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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose production num record of all rows is maximum . the title record of this row is bosko 's fox hunt . Output:
[ "eq { hop { argmax { all_rows ; production num } ; title } ; bosko 's fox hunt }" ]
task210-6d1c690a2048455b97d6103515fdb6bc
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose nominee record fuzzily matches to anthony hopkins . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; nominee ; anthony hopkins } } ; 2 }" ]
task210-6f92807f686f4e749ab0a0f2b79acd37
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose competition record fuzzily matches to 1994 fifa world cup qualification . select the row whose date record of these rows is minimum . the venue record of this row is estadio rigoberto lópez , managua , nicaragua . Output:
[ "eq { hop { argmin { filter_eq { all_rows ; competition ; 1994 fifa world cup qualification } ; date } ; venue } ; estadio rigoberto lópez , managua , nicaragua }" ]
task210-f9ad6bf3f6a143f48db2c463a620536a
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose points record is greater than 270 . the number of such rows is 2 . Output:
[ "eq { count { filter_greater { all_rows ; points ; 270 } } ; 2 }" ]
task210-d94571947f0c4736b24e2f5c481981f0
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the average of the 1 - year peak record of all rows is 2869 . Output:
[ "round_eq { avg { all_rows ; 1 - year peak } ; 2869 }" ]
task210-fdfffdcd186d440b99301fd9cfaea169
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose seasons at this level record fuzzily matches to 27 seasons . for the settlements records of these rows , most of them fuzzily match to lisbon . Output:
[ "most_eq { filter_eq { all_rows ; seasons at this level ; 27 seasons } ; settlements ; lisbon }" ]
task210-10703ba1d53447e49b9bed4da614758f
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose us viewers ( in millions ) record is equal to 3.69 . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; us viewers ( in millions ) ; 3.69 } } ; 2 }" ]
task210-c2bbf5a7a10040d88e45d68be5a8bfaf
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose provider ( national government ) record fuzzily matches to ministry of defense . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; provider ( national government ) ; ministry of defense } } ; 2 }" ]
task210-4bb0573e6c944aa58bfb45fb1b6867f3
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the average of the round record of all rows is 2.3 . Output:
[ "round_eq { avg { all_rows ; round } ; 2.3 }" ]
task210-3a2f127889c442dcbf7b3b0f71068668
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose name record is arbitrary . the number of such rows is 12 . Output:
[ "eq { count { filter_all { all_rows ; name } } ; 12 }" ]
task210-7b8c024e14af48468f03afd142946b49
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the date records of all rows , all of them fuzzily match to january . Output:
[ "all_eq { all_rows ; date ; january }" ]
task210-61ef3b73ae0846e1a4b33fe248d837cc
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose winner record fuzzily matches to brad jones . the minimum date record of these rows is 26 - 27 apr . Output:
[ "eq { min { filter_eq { all_rows ; winner ; brad jones } ; date } ; 26 - 27 apr }" ]
task210-accaf82e15a24035baf729d61b59f826
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the sum of the attendance record of all rows is 1135404 . Output:
[ "round_eq { sum { all_rows ; attendance } ; 1135404 }" ]
task210-7e036fe33b3a47c8b1680d1e7af87486
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose total record is equal to 24 . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; total ; 24 } } ; 2 }" ]
task210-abc04ae1bd0f45728f4d0d70f9de106f
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the nominated work records of all rows , most of them fuzzily match to 71 : into the fire . Output:
[ "most_eq { all_rows ; nominated work ; 71 : into the fire }" ]
task210-73d6755de2f84901845030bddb800f4c
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose channel record is less than 10 . there is only one such row in the table . the callsign record of this unqiue row is wnbc . Output:
[ "and { only { filter_less { all_rows ; channel ; 10 } } ; eq { hop { filter_less { all_rows ; channel ; 10 } ; callsign } ; wnbc } }" ]
