: select the rows whose game site record fuzzily matches to shea stadium . the number of such rows is 8 . Output:
[ "no" ]
task211-ae9cfd3721404d5eb0f56b65f3acb4dd
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { all_rows ; votes } ; election } ; 1990 }, interpretation: select the row whose votes record of all rows is maximum . the election record of this row is 1990 . Output:
[ "yes" ]
task211-6994c66600cb4b1ebc8e1e05b0eeda8e
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: greater { hop { filter_eq { all_rows ; home team ; fitzroy } ; home team score } ; hop { filter_eq { all_rows ; home team ; collingwood } ; home team score } }, interpretation: select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is tom barrett . Output:
[ "no" ]
task211-54d7e9c6b4bf4b2fa63395f0ab33864b
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; current status ; active }, interpretation: select the rows whose gpu frequency record fuzzily matches to 320 mhz . for the release price ( usd ) records of these rows , all of them are greater than 60 . Output:
[ "no" ]
task211-2c41af652fa94c0eacec01f70fb5783b
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_greater { all_rows ; first elected ; 1960 }, interpretation: the average of the erp w record of all rows is 37.5 watts . Output:
[ "no" ]
task211-c9ad6a255c494f308aa9b5132d552f13
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { all_rows ; multi lane } ; category wise } ; national highways }, interpretation: select the rows whose laps record is less than 5 . there is only one such row in the table . the year record of this unqiue row is 1953 . Output:
[ "no" ]
task211-e1480b657d644a5d833629159d82efcf
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { avg { all_rows ; crowd } ; 19900 }, interpretation: for the position records of all rows , most of them fuzzily match to 1st . Output:
[ "no" ]
task211-911dc0dff12c4ac09181d1203b23929d
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: all_eq { all_rows ; games played ; 36 }, interpretation: for the games played records of all rows , all of them are equal to 36 . Output:
[ "yes" ]
task211-3fa0a2730a1740549c8b165236b0c217
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; margin ; 3 strokes } } ; 2 }, interpretation: select the rows whose losses record is equal to 8 . the number of such rows is 2 . Output:
[ "no" ]
task211-c580c5f410bd45f889252d38f2dea01c
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: all_eq { filter_eq { all_rows ; date ; october } ; result ; w }, interpretation: select the rows whose date record fuzzily matches to october . for the result records of these rows , all of them fuzzily match to w . Output:
[ "yes" ]
task211-4577bbe29c93495c959fcb37388c88e4
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; released ; 2012 }, interpretation: select the rows whose player record fuzzily matches to fedor dmitriev . take the year born record of this row . select the rows whose player record fuzzily matches to anton ponkrashov . take the year born record of this row . the first record is less than the second record . Output:
[ "no" ]
task211-a7409850f0374545873d500bf1400201
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_eq { all_rows ; playoffs ; league finals } } ; eq { hop { filter_eq { all_rows ; playoffs ; league finals } ; year } ; 1978 } }, interpretation: for the winning team records of all rows , most of them fuzzily match to mobilecast impul . Output:
[ "no" ]
task211-cb645624e4904c76bf044c9582aed429
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { filter_eq { all_rows ; gpu model ; hd graphics 4000 } ; l3 cache ; 6mb }, interpretation: select the rows whose college record fuzzily matches to acadia . there is only one such row in the table . the player record of this unqiue row is karl ortmanns . Output:
[ "no" ]
task211-9cbf637ffba04cd6aef96d9bcf955cc7
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_less { all_rows ; rating ; 3 } } ; eq { hop { filter_less { all_rows ; rating ; 3 } ; ride } ; taxi jam } }, interpretation: select the rows whose earpads record fuzzily matches to comfort pads . the number of such rows is 4 . Output:
[ "no" ]
task211-c3eaf6ad10a84c50b36da90852188a44
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { all_rows ; length } ; name } ; northern eagle }, interpretation: select the rows whose state / territory record fuzzily matches to queensland . the number of such rows is 6 . Output:
[ "no" ]
task211-c222281b16bb41c5852ba49cd9e4da04
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; type ; private }, interpretation: for the type records of all rows , most of them fuzzily match to private . Output:
[ "yes" ]
task211-9a82deb3630d4c5d8f556e53e12c479d
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmax { all_rows ; round ; 2 } ; player } ; jeffrey hunter }, interpretation: select the rows whose date record fuzzily matches to october 3 . take the attendance record of this row . select the rows whose date record fuzzily matches to september 26 . take the attendance record of this row . the first record is 8306 larger than the second record . Output:
[ "no" ]
task211-c2f181f60f9a4f59a5c831cd968518e6
