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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: and { only { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } } ; eq { hop { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } ; date } ; december 6 } }, interpretation: select the row whose position record of all rows is minimum . the year record of this row is 2009 . Output:
[ "no" ]
task211-7b63ae7d68c0432c843c37681d9b0b1f
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 { filter_eq { all_rows ; country ; united states } ; score } ; 66 }, interpretation: for the surface records of all rows , most of them fuzzily match to hard . Output:
[ "no" ]
task211-a8e715dc16344163a50b6e54311a0601
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 ; country ; united states }, interpretation: for the country records of all rows , all of them fuzzily match to united states . Output:
[ "yes" ]
task211-e1953e74da734a208ee9ad73231e3728
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 ; visitor ; winnipeg } ; date } ; hop { filter_eq { all_rows ; visitor ; chicago } ; date } }, interpretation: select the row whose points record of all rows is maximum . the player record of this row is dave allerdice . Output:
[ "no" ]
task211-4c34d45b85d44829a27b9a9235c60d0c
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 ; county ; wexford } } ; eq { hop { filter_eq { all_rows ; county ; wexford } ; player } ; christy kehoe } }, interpretation: select the rows whose county record fuzzily matches to wexford . there is only one such row in the table . the player record of this unqiue row is christy kehoe . Output:
[ "yes" ]
task211-2d477dbecbfb43a28cd30744ccb84dc0
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 } ; 21012 }, interpretation: the average of the crowd record of all rows is 21012 . Output:
[ "yes" ]
task211-05d0ec7c95284ebaa7530e2b57aa8ea9
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 ; nation } } ; 6 }, interpretation: select the rows whose nation record is arbitrary . the number of such rows is 6 . Output:
[ "yes" ]
task211-d6ed486108ac48baa3490cb8453850ec
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 ; crowd ; 2 } ; home team } ; melbourne }, interpretation: select the rows whose points record is greater than 0 . the number of such rows is 2 . Output:
[ "no" ]
task211-ff8311ac51a847bfaebf70464c21b82a
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 ; ratings } ; guest ( s ) } ; matt lucas }, interpretation: select the row whose ratings record of all rows is maximum . the guest ( s ) record of this row is matt lucas . Output:
[ "yes" ]
task211-8a94b245b2a64a5ead6e332922dee21b
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 { filter_eq { all_rows ; position ; ol } ; pick } ; cfl team } ; montreal alouettes }, interpretation: select the rows whose 2008 club record fuzzily matches to henan . the number of such rows is 2 . Output:
[ "no" ]
task211-acaeacf3b9be4ff2bbfedce6679bb809
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 ; player ; ian smart } ; rating } ; hop { filter_eq { all_rows ; player ; dave dickenson } ; rating } }, interpretation: for the party records of all rows , most of them fuzzily match to republican . Output:
[ "no" ]
task211-b236916b16be4666a5d9ac5904ec1f2b
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 ; l ; 0 } } ; eq { hop { filter_eq { all_rows ; l ; 0 } ; skip ( club ) } ; brad gushue ( bally haly ) } }, interpretation: select the rows whose l record is equal to 0 . there is only one such row in the table . the skip ( club ) record of this unqiue row is brad gushue ( bally haly ) . Output:
[ "yes" ]
task211-a1edffc4356e46d1bfd609d4f62710d1
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 ; tournament ; 25000 }, interpretation: for the tournament records of all rows , most of them fuzzily match to 25000 . Output:
[ "yes" ]
task211-73a7efe1c52b4ef3901adab3145d8f93
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 ; position ; rhp } } ; 6 }, interpretation: select the rows whose position record fuzzily matches to rhp . the number of such rows is 6 . Output:
[ "yes" ]
task211-7ea15313efef499e9a8f04ed0e3ddd43
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 ; january }, interpretation: for the date records of all rows , all of them fuzzily match to january . Output:
[ "yes" ]
task211-6ebdf8604fec43a3bd93127abacb20fc