task210-c0b1cb0ff3a741258cab98aaaced10f6
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose role record fuzzily matches to guy holden . the number of such rows is 3 . Output:
[ "eq { count { filter_eq { all_rows ; role ; guy holden } } ; 3 }" ]
task210-f50e2f7ecf654de9a28ab43d47fe6842
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the high assists records of all rows , most of them fuzzily match to mike conley . Output:
[ "most_eq { all_rows ; high assists ; mike conley }" ]
task210-c7f314f713b6490699c6f2b23322be91
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose tournament record fuzzily matches to japan . select the row whose date record of these rows is 2nd minimum . the surface record of this row is carpet ( i ) . Output:
[ "eq { hop { nth_argmin { filter_eq { all_rows ; tournament ; japan } ; date ; 2 } ; surface } ; carpet ( i ) }" ]
task210-6b174eaeb901438592c6102441373c27
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose note record of all rows is maximum . the date record of this row is april 21 , 1980 . the format record of this row is stereo lp . Output:
[ "and { eq { hop { argmax { all_rows ; note } ; date } ; april 21 , 1980 } ; eq { hop { argmax { all_rows ; note } ; format } ; stereo lp } }" ]
task210-9eb48a48d6ec411d980606303dc8fa4d
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the population density ( per km square ) records of all rows , all of them are greater than 100 . Output:
[ "all_greater { all_rows ; population density ( per km square ) ; 100 }" ]
task210-864d671628ef4cfa8d3a84259ebb70df
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose venue record fuzzily matches to park . the maximum away team score record of these rows is 21.10 ( 136 ) . Output:
[ "eq { max { filter_eq { all_rows ; venue ; park } ; away team score } ; 21.10 ( 136 ) }" ]
task210-0e18a569144e4a8893c2cd50c5d01601
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose us viewers ( millions ) record of all rows is maximum . the no in series record of this row is 1 . Output:
[ "eq { hop { argmax { all_rows ; us viewers ( millions ) } ; no in series } ; 1 }" ]
task210-bf6fca744cca4ec0bccf26309ecf94db
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the result records of all rows , most of them fuzzily match to 2 . Output:
[ "most_eq { all_rows ; result ; 2 }" ]
task210-771003c4e47143e9b88a789efe14e87a
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose total offense record of all rows is maximum . the player record of this row is devin gardner . Output:
[ "eq { hop { argmax { all_rows ; total offense } ; player } ; devin gardner }" ]
task210-31547ebf9fa8405696b06d50e82eb7ed
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the writer records of all rows , all of them fuzzily match to mike bullen . Output:
[ "all_eq { all_rows ; writer ; mike bullen }" ]
task210-58fc3ece7fe644ea86f3010eb0efa8a9
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose player record fuzzily matches to jim farmer . take the no record of this row . select the rows whose player record fuzzily matches to derek fisher . take the no record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; player ; jim farmer } ; no } ; hop { filter_eq { all_rows ; player ; derek fisher } ; no } }" ]
task210-da22ec6538c0444b8277290596d5f7b0
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose type record fuzzily matches to fraternity . the number of such rows is 4 . Output:
[ "eq { count { filter_eq { all_rows ; type ; fraternity } } ; 4 }" ]
task210-4935970e849c43babd1df2e9ad0006b5
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the maximum frequency record of all rows is 1000 mhz . Output:
[ "eq { max { all_rows ; frequency } ; 1000 mhz }" ]
task210-10e4eb6c9ef4404e83df74a1ae4d8437
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the sum of the attendance record of all rows is 791,469 . Output:
[ "round_eq { sum { all_rows ; attendance } ; 791,469 }" ]
task210-7864a785c19443b9a8bc555e8b7d8685
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose time record of all rows is 2nd minimum . the athletes record of this row is mathieu goubel . Output:
[ "eq { hop { nth_argmin { all_rows ; time ; 2 } ; athletes } ; mathieu goubel }" ]
task210-4d75537b7564428aba1414e0131e7fad