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; kiplinger 's top 100 values ; n / a } } ; 6 }, interpretation: select the rows whose kiplinger 's top 100 values record fuzzily matches to n / a . the number of such rows is 6 . Output:
[ "yes" ]
task211-4f3a379cfe3b490b88b4a9de939d8ebf
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { all_rows ; pts } ; entrant } ; leyton house march racing team }, interpretation: select the row whose pts record of all rows is maximum . the entrant record of this row is leyton house march racing team . Output:
[ "yes" ]
task211-653420468d3c4d8999991af6e333e9c0
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { diff { hop { filter_eq { all_rows ; incumbent ; frank t bow } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; louis stokes } ; first elected } } ; -18 years }, interpretation: select the rows whose height in ft record is less than 6-0 . there is only one such row in the table . the player record of this unqiue row is turner , andre andre turner . Output:
[ "no" ]
task211-051f5dbc4aef44b989b99d5046784619
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: greater { hop { filter_eq { all_rows ; opponent ; murilo bustamante } ; round } ; hop { filter_eq { all_rows ; opponent ; david abbott } ; round } }, interpretation: the 1st maximum crowd record of all rows is 26000 . the venue record of the row with 1st maximum crowd record is punt road oval . the date record of the row with 1st maximum crowd record is 9 august 1941 . Output:
[ "no" ]
task211-ae8394a07c9b4189bab129406c902460
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; owner ; wnetorg } } ; 2 }, interpretation: select the rows whose owner record fuzzily matches to wnetorg . the number of such rows is 2 . Output:
[ "yes" ]
task211-8ebd05a3d7024b11a5cbe9872d1f670a
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: greater { hop { filter_eq { all_rows ; goalkeeper ; matías garavano } ; goals } ; hop { filter_eq { all_rows ; goalkeeper ; álvaro campos } ; goals } }, interpretation: select the row whose score record of all rows is minimum . the player record of this row is tim simpson . Output:
[ "no" ]
task211-a338d757e5c847f7ae5bc1743e025775
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { avg { all_rows ; goals per match } ; 1.052 }, interpretation: select the rows whose location record fuzzily matches to arnhem . take the date ( from ) record of this row . select the rows whose location record fuzzily matches to nijmegen . take the date ( from ) record of this row . the first record is less than the second record . Output:
[ "no" ]
task211-75242d0c2cef46709889bc54a4096090
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; written by ; shonda rhimes } } ; 4 }, interpretation: select the rows whose written by record fuzzily matches to shonda rhimes . the number of such rows is 4 . Output:
[ "yes" ]
task211-c18c64deb19e4d2e8e7cd541c16b867e
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { avg { all_rows ; score } ; 2.2 }, interpretation: select the rows whose opponent record fuzzily matches to brooklyn dodgers . the number of such rows is 2 . Output:
[ "no" ]
task211-bc151ad9a15b40c588abb4bddcbb26fc
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; date ( s ) ; september 2006 } } ; 2 }, interpretation: for the long records of all rows , most of them are less than 10 . Output:
[ "no" ]
task211-8346e03f11c949e3b44c78ed80707616
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { avg { all_rows ; total } ; 2.13 }, interpretation: select the rows whose rank record is less than or equal to 5 . the average of the bronze record of these rows is 4 . Output:
[ "no" ]
task211-fafa0dbc064e49cdbfe52dad17495135
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { filter_eq { all_rows ; date ; november } ; result ; l }, interpretation: select the rows whose tournament record fuzzily matches to mci heritage golf classic . there is only one such row in the table . the date record of this unqiue row is 17 apr 1988 . Output:
[ "no" ]
task211-b37249801bc144f483097a0b0a5b3075
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmax { filter_eq { all_rows ; original air date ; august } ; us viewers ( million ) ; 2 } ; title } ; a little death }, interpretation: select the rows whose original air date record fuzzily matches to august . select the row whose us viewers ( million ) record of these rows is 2nd maximum . the title record of this row is a little death . Output:
[ "yes" ]
task211-69d90b1b80234fc3b4335cc433873aca
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { diff { hop { filter_eq { all_rows ; name ; keutenberg } ; kilometer } ; hop { filter_eq { all_rows ; name ; fromberg } ; kilometer } } ; 4 }, interpretation: select the rows whose name record fuzzily matches to keutenberg . take the kilometer record of this row . select the rows whose name record fuzzily matches to fromberg . take the kilometer record of this row . the first record is 4 larger than the second record . Output:
[ "yes" ]
task211-eb55c2ea26b24af1aa38c67e54f5e9ae
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; date ; 25 october }, interpretation: for the date records of all rows , most of them fuzzily match to 25 october . Output:
[ "yes" ]
task211-e28a23f7760046e39b480ac960c48cb7
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_eq { all_rows ; developer ; cloud imperium games corporation } } ; eq { hop { filter_eq { all_rows ; developer ; cloud imperium games corporation } ; title } ; star citizen } }, interpretation: select the rows whose position record fuzzily matches to defensive end . the number of such rows is 2 . Output:
[ "no" ]
task211-8f9123f276de4000925a6c81a56d240a
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; uccfs ; 2006 }, interpretation: select the rows whose native american record fuzzily matches to 0.0 % . the number of such rows is 4 . Output:
[ "no" ]
task211-51833e1361924c2ebb45430363faf352
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_all { all_rows ; player } } ; 12 }, interpretation: select the rows whose player record is arbitrary . the number of such rows is 12 . Output:
[ "yes" ]
task211-2f244d6aefc24f1987985fdb28814db3
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmax { all_rows ; location / attendance ; 1 } ; opponent } ; new york }, interpretation: for the venue records of all rows , most of them fuzzily match to hampden park , glasgow . Output:
[ "no" ]
task211-c3e9143567704b61b10cbf10a80c1430
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmin { all_rows ; 1st run ; 2 } ; name } ; donny robinson ( usa ) }, interpretation: select the row whose juries record of all rows is maximum . the artist record of this row is danny saucedo . Output:
[ "no" ]
task211-a7acf6616cae4003be476be2f5426074
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; fate ; damaged } } ; 2 }, interpretation: select the rows whose fate record fuzzily matches to damaged . the number of such rows is 2 . Output:
[ "yes" ]
task211-b2ec1168017a4ff380ea3b971e542b72
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_not_eq { all_rows ; result ; re-elected } } ; eq { hop { filter_not_eq { all_rows ; result ; re-elected } ; incumbent } ; iris faircloth blitch } }, interpretation: select the rows whose result record does not match to re-elected . there is only one such row in the table . the incumbent record of this unqiue row is iris faircloth blitch . Output:
[ "yes" ]
task211-94ee7af63e9b46059c338c01543bae20
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_eq { all_rows ; type ; nursery } } ; eq { hop { filter_eq { all_rows ; type ; nursery } ; name } ; heath lane } }, interpretation: select the rows whose type record fuzzily matches to nursery . there is only one such row in the table . the name record of this unqiue row is heath lane . Output:
[ "yes" ]
task211-605a8d935ff24b34875ef27200cb3764
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: less { hop { filter_eq { all_rows ; season ; 2010 - 11 } ; rank ( league / conference ) } ; hop { filter_eq { all_rows ; season ; 2012 - 13 } ; rank ( league / conference ) } }, interpretation: select the rows whose season record fuzzily matches to 2010 - 11 . take the rank ( league / conference ) record of this row . select the rows whose season record fuzzily matches to 2012 - 13 . take the rank ( league / conference ) record of this row . the first record is less than the second record . Output:
[ "yes" ]
task211-f6e1aae9559848f6b2bc6a51c651f3bc
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_eq { all_rows ; years in orlando ; present } } ; eq { hop { filter_eq { all_rows ; years in orlando ; present } ; player } ; victor oladipo } }, interpretation: select the row whose year joined record of all rows is 1st maximum . the school record of this row is elkhart christian . Output:
[ "no" ]
task211-bbfed92fc0394452a218d7b35bb468b5
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmax { all_rows ; swing to gain ; 3 } ; constituency } ; ayr }, interpretation: select the rows whose year record is equal to 2013 . there is only one such row in the table . the nominated work record of this unqiue row is commitment . Output:
[ "no" ]
task211-95ff4b9a466d40898747a50a183fa249
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { all_rows ; score ; 0 } } ; 7 }, interpretation: select the rows whose score record is equal to 0 . the number of such rows is 7 . Output:
[ "yes" ]
task211-1743fa2f77c84a19bf63bc8e2ca9b1fe
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmin { all_rows ; time ; 3 } ; race } ; derrinstown stud derby trial }, interpretation: select the rows whose venue record fuzzily matches to athens , greece . take the date record of this row . select the rows whose venue record fuzzily matches to oslo , norway . take the date record of this row . the first record is less than the second record . Output:
[ "no" ]
task211-bce3e5d56bf842b1843827008cdf34b5
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; director ; paul gay }, interpretation: for the director records of all rows , most of them fuzzily match to paul gay . Output:
[ "yes" ]
task211-4e183013d9484717bc73ed163b30e84f