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 ; september } ; result ; l }, interpretation: select the rows whose visitor record fuzzily matches to cavaliers . take the date record of this row . select the rows whose visitor record fuzzily matches to hornets . take the date record of this row . the first record is less than the second record . Output:
[ "no" ]
task211-f95b78b0a5254888ac568c9c2d20e3ea
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 ; 1 } ; winning driver } ; eugenio silvani }, interpretation: select the row whose points record of all rows is maximum . the year record of this row is 1989 . Output:
[ "no" ]
task211-89f67e5d7b854f828c6da2043d7e2c4b
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 ; director ; benedict andrews } } ; eq { hop { filter_eq { all_rows ; director ; benedict andrews } ; production } ; the war of the roses } }, interpretation: select the rows whose format record fuzzily matches to oldies . the number of such rows is 4 . Output:
[ "no" ]
task211-ee98ab89e5dd45dd8a4035bfa1174d45
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: the average of the weight record of all rows is 88 . Output:
[ "yes" ]
task211-25a549b5652448d697dc5b3193fe09d0
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_less { all_rows ; played ; 10 } ; palace wins ; 0 } } ; 3 }, interpretation: select the rows whose us viewers ( millions ) record does not match to n/a . the average of the us viewers ( millions ) record of these rows is 2.59 . Output:
[ "no" ]
task211-1f28358b5f1f421ba812ce52c43978f2
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 ; new membership total } ; conference } ; hockey east ( men ) }, interpretation: select the rows whose bronze record is equal to 8 . there is only one such row in the table . the rank record of this unqiue row is 3 . Output:
[ "no" ]
task211-6c06bbf57ea34a01bc780ac26c5f4201
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 ; year ; 1987 } ; points } ; hop { filter_eq { all_rows ; year ; 1995 } ; points } }, interpretation: select the rows whose home team score record is greater than 10 . for the crowd records of these rows , most of them are less than 20000 . Output:
[ "no" ]
task211-7f3721aa231e40779061c2088789d8d0
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_eq { all_rows ; team ; aermacchi } }, interpretation: select the rows whose surface record fuzzily matches to clay . there is only one such row in the table . the tournament record of this unqiue row is valencia , spain . Output:
[ "no" ]
task211-824231dc5c274e4e8c2a94851805fdac
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_eq { all_rows ; date ; may } }, interpretation: select the rows whose city record fuzzily matches to barisal . take the country record of this row . select the rows whose city record fuzzily matches to chittagong . take the country record of this row . the first record fuzzily matches to the second record . the country record of the first row is bangladesh . the country record of the second row is bangladesh . Output:
[ "no" ]
task211-64db86f4da1c4911b959445c3df813e4
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 ; horwood } ; 8 }, interpretation: select the rows whose date record fuzzily matches to january . among these rows , select the rows whose crowd record is less than 4000 . the number of such rows is 3 . Output:
[ "no" ]
task211-95e34645d4a542e980be6be6916962e6
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 ; gold ; 0 } ; silver ; 2 } } ; 2 }, interpretation: select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 2 . the number of such rows is 2 . Output:
[ "yes" ]
task211-7f1e05e485d543a29f0222dc34ea962e
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 ; south asians 2011 } ; province } ; ontario }, interpretation: select the rows whose time record is greater than 7:00:00 . there is only one such row in the table . the country record of this unqiue row is iraq . Output:
[ "no" ]
task211-c476394ea3b9406a86199985db410b5b
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 ; written by ; michael hirst }, interpretation: for the written by records of all rows , all of them fuzzily match to michael hirst . Output:
[ "yes" ]
task211-02a2b096d8e54d5d83bf6d40035c2c7b
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 ; club ; real murcia } ; wins } ; hop { filter_eq { all_rows ; club ; jerez cd } ; wins } }, interpretation: the average of the population served record of all rows is 4038 . Output:
[ "no" ]
task211-f318d0fff95b43e6b4c90f50fdc2f263
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 ; location attendance ; united center } } ; 3 }, interpretation: the sum of the score record of all rows is 16 . Output:
[ "no" ]