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose avg attend record of all rows is 2nd maximum . the indoor year record of this row is 1978 . Output:
[ "eq { hop { nth_argmax { all_rows ; avg attend ; 2 } ; indoor year } ; 1978 }" ]
task210-28c113088ea04fcf8ca534b0b8a0103f
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose year record of all rows is 2nd maximum . the role record of this row is ahana sharma . Output:
[ "eq { hop { nth_argmax { all_rows ; year ; 2 } ; role } ; ahana sharma }" ]
task210-be1bca96b8d34dc282301d9bb8fcdc31
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose country record fuzzily matches to united states . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; country ; united states } } ; 2 }" ]
task210-d6b26a4d8908400494b50861f3584d6b
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the sum of the against record of all rows is 49 . Output:
[ "round_eq { sum { all_rows ; against } ; 49 }" ]
task210-668f1bc2ce504d99847e3b4beadab449
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose year record is equal to 2008 . among these rows , select the rows whose nominated / won record fuzzily matches to won . the number of such rows is 3 . Output:
[ "eq { count { filter_eq { filter_eq { all_rows ; year ; 2008 } ; nominated / won ; won } } ; 3 }" ]
task210-98085480fe8b45ddbb1c7fc9d4f3a3fd
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose chassis record fuzzily matches to brm p201 . take the year record of this row . select the rows whose chassis record fuzzily matches to hill gh1 . take the year record of this row . the first record is less than the second record . Output:
[ "less { hop { filter_eq { all_rows ; chassis ; brm p201 } ; year } ; hop { filter_eq { all_rows ; chassis ; hill gh1 } ; year } }" ]
task210-c61b5a41bc6d417fb86a7b05f61e6ce9
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose manufacturer record fuzzily matches to suzuki . the average of the laps record of these rows is 21.5 . Output:
[ "round_eq { avg { filter_eq { all_rows ; manufacturer ; suzuki } ; laps } ; 21.5 }" ]
task210-b3324cb75a4343aab8407b9eaa10bd3d
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose 2006 - 10 record of all rows is maximum . the state record of this row is bihar . Output:
[ "eq { hop { argmax { all_rows ; 2006 - 10 } ; state } ; bihar }" ]
task210-f287d6bf71c64f34b71d22bc0a623cd1
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose ngc number record fuzzily matches to 5823 . take the right ascension ( j2000 ) record of this row . select the rows whose ngc number record fuzzily matches to 5822 . take the right ascension ( j2000 ) record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; ngc number ; 5823 } ; right ascension ( j2000 ) } ; hop { filter_eq { all_rows ; ngc number ; 5822 } ; right ascension ( j2000 ) } }" ]
task210-1c294c49aa8641e9a65198b56d76d725
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the city records of all rows , most of them fuzzily match to los angeles , california . Output:
[ "most_eq { all_rows ; city ; los angeles , california }" ]
task210-90bcdb8c9cad4d49aed73f951c4d0800
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose event record fuzzily matches to 400 m h . the average of the notes record of these rows is 54.54 seconds . Output:
[ "round_eq { avg { filter_eq { all_rows ; event ; 400 m h } ; notes } ; 54.54 seconds }" ]
task210-09b38487e53041d6bf3279828e3aaa27
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose finish record of all rows is 2nd minimum . the year record of this row is 1967 . Output:
[ "eq { hop { nth_argmin { all_rows ; finish ; 2 } ; year } ; 1967 }" ]
task210-9085547e98414bdbb2ebcd4ffc59d517
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose total record of all rows is 2nd maximum . the nation record of this row is argentina . Output:
[ "eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; argentina }" ]
task210-dda5ff64f05c4f3ba8d0c3748cfdca53
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose reason for change record fuzzily matches to died . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; reason for change ; died } } ; 2 }" ]
task210-0e490cf6be67481bb05f9c1ac8fa06b5
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose championships record of all rows is 2nd maximum . the teams record of this row is new york nets . Output:
[ "eq { hop { nth_argmax { all_rows ; championships ; 2 } ; teams } ; new york nets }" ]
task210-0fbb7b0fa87744a48d1397ec23e96c7d
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose high points record fuzzily matches to al harrington . the number of such rows is 4 . Output:
[ "eq { count { filter_eq { all_rows ; high points ; al harrington } } ; 4 }" ]
task210-096597f7447a4d59aedea89f424a3285
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the gold records of all rows , most of them are equal to 0 . Output:
[ "most_eq { all_rows ; gold ; 0 }" ]
task210-390bcc83cd0e4dac92ccde2b9ee2db14
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose competition record does not match to friendly . there is only one such row in the table . Output:
[ "only { filter_not_eq { all_rows ; competition ; friendly } }" ]
task210-02e8bde208b74b1f9a46cea96b802cfb
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose established record of all rows is 2nd maximum . the league record of this row is ahl . Output:
[ "eq { hop { nth_argmax { all_rows ; established ; 2 } ; league } ; ahl }" ]
task210-6a7a7b449d4c4761aee49f745ff9625d
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is adelaide 36ers . Output:
[ "eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; adelaide 36ers }" ]
task210-2bab9bd1f7b14983a506cd53380adbd4
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose weight ( lb ) record is less than 200 . the number of such rows is 4 . Output:
[ "eq { count { filter_less { all_rows ; weight ( lb ) ; 200 } } ; 4 }" ]
task210-9dc31bd91bc642f398054a2c29ac1087
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose podiums record of all rows is maximum . the points record of this row is 357 . Output:
[ "eq { hop { argmax { all_rows ; podiums } ; points } ; 357 }" ]
task210-c6e8b5a6212541fd8530b6386b6be174
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the results records of all rows , most of them fuzzily match to re - elected . Output:
[ "most_eq { all_rows ; results ; re - elected }" ]
task210-20da3fda6bb94f3ba238e8d0027a19bd
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose away team record fuzzily matches to richmond . take the away team score record of this row . select the rows whose away team record fuzzily matches to swans . take the away team score record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; away team ; richmond } ; away team score } ; hop { filter_eq { all_rows ; away team ; swans } ; away team score } }" ]
task210-1138880dd16e4a43aa8e29f70f3fb505
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose party record fuzzily matches to democratic . select the row whose first elected record of these rows is minimum . the incumbent record of this row is charles edward bennett . Output:
[ "eq { hop { argmin { filter_eq { all_rows ; party ; democratic } ; first elected } ; incumbent } ; charles edward bennett }" ]
task210-87eabe10e630437b877881e2603ef715
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose label record fuzzily matches to atlantic records . among these rows , select the rows whose region record fuzzily matches to united states . the number of such rows is 4 . Output:
[ "eq { count { filter_eq { filter_eq { all_rows ; label ; atlantic records } ; region ; united states } } ; 4 }" ]
task210-6e4f1ca30c8a4235bfc2569f726c7165
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose position record fuzzily matches to tackle . for the round records of these rows , all of them are less than 7 . Output:
[ "all_less { filter_eq { all_rows ; position ; tackle } ; round ; 7 }" ]
task210-e3b6cccb38bb48afafec55bcd9d65e7c
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose date record fuzzily matches to november . among these rows , select the rows whose attendance record is greater than 60,000 . the number of such rows is 1 . Output:
[ "eq { count { filter_greater { filter_eq { all_rows ; date ; november } ; attendance ; 60,000 } } ; 1 }" ]
task210-abbcdcb347034c49b16c593ae0825b24
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose points record of all rows is 2nd maximum . the name record of this row is angelika buck / erich buck . Output:
[ "eq { hop { nth_argmax { all_rows ; points ; 2 } ; name } ; angelika buck / erich buck }" ]
task210-f787a0f9375e4faf93e6d8b09077c76b