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: less { hop { filter_eq { all_rows ; round winner ; larry perkins } ; date } ; hop { filter_eq { all_rows ; round winner ; mark skaife } ; date } }, interpretation: select the rows whose round winner record fuzzily matches to larry perkins . take the date record of this row . select the rows whose round winner record fuzzily matches to mark skaife . take the date record of this row . the first record is less than the second record . Output:
[ "yes" ]
task211-acf82001e88a4cd698d1c21ba13d1521
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: and { only { filter_eq { all_rows ; agricultural panel ; 0 } } ; eq { hop { filter_eq { all_rows ; agricultural panel ; 0 } ; party } ; independent } }, interpretation: for the to par records of all rows , most of them are equal to 7 . Output:
[ "no" ]
task211-33c5d7f2ef7e4e3ea17464bda909672d
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: most_eq { all_rows ; result ; safe }, interpretation: select the rows whose title record fuzzily matches to trust and consequence . take the original air date record of this row . select the rows whose title record fuzzily matches to father , can you hair me . take the original air date record of this row . the second record is 7 days larger than the first record . Output:
[ "no" ]
task211-52bbf6e2ec824a1aabafad30047f96a1
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { all_rows ; home team score } ; home team } ; st kilda }, interpretation: select the row whose home team score record of all rows is maximum . the home team record of this row is st kilda . Output:
[ "yes" ]
task211-88d59bf5012c4a9084fae4ba0c7c2c84
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { argmax { all_rows ; attendance } ; opponent } ; denver broncos }, interpretation: select the row whose attendance record of all rows is maximum . the opponent record of this row is denver broncos . Output:
[ "yes" ]
task211-80ea63896f034ff687e98993f1c9c65c
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: round_eq { avg { all_rows ; total receipts } ; 12444351 }, interpretation: select the rows whose year record is less than or equal to 2002 . the average of the winnings record of these rows is 44881 . Output:
[ "no" ]
task211-ae0f67ff548f4e46ab29a3788c0dbb9f
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_greater_eq { filter_greater_eq { all_rows ; gold ; 10 } ; silver ; 20 } } ; 3 }, interpretation: select the rows whose gold record is greater than or equal to 10 . among these rows , select the rows whose silver record is greater than or equal to 20 . the number of such rows is 3 . Output:
[ "yes" ]
task211-dc6117b0a4bf4f5ab810d0b52627835a
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: all_eq { all_rows ; songwriter ( s ) ; ( adapted by malcolm dodds ) }, interpretation: select the row whose time record of all rows is 1st minimum . the winner record of this row is cashier 's dream . Output:
[ "no" ]
task211-3722de6766cb431186862e583ce80d44
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { count { filter_eq { filter_eq { all_rows ; service ; marine corps } ; rank ; private } } ; 5 }, interpretation: select the rows whose first elected record fuzzily matches to 196 . the number of such rows is 2 . Output:
[ "no" ]
task211-b31a74e5adf8478599b8000bd362560d
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { diff { hop { filter_eq { all_rows ; venue ; western oval } ; crowd } ; hop { filter_eq { all_rows ; venue ; windy hill } ; crowd } } ; 3755 }, interpretation: select the rows whose venue record fuzzily matches to western oval . take the crowd record of this row . select the rows whose venue record fuzzily matches to windy hill . take the crowd record of this row . the first record is 3755 larger than the second record . Output:
[ "yes" ]
task211-8c3c2a256d60495a9623d7eede5f7933
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: eq { hop { nth_argmax { all_rows ; year ; 2 } ; album title } ; realism }, interpretation: select the row whose year record of all rows is 2nd maximum . the album title record of this row is realism . Output:
[ "yes" ]
task211-2512c4b6e8bc40caab946011bcf6602e
Definition: In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". Here are the definitions of logical operators: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: yes Positive Example 2 - Input: Command: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }, interpretation: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: yes Negative Example 1 - Input: Command: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }, interpretation: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: no Negative Example 2 - Input: Command: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }, interpretation: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna. Output: yes Now complete the following example - Input: Command: less { hop { filter_eq { all_rows ; sport ; soccer } ; 1st tournament } ; hop { filter_eq { all_rows ; sport ; bowling } ; 1st tournament } }, interpretation: select the rows whose sport record fuzzily matches to soccer . take the 1st tournament record of this row . select the rows whose sport record fuzzily matches to bowling . take the 1st tournament record of this row . the first record is less than the second record . Output:
[ "yes" ]
task211-798b79486ea246dcb105337355697d78