task211-b7d75741d6a946dea598128229325a44
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 ; record label ; for us } } ; eq { hop { filter_eq { all_rows ; record label ; for us } ; single } ; moped girls } }, interpretation: select the rows whose team record fuzzily matches to ducati . the number of such rows is 3 . Output:
[ "no" ]
task211-808e29a17d7641bfa3538024baab31bb
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 ; pick ; 19 } } ; 3 }, interpretation: for the issue price records of all rows , most of them are less than 100.0 . Output:
[ "no" ]
task211-4a37812aacd240ddae1a457c406665f6
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 ; town ships ; 18 } } ; eq { hop { filter_eq { all_rows ; town ships ; 18 } ; state / region } ; kachin state } }, interpretation: select the row whose vuelta record of all rows is maximum . the name record of this row is tony rominger ( sui ) . Output:
[ "no" ]
task211-daed7554e7154523a0650ebca3bdfa96
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 { filter_less_eq { all_rows ; rank ; 2 } ; wins } ; 35 }, interpretation: select the rows whose rank record is less than or equal to 2 . the sum of the wins record of these rows is 35 . Output:
[ "yes" ]
task211-b21cdc30ebcf45a7a5afc44e03cc0d8a
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 ; venue ; sydney cricket ground } ; date } ; hop { filter_eq { all_rows ; venue ; waca ground } ; date } }, interpretation: select the row whose goals record of all rows is maximum . the player record of this row is oleg veretennikov . Output:
[ "no" ]
task211-05f42cccff8f4d508bc714ed9df14137
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 ; scoring average } ; year } ; 2007 }, interpretation: select the row whose scoring average record of all rows is minimum . the year record of this row is 2007 . Output:
[ "yes" ]
task211-f7001f96fc4b43999339f4abe145afa1
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 ; 9 august 1952 }, interpretation: for the date records of all rows , all of them fuzzily match to 9 august 1952 . Output:
[ "yes" ]
task211-55d3f9f00f5045079d10966d8f51458b
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 ; incumbent ; john page } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; francis walker } ; first elected } }, interpretation: the average of the 1990 - 95 record of all rows is 0.27 . Output:
[ "no" ]
task211-7a000bde361f49c1b08a9cd65fc8365d
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 ; score } ; date } ; 9 october 2012 }, interpretation: select the rows whose tournament record fuzzily matches to the open championship . take the events record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the events record of this row . the first record is greater than the second record . Output:
[ "no" ]
task211-a42282bf250b44c1a54ab0bb2c0543f3
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 ; administrative panel } ; party } ; fine gael }, interpretation: select the rows whose tournaments played record is greater than 20 . there is only one such row in the table . Output:
[ "no" ]
task211-9a11e4c1d0f949659e3c4bf45a8b2176
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 ; 3 } ; version } ; album version }, interpretation: select the row whose year record of all rows is 3rd maximum . the version record of this row is album version . Output:
[ "yes" ]
task211-2af4e6c6e17145e69f78f9e305bf622d
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 ; result } ; driver } ; emerson fittipaldi }, interpretation: select the row whose result record of all rows is minimum . the driver record of this row is emerson fittipaldi . Output:
[ "yes" ]
task211-8bde479a0ce043ed8c28738cd900e9ed
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 ; candidates ; unopposed } } ; eq { hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent } ; tony p hall } }, interpretation: select the rows whose position record fuzzily matches to guard . the minimum round record of these rows is 11 . Output:
[ "no" ]
task211-7c13ae5e2a3047b89592d1007a0b0f42
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 ; crowd } ; venue } ; punt road oval }, interpretation: select the row whose crowd record of all rows is maximum . the venue record of this row is punt road oval . Output:
[ "yes" ]
task211-17022c4d79504757a23e03402617be1f
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 ; opponent ; denver broncos } ; date } ; hop { filter_eq { all_rows ; opponent ; new york titans } ; date } }, interpretation: select the rows whose opponent record fuzzily matches to denver broncos . take the date record of this row . select the rows whose opponent record fuzzily matches to new york titans . take the date record of this row . the first record is less than the second record . Output:
[ "yes" ]
task211-2e8e6a6082374e258fdc83f964a035ae
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 english name record fuzzily matches to hexi district . take the density record of this row . select the rows whose english name record fuzzily matches to fenghuang . take the density record of this row . the first record is greater than the second record . Output:
[ "yes" ]
task211-3cfbb60ab4144a0ba8f5d1550cd8eb96
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 ; cover model ; no model pictured } } ; eq { hop { filter_eq { all_rows ; cover model ; no model pictured } ; date } ; 1 - 84 } }, interpretation: select the rows whose cover model record fuzzily matches to no model pictured . there is only one such row in the table . the date record of this unqiue row is 1 - 84 . Output:
[ "yes" ]
task211-571434986faf4c2cbc725e6701f11897
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 ; region ; united states } } ; eq { hop { filter_eq { all_rows ; region ; united states } ; date } ; 17 march 2009 } }, interpretation: select the rows whose nickname record fuzzily matches to polar bears . there is only one such row in the table . the school record of this unqiue row is jackson . Output:
[ "no" ]
task211-1125e0f5b0bf4d43a5351a592d65fe89
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_greater { all_rows ; points ; 10 } ; lost ; 2 } ; team } ; aa palmeiras }, interpretation: select the rows whose team name record fuzzily matches to isport international . the number of such rows is 4 . Output:
[ "no" ]
task211-4b0dd857a35b40a5b850fa2b24fade15
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 ; to par } ; player } ; bill rogers }, interpretation: select the row whose goals record of all rows is minimum . the player record of this row is mehmet yılmaz . Output:
[ "no" ]
task211-f94c9c98f37e4053aba215fc4c64ca40
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 ; events } ; player } ; jim thorpe }, interpretation: for the venue records of all rows , most of them fuzzily match to amman . Output:
[ "no" ]
task211-d9320a4347844a3b98292e6196577699
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 ; height ( in ) } ; contestant } ; happie ntelamo }, interpretation: select the row whose height ( in ) record of all rows is maximum . the contestant record of this row is happie ntelamo . Output:
[ "yes" ]
task211-ea9090ad7591455dbb8ec57bdc4e84aa
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 ; opening week nett gross } ; movie } ; chennai express }, interpretation: select the rows whose number of contestants record is equal to 11 . the number of such rows is 3 . Output:
[ "no" ]
task211-a0f7e0c2f30a4274a6d7610dcf9dd07e
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 ; general classification ; nick nuyens } } ; 5 }, interpretation: select the rows whose general classification record fuzzily matches to nick nuyens . the number of such rows is 5 . Output:
[ "yes" ]
task211-7db8344d31aa49cf9007520c618a52cd
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 ; opponent ; brooklyn dodgers } } ; 2 }, interpretation: for the engine records of all rows , most of them fuzzily match to ferrari v12 . Output:
[ "no" ]
task211-a8fd289984f44c8a864f337f4c11b30d
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 ; country ; united states } ; score ; 143 } } ; 2 }, interpretation: for the area ( km square ) records of all rows , most of them are greater than 40 . Output:
[ "no" ]
task211-0404c486dd1a4b38b53011f4ad03592d
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 ; floors ; 2 } ; name } ; aul tower }, interpretation: select the row whose size record of all rows is maximum . the school record of this row is mitchell . Output:
[ "no" ]
task211-40f465b06d0a402194c34ed69115da3c
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 ; points } ; year } ; 2007 - 08 }, interpretation: select the row whose points record of all rows is maximum . the year record of this row is 2007 - 08 . Output:
[ "yes" ]
task211-84ffafca12db4a338b4489978a23ad72
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 ; college ; oklahoma } } ; eq { hop { filter_eq { all_rows ; college ; oklahoma } ; name } ; dominique franks } }, interpretation: select the rows whose college record fuzzily matches to oklahoma . there is only one such row in the table . the name record of this unqiue row is dominique franks . Output:
[ "yes" ]
task211-df9fd91563fc4c6eb386162a8a9096bb
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 { less { hop { filter_eq { all_rows ; week 5 ; melisa jackson } ; } ; hop { filter_eq { all_rows ; week 5 ; - } ; } } ; and { eq { hop { filter_eq { all_rows ; week 5 ; melisa jackson } ; } ; january } ; eq { hop { filter_eq { all_rows ; week 5 ; - } ; } ; february } } }, interpretation: the average of the height in ft record of all rows is 6 - 9 . Output:
[ "no" ]
task211-7a9038d0d4ae4692ac4f41619d4c357b
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 { eq { max { all_rows ; best finish } ; t - 17 } ; eq { hop { argmax { all_rows ; best finish } ; year } ; 2000 } }, interpretation: the maximum best finish record of all rows is t - 17 . the year record of the row with superlative best finish record is 2000 . Output:
[ "yes" ]
task211-bb5b158ccccc4d55832c65f5954143b9
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 ; total matches ; 5 } } ; 6 }, interpretation: select the rows whose total matches record is equal to 5 . the number of such rows is 6 . Output:
[ "yes" ]
task211-a6d6b95fa59e4b619aa10b93f6594930
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 ; year ; 2005 } } ; 2 }, interpretation: select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -6 . the number of such rows is 2 . Output:
[ "no" ]
task211-5e45f6ac286e4fd3850ea50e5fe53577
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 ; erp w } ; 37.5 watts }, interpretation: the average of the erp w record of all rows is 37.5 watts . Output:
[ "yes" ]
task211-5b59a1fa881d48718e86d34891c2fada
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 ; played ; 114 } ; points ; 100 }, interpretation: select the row whose losses record of all rows is maximum . the team record of this row is liverpool city . Output:
[ "no" ]
task211-569a8afcb34e4ce18a0b90948da2e513
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 ; headquarters ; united kingdom } } ; 2 }, interpretation: select the rows whose player record fuzzily matches to linden rowat ( g ) . take the round record of this row . select the rows whose player record fuzzily matches to dwight king ( c ) . take the round record of this row . the first record is 1 larger than the second record . the round record of the first row is 5 . the round record of the second row is 4 . Output:
[ "no" ]
task211-d062c4e27c064a5d8cd7044cee21a49d
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 ; ecuador } ; 2011 ( imf ) } ; hop { filter_eq { all_rows ; nation ; paraguay } ; 2011 ( imf ) } }, interpretation: select the rows whose nation record fuzzily matches to ecuador . take the 2011 ( imf ) record of this row . select the rows whose nation record fuzzily matches to paraguay . take the 2011 ( imf ) record of this row . the first record is greater than the second record . Output:
[ "yes" ]
task211-b621feda78b6494fbe08a5a3ea0df5f2
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 ; acquisition via ; rookie draft } } ; eq { hop { filter_eq { all_rows ; acquisition via ; rookie draft } ; name } ; ronjay buenafe } }, interpretation: select the rows whose acquisition via record fuzzily matches to rookie draft . there is only one such row in the table . the name record of this unqiue row is ronjay buenafe . Output:
[ "yes" ]
task211-6bc7da0fbf034326b56403830235a987
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 ; race title } } ; 5 }, interpretation: the average of the total record of all rows is 3 . Output:
[ "no" ]
task211-0ddb1c90c25f460184e57bfa74e1beb9
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 } ; 124845 }, interpretation: select the rows whose transfer fee record is greater than 0 . there is only one such row in the table . the player record of this unqiue row is matthew mills . Output:
[ "no" ]
task211-226da7a22e8a48a79a93fa1bbb76cb4a
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 ; call sign ; w269ax } ; frequency mhz } ; hop { filter_eq { all_rows ; call sign ; w230av } ; frequency mhz } }, 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:
[ "yes" ]
task211-9eae2c6ce24a40e6be6144e7b1ad9509
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 ; score } ; date } ; june 24 }, interpretation: for the date records of all rows , all of them fuzzily match to december . Output:
[ "no" ]
task211-595873d84aff401bb130f5a75f44ee05
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 ; pick ; 1 } ; nationality } ; canada }, interpretation: select the row whose pick record of all rows is 1st minimum . the nationality record of this row is canada . Output:
[ "yes" ]
task211-fa399bba1ec84a5caea721bb6620029c
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 ; first elected } ; 1953.5 }, interpretation: the average of the first elected record of all rows is 1953.5 . Output:
[ "yes" ]
task211-69cfc7f6e9394b679c1411490c93571c
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 ; class / type ; passenger ship } } ; eq { hop { filter_eq { all_rows ; class / type ; passenger ship } ; builder } ; john roach and son } }, interpretation: select the row whose pts record of all rows is maximum . the team record of this row is castres olympique . Output:
[ "no" ]
task211-eb11ae791d784a898b75f46387dae51c
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 ; tries for } ; club } ; bridgend ravens }, interpretation: select the row whose tries for record of all rows is maximum . the club record of this row is bridgend ravens . Output:
[ "yes" ]
task211-fa3ee4a5d4dd40259e46a304a7c1726a
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 ; founded } ; team } ; northern demons }, interpretation: select the row whose founded record of all rows is minimum . the team record of this row is northern demons . Output:
[ "yes" ]
task211-0df1e41b2df446cbb2dfd062340b2c4f
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 ; rank } ; name } ; environmental sustainability index }, interpretation: select the rows whose name record fuzzily matches to margravine johanna of baden - baden . take the became duchess record of this row . select the rows whose name record fuzzily matches to victoria of saxe - coburg and gotha . take the became duchess record of this row . the first record is less than the second record . Output:
[ "no" ]
task211-30365cc1c9b543f79c4bcd39e973a4d1
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 ; position ; m } ; pick ; 27 } } ; 3 }, interpretation: select the rows whose constructor record fuzzily matches to talbot - lago - talbot . among these rows , select the rows whose laps record is greater than 30 . the number of such rows is 5 . Output:
[ "no" ]
task211-a3eeb98519e14ec193832ffa4a9ebd9c
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 ; country ; zimbabwe } } ; eq { hop { filter_eq { all_rows ; country ; zimbabwe } ; player } ; nick price } }, interpretation: select the rows whose country record fuzzily matches to zimbabwe . there is only one such row in the table . the player record of this unqiue row is nick price . Output:
[ "yes" ]
task211-c83bf86250274142acf840f88bb093e2
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 ; date ; 6 june 2010 ( round 13 ) } ; total } ; hop { filter_eq { all_rows ; date ; 5 april 2008 ( round 4 ) } ; total } }, interpretation: select the rows whose nationality record fuzzily matches to aut . there is only one such row in the table . the name record of this unqiue row is gregor schlierenzauer . Output:
[ "no" ]
task211-abaa7b1b56c34a858bd23bf21d1331b5
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 ; president ; joão havelange } ; took office } ; hop { filter_eq { all_rows ; president ; sepp blatter } ; took office } }, interpretation: select the rows whose president record fuzzily matches to joão havelange . take the took office record of this row . select the rows whose president record fuzzily matches to sepp blatter . take the took office record of this row . the first record is less than the second record . Output:
[ "yes" ]
task211-3fcf3ae489324af0a1ff8d548b9791e5
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 { all_rows ; goal difference ; 0 } } ; 8 }, interpretation: select the rows whose goal difference record is less than 0 . the number of such rows is 8 . Output:
[ "yes" ]
task211-6193a16b05af4c25964cde6244d6ee73
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_greater { all_rows ; time ; 7:00:00 } } ; eq { hop { filter_greater { all_rows ; time ; 7:00:00 } ; country } ; iraq } }, interpretation: select the rows whose time record is greater than 7:00:00 . there is only one such row in the table . the country record of this unqiue row is iraq . Output:
[ "yes" ]
task211-074e5c42d5e14a78a4f0f1f5559ecc2a
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 ; language ; norwegian } } ; eq { hop { filter_eq { all_rows ; language ; norwegian } ; song } ; sommer i palma } }, interpretation: select the rows whose language record fuzzily matches to norwegian . there is only one such row in the table . the song record of this unqiue row is sommer i palma . Output:
[ "yes" ]