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose total dismissals record is less than 10 . the sum of the total dismissals record of these rows is 8 . Output:
[ "round_eq { sum { filter_less { all_rows ; total dismissals ; 10 } ; total dismissals } ; 8 }" ]
task210-bb80ffae03244e9f869a09a855433ff1
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the total units sold records of all rows , most of them are greater than 1500000 . Output:
[ "most_greater { all_rows ; total units sold ; 1500000 }" ]
task210-2edb17c07fec4ce5900e8232c9462f98
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the sum of the round record of all rows is 26 . Output:
[ "round_eq { sum { all_rows ; round } ; 26 }" ]
task210-1e1e6414acfb47bcb31c6badaf8c2bbd
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the average of the wheels record of all rows is 120 . Output:
[ "round_eq { avg { all_rows ; wheels } ; 120 }" ]
task210-259dede2d8b84dbb96131b83d0801a8e
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose tournament record fuzzily matches to masters tournament . take the top - 25 record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the top - 25 record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 25 } ; hop { filter_eq { all_rows ; tournament ; pga championship } ; top - 25 } }" ]
task210-d3ee6d373c0643979e615f23722d12fe
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose attendance record of all rows is maximum . the date record of this row is december 14 , 1958 . Output:
[ "eq { hop { argmax { all_rows ; attendance } ; date } ; december 14 , 1958 }" ]
task210-7df2ebe09f45460d92789f956e98041c
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the shot pct records of all rows , most of them are less than 80 % . Output:
[ "most_less { all_rows ; shot pct ; 80 % }" ]
task210-3b319c2e32424d79a9ad10e4b0007405
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose height ( m ) record of all rows is 2nd maximum . the name record of this row is messeturm . Output:
[ "eq { hop { nth_argmax { all_rows ; height ( m ) ; 2 } ; name } ; messeturm }" ]
task210-22969a18577a4ac39b4d807111df7a7b
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose partnerships record fuzzily matches to younis khan / shoaib malik . take the runs ( balls ) record of this row . select the rows whose partnerships record fuzzily matches to gautam gambhir / virender sehwag . take the runs ( balls ) record of this row . the first record is less than the second record . Output:
[ "less { hop { filter_eq { all_rows ; partnerships ; younis khan / shoaib malik } ; runs ( balls ) } ; hop { filter_eq { all_rows ; partnerships ; gautam gambhir / virender sehwag } ; runs ( balls ) } }" ]
task210-601d88f988684aa7b1838313d098750b
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose member countries record fuzzily matches to sweden . take the population record of this row . select the rows whose member countries record fuzzily matches to austria . take the population record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; member countries ; sweden } ; population } ; hop { filter_eq { all_rows ; member countries ; austria } ; population } }" ]
task210-6a51781ef6a8489284b906180e19ee98
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose ties record is equal to 1 . the number of such rows is 3 . Output:
[ "eq { count { filter_eq { all_rows ; ties ; 1 } } ; 3 }" ]
task210-79a93a638c0447519a4d6e1369b98262
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose player record fuzzily matches to jack kemp ( la ) . take the yards record of this row . select the rows whose player record fuzzily matches to tom flores ( oak ) . take the yards record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; player ; jack kemp ( la ) } ; yards } ; hop { filter_eq { all_rows ; player ; tom flores ( oak ) } ; yards } }" ]
task210-58b74c2f79b7407f81d1a58fcf0144c6
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose official name record fuzzily matches to madawaska . take the area km 2 record of this row . select the rows whose official name record fuzzily matches to baker brook . take the area km 2 record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; official name ; madawaska } ; area km 2 } ; hop { filter_eq { all_rows ; official name ; baker brook } ; area km 2 } }" ]
task210-87722a382a914c11b001c9542a24c83a
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose position record fuzzily matches to 7th . there is only one such row in the table . the competition record of this unqiue row is 58th national sports festival of japan . Output:
[ "and { only { filter_eq { all_rows ; position ; 7th } } ; eq { hop { filter_eq { all_rows ; position ; 7th } ; competition } ; 58th national sports festival of japan } }" ]
task210-f609249806194530bdcec179030c625c
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose genre record fuzzily matches to period drama . there is only one such row in the table . the english title ( chinese title ) record of this unqiue row is old time buddy - to catch a thief 難兄難弟之神探李奇 . Output:
[ "and { only { filter_eq { all_rows ; genre ; period drama } } ; eq { hop { filter_eq { all_rows ; genre ; period drama } ; english title ( chinese title ) } ; old time buddy - to catch a thief 難兄難弟之神探李奇 } }" ]
task210-5009d7eb51664f9593f2bc9f6220a7f4
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the socialist ticket records of all rows , most of them fuzzily match to man . Output:
[ "most_eq { all_rows ; socialist ticket ; man }" ]
task210-22a0c64dfa1e43cd977b8eb0e45b992e
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose championship record fuzzily matches to us open . the number of such rows is 6 . Output:
[ "eq { count { filter_eq { all_rows ; championship ; us open } } ; 6 }" ]
task210-5943a876d42546d89b6ed377adb35212
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose winner record fuzzily matches to luke youlden . there is only one such row in the table . the race title record of this unqiue row is mallala . Output:
[ "and { only { filter_eq { all_rows ; winner ; luke youlden } } ; eq { hop { filter_eq { all_rows ; winner ; luke youlden } ; race title } ; mallala } }" ]
task210-ffdfc5a79b9e42b5aaeac748c5ed761b
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose team record fuzzily matches to ulrich . select the row whose year record of these rows is maximum . the start record of this row is 33 . Output:
[ "eq { hop { argmax { filter_eq { all_rows ; team ; ulrich } ; year } ; start } ; 33 }" ]
task210-34ead696da064bab909e8720d3dc5232
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose ties record of all rows is maximum . the season record of this row is 2011 . Output:
[ "eq { hop { argmax { all_rows ; ties } ; season } ; 2011 }" ]
task210-c4c78619881846a3a2be9726fdb51fcd
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the average of the result record of all rows is 10.15 th . Output:
[ "round_eq { avg { all_rows ; result } ; 10.15 th }" ]
task210-fa85a3e4b2f24bd99801dbe4b9ac3bc7
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose tv station ( operator ) record fuzzily matches to modernine tv . take the 2005 record of this row . select the rows whose tv station ( operator ) record fuzzily matches to nbt . take the 2005 record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; tv station ( operator ) ; modernine tv } ; 2005 } ; hop { filter_eq { all_rows ; tv station ( operator ) ; nbt } ; 2005 } }" ]
task210-997127805bee4382880031c2b2275b97
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose total record of all rows is 1st maximum . the nation record of this row is china . Output:
[ "eq { hop { nth_argmax { all_rows ; total ; 1 } ; nation } ; china }" ]
task210-be7374b498584257b1f4c4f931896d4c
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the team records of all rows , most of them fuzzily match to triple eight race engineering . Output:
[ "most_eq { all_rows ; team ; triple eight race engineering }" ]
task210-ee529e6d23bc4d4fb4156a71cf17b707
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose population record of all rows is 1st maximum . the official name record of this row is chipman . Output:
[ "eq { hop { nth_argmax { all_rows ; population ; 1 } ; official name } ; chipman }" ]
task210-b718ac537d17468f9e7fa2176a8036f5
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose country record fuzzily matches to australia . there is only one such row in the table . the player record of this unqiue row is david graham . Output:
[ "and { only { filter_eq { all_rows ; country ; australia } } ; eq { hop { filter_eq { all_rows ; country ; australia } ; player } ; david graham } }" ]
task210-ad24b610ccab4e76b1065242460ac81c