task211-f23db735d8c44510a3c69a84359efb8b
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 { filter_eq { all_rows ; surface ; clay } ; score } ; 7 }, interpretation: select the rows whose surface record fuzzily matches to clay . the sum of the score record of these rows is 7 . Output:
[ "yes" ]
task211-c40e764adbee43a196003a3f94c08038
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 ( lbs ) } ; 238.05 }, interpretation: the average of the weight ( lbs ) record of all rows is 238.05 . Output:
[ "yes" ]
task211-7af706478a42413f9ef8d346749e9968
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 ; years for jazz ; 2 } ; player } ; j j anderson }, interpretation: select the row whose years for jazz record of all rows is 2nd minimum . the player record of this row is j j anderson . Output:
[ "yes" ]
task211-2cfd092425be46a1b0056bb227312a78
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 ; turbines ; 1 } } ; eq { hop { filter_eq { all_rows ; turbines ; 1 } ; wind farm } ; glenough extension } }, interpretation: select the row whose location attendance record of all rows is maximum . the date record of this row is april 2 . Output:
[ "no" ]
task211-3e813b86539f4ebba17bbcfe1a3f2bb2
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 ; lebanon } ; total } ; hop { filter_eq { all_rows ; nation ; french community of belgium } ; total } }, interpretation: select the rows whose tournament record fuzzily matches to australia . the number of such rows is 5 . Output:
[ "no" ]
task211-f35f65d5235146d59135db254cd00c0e
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 ; uncut run time ; 2 } ; title } ; addio zio tom }, interpretation: select the row whose uncut run time record of all rows is 2nd maximum . the title record of this row is addio zio tom . Output:
[ "yes" ]
task211-378e6cd81c92455dbd1e41daab16664f
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 ; interregnum began ; 20 february 1790 death of joseph ii } ; duration } ; hop { filter_eq { all_rows ; interregnum began ; 1 march 1792 death of leopold ii } ; duration } }, interpretation: select the rows whose result record fuzzily matches to final . the number of such rows is 4 . Output:
[ "no" ]
task211-86bb344722e742cba8475bf44375cdf8
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 ; county ; mobile } } ; 3 }, interpretation: select the rows whose county record fuzzily matches to mobile . the number of such rows is 3 . Output:
[ "yes" ]
task211-77b1efacd92649f585fcef9eac1c9fe2
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 ; bronze } ; 1.7 }, interpretation: the average of the bronze record of all rows is 1.7 . Output:
[ "yes" ]
task211-83e6d044d06a40658be8f2cceb3136f4
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 ; ratings ; 1 } ; broadcast date } ; 14 august 2012 }, interpretation: select the row whose us viewers ( millions ) record of all rows is maximum . the original air date record of this row is november 7 , 2010 . Output:
[ "no" ]
task211-5bf003ebfe0447a8810f89e2acb2658a
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 ; winter olympics ; 2 } ; winner } ; thomas wassberg }, interpretation: select the row whose winter olympics record of all rows is 2nd maximum . the winner record of this row is thomas wassberg . Output:
[ "yes" ]
task211-f172bd7e62e3487cb131024f51131cb4
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 ; gold } ; 36 }, interpretation: select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is frank wolf . Output:
[ "no" ]
task211-dcccf1573cbc45c99fd7bc9de769579c
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 ; election ; 1988 } ; of total votes } ; hop { filter_eq { all_rows ; election ; 1993 } ; of total votes } }, interpretation: select the rows whose election record fuzzily matches to 1988 . take the of total votes record of this row . select the rows whose election record fuzzily matches to 1993 . take the of total votes record of this row . the first record is greater than the second record . Output:
[ "yes" ]
task211-8a6ce6394dfa459188a413c97f209767
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 } ; november 17 }, interpretation: select the rows whose sport record fuzzily matches to wrestling . the number of such rows is 2 . Output:
[ "no" ]
task211-3a520b316c7a4eafb2c1ac6f1aa954eb
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 ; age } ; 25.6 }, interpretation: select the row whose length record of all rows is maximum . the name record of this row is northern eagle . Output:
[ "no" ]
task211-55f984372bcb4af8b9f384ed0f491658