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose foundation record of all rows is maximum . the organization record of this row is radiotelevisión del principado de asturias ( rtpa ) . Output:
[ "eq { hop { argmax { all_rows ; foundation } ; organization } ; radiotelevisión del principado de asturias ( rtpa ) }" ]
task210-8db6bb4653cb4983abbcf3f5c456b09f
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose host location record fuzzily matches to plainview , tx . there is only one such row in the table . the year record of this unqiue row is 1952 . Output:
[ "and { only { filter_eq { all_rows ; host location ; plainview , tx } } ; eq { hop { filter_eq { all_rows ; host location ; plainview , tx } ; year } ; 1952 } }" ]
task210-3ceb2d7d1eda4ba9a6b0e6d6b31303bd
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose first place record is equal to 0 . the number of such rows is 3 . Output:
[ "eq { count { filter_eq { all_rows ; first place ; 0 } } ; 3 }" ]
task210-b9c10bbd5e26489a83da423264963e36
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the average of the cuts made record of all rows is 4 . Output:
[ "round_eq { avg { all_rows ; cuts made } ; 4 }" ]
task210-d066a86d32794a6a862bf32087f51568
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose career win - loss record fuzzily matches to 2 - . there is only one such row in the table . the tournament record of this unqiue row is us open . Output:
[ "and { only { filter_eq { all_rows ; career win - loss ; 2 - } } ; eq { hop { filter_eq { all_rows ; career win - loss ; 2 - } ; tournament } ; us open } }" ]
task210-06cb7a37d36645309c37294707a221fd
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose attendance record is greater than 50000 . among these rows , select the rows whose date record fuzzily matches to december . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { filter_greater { all_rows ; attendance ; 50000 } ; date ; december } } ; 2 }" ]
task210-8bca887a833249608c796dca57d62ee9
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the average of the stations served record of all rows is 17.5 . Output:
[ "round_eq { avg { all_rows ; stations served } ; 17.5 }" ]
task210-f75dc1a98eac40bf83ffa9a438c603ca
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose no in season record fuzzily matches to 1 / 2 . take the us viewers ( million ) record of this row . select the rows whose no in season record fuzzily matches to 16 . take the us viewers ( million ) record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; no in season ; 1 / 2 } ; us viewers ( million ) } ; hop { filter_eq { all_rows ; no in season ; 16 } ; us viewers ( million ) } }" ]
task210-07534e6377c24d3b81d79dcfaa799b5f
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose round of 16 record does not match to did not advance . the number of such rows is 4 . Output:
[ "eq { count { filter_not_eq { all_rows ; round of 16 ; did not advance } } ; 4 }" ]
task210-eac4ec0c92004214bf5078bd093177cb
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose location attendance record fuzzily matches to us airways center 18422 . the number of such rows is 7 . Output:
[ "eq { count { filter_eq { all_rows ; location attendance ; us airways center 18422 } } ; 7 }" ]
task210-bd5ef1f0c90248c7949be42faec1d278
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose island record fuzzily matches to hawaii . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; island ; hawaii } } ; 2 }" ]
task210-42e3cc991dee4ca290807be9b745d239
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the engine records of all rows , most of them fuzzily match to v8 . Output:
[ "most_eq { all_rows ; engine ; v8 }" ]
task210-30db39890db6499d839034b08c6071f3
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose goal difference record of all rows is 3rd maximum . the club record of this row is real murcia . Output:
[ "eq { hop { nth_argmax { all_rows ; goal difference ; 3 } ; club } ; real murcia }" ]
task210-280bd2ba82ac4b61bd41cbfb09ad1160
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 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: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose gymnast record fuzzily matches to kor . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; gymnast ; kor } } ; 2 }" ]
task210-4d7b5ed1302a443193df984ccffdb0a2