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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 rows whose height record fuzzily matches to 6 - 4 . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; height ; 6 - 4 } } ; 2 }" ]
task210-b313342039614609a769d9b1b58253ae
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 attendance record of all rows is 23350 . Output:
[ "round_eq { avg { all_rows ; attendance } ; 23350 }" ]
task210-643289a6b3384dd4bdb1d8e42f634f8a
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 imports record of all rows is maximum . the country record of this row is china . Output:
[ "eq { hop { argmax { all_rows ; imports } ; country } ; china }" ]
task210-f55437175d2148a6bad7ea1f44278b27
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 pieces record of all rows is 271.6 . Output:
[ "round_eq { avg { all_rows ; pieces } ; 271.6 }" ]
task210-4cadca37a9954849abec1c49a40ad8e6
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 3 - 5 . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; career win - loss ; 3 - 5 } } ; 2 }" ]
task210-ad61c5ddc6d64170a794af1bdd4d20d6
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 crowd record of all rows is 123128 . Output:
[ "round_eq { sum { all_rows ; crowd } ; 123128 }" ]
task210-c8787b42c57b4d878c2444cdfdd0432f
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 visitor record fuzzily matches to spurs . select the row whose attendance record of these rows is 1st maximum . the home record of this row is jazz . Output:
[ "eq { hop { nth_argmax { filter_eq { all_rows ; visitor ; spurs } ; attendance ; 1 } ; home } ; jazz }" ]
task210-484a323ce5d3488ba093900c9a49ddcc
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 1948 . the sum of the round record of these rows is 4 . Output:
[ "round_eq { sum { filter_eq { all_rows ; date ; 1948 } ; round } ; 4 }" ]
task210-9b0d0d6af97144d8b7267dbb13760a78
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 host record of this row is marty reid . Output:
[ "eq { hop { nth_argmax { all_rows ; year ; 2 } ; host } ; marty reid }" ]
task210-7b4c73bd4e5741d381c82b6fb9851dac
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 high points record of all rows is 29.5 . Output:
[ "round_eq { avg { all_rows ; high points } ; 29.5 }" ]
task210-92a2ee6a439e44ae9878bff0677137a8
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 minimum . the player record of this row is seve ballesteros . Output:
[ "eq { hop { argmin { all_rows ; total } ; player } ; seve ballesteros }" ]
task210-cde8079b2dc344e7b85cf9e786a095a4
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 original album record fuzzily matches to previously unreleased . among these rows , select the rows whose time record is greater than 4:00 . the number of such rows is 2 . Output:
[ "eq { count { filter_greater { filter_eq { all_rows ; original album ; previously unreleased } ; time ; 4:00 } } ; 2 }" ]
task210-2f97e03b9ec24a45aa1996383ba3fa57
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 canada . there is only one such row in the table . the champion record of this unqiue row is jessica shepley . Output:
[ "and { only { filter_eq { all_rows ; country ; canada } } ; eq { hop { filter_eq { all_rows ; country ; canada } ; champion } ; jessica shepley } }" ]
task210-af3515738ef44a089103c50f8c388b98
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 4th maximum points record of all rows is 6 . Output:
[ "eq { nth_max { all_rows ; points ; 4 } ; 6 }" ]
task210-2c16150c97a04f79ab01e12505022746
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 engine record fuzzily matches to offy . the number of such rows is 4 . Output:
[ "eq { count { filter_eq { all_rows ; engine ; offy } } ; 4 }" ]
task210-592633f6266544abbd8f12e41e03ca09
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 goals against record of all rows is maximum . the team record of this row is montreal crystals . Output:
[ "eq { hop { argmax { all_rows ; goals against } ; team } ; montreal crystals }" ]
task210-754a135b3c6e4b4aa618de466a54fa65
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 enrollment record of all rows is 2nd maximum . the name record of this row is orangeville district secondary school . Output:
[ "eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; name } ; orangeville district secondary school }" ]
task210-6c2f1534203b48bcaf653386eb11efb1
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 result record fuzzily matches to none . there is only one such row in the table . the week record of this unqiue row is 3 . Output:
[ "and { only { filter_eq { all_rows ; result ; none } } ; eq { hop { filter_eq { all_rows ; result ; none } ; week } ; 3 } }" ]
task210-11e19664bc2a4750a6c96b30434ec473
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 is greater than 15 . there is only one such row in the table . the year record of this unqiue row is 2005 . the competition record of this unqiue row is world youth championships . Output:
[ "and { only { filter_greater { all_rows ; position ; 15 } } ; and { eq { hop { filter_greater { all_rows ; position ; 15 } ; year } ; 2005 } ; eq { hop { filter_greater { all_rows ; position ; 15 } ; competition } ; world youth championships } } }" ]
task210-1f2b3f13d8884d6c9221ac5ec1438930
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 gold record of all rows is 70 . Output:
[ "round_eq { sum { all_rows ; gold } ; 70 }" ]
task210-decb4561fa6d45b8936ec66ee6bca3d4
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 record fuzzily matches to fleetcenter . the minimum date record of these rows is fri mar 1 . Output:
[ "eq { min { filter_eq { all_rows ; location ; fleetcenter } ; date } ; fri mar 1 }" ]
task210-3a8c0dcaa576490f89fd6b475dc69c0b
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 8 . Output:
[ "eq { count { filter_all { all_rows ; name } } ; 8 }" ]
task210-446e71d789764d0b8a9a539c340abf56
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 gold record is equal to 3 . select the row whose silver record of these rows is maximum . the nation record of this row is china . Output:
[ "eq { hop { argmax { filter_eq { all_rows ; gold ; 3 } ; silver } ; nation } ; china }" ]
task210-569522ddf8a14e51b316ad4e40b1edfc
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 try bonus record is equal to 1 . there is only one such row in the table . the club record of this unqiue row is cefn coed rfc . Output:
[ "and { only { filter_eq { all_rows ; try bonus ; 1 } } ; eq { hop { filter_eq { all_rows ; try bonus ; 1 } ; club } ; cefn coed rfc } }" ]
task210-fe6909f1c3f045dea07ddc596aa5aab4
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 attendance record of all rows is 16325 . Output:
[ "round_eq { avg { all_rows ; attendance } ; 16325 }" ]
task210-da7e66f25f5d4cc696d8140eb31c6131
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 planet type record fuzzily matches to ice giant . there is only one such row in the table . the planet record of this unqiue row is neptune . Output:
[ "and { only { filter_eq { all_rows ; planet type ; ice giant } } ; eq { hop { filter_eq { all_rows ; planet type ; ice giant } ; planet } ; neptune } }" ]
task210-c5319e3c15094fd5ad0c6805a0f4ca12
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 record fuzzily matches to tifton . there is only one such row in the table . the institution record of this unqiue row is abraham baldwin agricultural college . Output:
[ "and { only { filter_eq { all_rows ; location ; tifton } } ; eq { hop { filter_eq { all_rows ; location ; tifton } ; institution } ; abraham baldwin agricultural college } }" ]
task210-b4254d59c45b436982cba16449d87bb8
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 joined record of all rows is 1st maximum . the school record of this row is fishers . Output:
[ "eq { hop { nth_argmax { all_rows ; year joined ; 1 } ; school } ; fishers }" ]
task210-e7508e2abb574c008d9793aec765df60
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 round record of all rows is 3rd maximum . the player record of this row is tyree davis . Output:
[ "eq { hop { nth_argmax { all_rows ; round ; 3 } ; player } ; tyree davis }" ]
task210-2c7e609f7bb04847bc151c48517b30b9
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 w record is greater than 2 . the number of such rows is 2 . Output:
[ "eq { count { filter_greater { all_rows ; w ; 2 } } ; 2 }" ]
task210-9696e822a58d4119b81f2389e6e7ddd2
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 position record of all rows is 100 . Output:
[ "round_eq { avg { all_rows ; position } ; 100 }" ]
task210-f5605ba508f94964a6521b78888ed5df
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 minardi team usa . select the row whose laps record of these rows is maximum . the driver record of this row is robert doornbos . Output:
[ "eq { hop { argmax { filter_eq { all_rows ; team ; minardi team usa } ; laps } ; driver } ; robert doornbos }" ]
task210-54b3f98ebd3842a2a8741be2d59822ba
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 package / option records of all rows , most of them fuzzily match to no ( fta ) . Output:
[ "most_eq { all_rows ; package / option ; no ( fta ) }" ]
task210-77d3d27540814ff988b6730b0a6fe17c
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 january 29 . take the high points record of this row . select the rows whose date record fuzzily matches to january 1 . take the high points record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; date ; january 29 } ; high points } ; hop { filter_eq { all_rows ; date ; january 1 } ; high points } }" ]
task210-a9354cebceb9486e8934445638e5bc5e
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 10 june 2009 . take the competition record of this row . select the rows whose date record fuzzily matches to 5 september 2009 . take the competition record of this row . the first record fuzzily matches to the second record . the competition record of the first row is 2010 fifa world cup qualification . the competition record of the second row is 2010 fifa world cup qualification . Output:
[ "and { eq { hop { filter_eq { all_rows ; date ; 10 june 2009 } ; competition } ; hop { filter_eq { all_rows ; date ; 5 september 2009 } ; competition } } ; and { eq { hop { filter_eq { all_rows ; date ; 10 june 2009 } ; competition } ; 2010 fifa world cup qualification } ; eq { hop { filter_eq { all_rows ; date ; 5 september 2009 } ; competition } ; 2010 fifa world cup qualification } } }" ]
task210-047b9ab88b81455088637b1fe04e243a
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 8 , 1992 . take the date record of this row . select the rows whose date record fuzzily matches to november 22 , 1992 . take the date record of this row . the second record is 14 days larger than the first record . Output:
[ "eq { diff { hop { filter_eq { all_rows ; date ; november 8 , 1992 } ; date } ; hop { filter_eq { all_rows ; date ; november 22 , 1992 } ; date } } ; -14 days }" ]
task210-fe9d0b8599dd4c31a073c9fd94841e2f
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 score record of all rows is 29 . Output:
[ "round_eq { sum { all_rows ; score } ; 29 }" ]
task210-72edb038067948239f09872d71fc1164
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 category record fuzzily matches to arts . the number of such rows is 4 . Output:
[ "eq { count { filter_eq { all_rows ; category ; arts } } ; 4 }" ]
task210-246384fb218d4aab95e104e767a38db3
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 home team record fuzzily matches to manchester city . take the score record of this row . select the rows whose home team record fuzzily matches to arsenal . take the score record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; home team ; manchester city } ; score } ; hop { filter_eq { all_rows ; home team ; arsenal } ; score } }" ]
task210-d201caa28ec54641a972f61cd3b087b1
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 maximum . the team record of this row is alianza fc . Output:
[ "eq { hop { argmax { all_rows ; points } ; team } ; alianza fc }" ]
task210-45a10a2ff6a6451bb84669cf8e593f7a
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 product record fuzzily matches to grain . take the 2001 record of this row . select the rows whose product record fuzzily matches to timber . take the 2001 record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; product ; grain } ; 2001 } ; hop { filter_eq { all_rows ; product ; timber } ; 2001 } }" ]
task210-e250efa46e9e44efa1c90c8a6b20dfc8
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 points records of all rows , most of them are greater than 10 . Output:
[ "most_greater { all_rows ; points ; 10 }" ]
task210-f66e4ee5bb994f67b9bd9518c417e863
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 margin ( pts ) record of all rows is 27.25 . Output:
[ "round_eq { avg { all_rows ; margin ( pts ) } ; 27.25 }" ]
task210-8b4515de8fad42dbb8b932628eb3bc69
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 segment d record fuzzily matches to part 2 . there is only one such row in the table . the series ep record of this unqiue row is 4 - 04 . Output:
[ "and { only { filter_eq { all_rows ; segment d ; part 2 } } ; eq { hop { filter_eq { all_rows ; segment d ; part 2 } ; series ep } ; 4 - 04 } }" ]
task210-9f6606c6147a40c881a8dfc27258b336
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 original air date record fuzzily matches to august . select the row whose us viewers ( million ) record of these rows is 2nd maximum . the title record of this row is a little death . Output:
[ "eq { hop { nth_argmax { filter_eq { all_rows ; original air date ; august } ; us viewers ( million ) ; 2 } ; title } ; a little death }" ]
task210-59a576cd5dcb41209eaa20e0b44ba5cd
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 founded record is greater than or equal to 1980 . the number of such rows is 3 . Output:
[ "eq { count { filter_greater_eq { all_rows ; founded ; 1980 } } ; 3 }" ]
task210-600c654528a8498098632be1940a0cec
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 minimum . the name record of this row is tyson gay . Output:
[ "eq { hop { argmin { all_rows ; time } ; name } ; tyson gay }" ]
task210-a46579fdc8c6481e9a8d8c81ddabd306
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 october 10 . Output:
[ "eq { hop { argmax { all_rows ; attendance } ; date } ; october 10 }" ]
task210-03841f47c7d248b2b47ea95c52a9b071
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 college record fuzzily matches to utah . there is only one such row in the table . the name record of this unqiue row is dewey nelson . Output:
[ "and { only { filter_eq { all_rows ; college ; utah } } ; eq { hop { filter_eq { all_rows ; college ; utah } ; name } ; dewey nelson } }" ]
task210-dd36b5c001084304855778db085fbfd9
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 winning driver record fuzzily matches to craig baird . among these rows , select the rows whose location record fuzzily matches to melbourne , victoria . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { filter_eq { all_rows ; winning driver ; craig baird } ; location ; melbourne , victoria } } ; 2 }" ]
task210-e09d6cf064674397b816bed4ebf31fe8
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 number of electorates ( 2009 ) record of all rows is 2nd maximum . the name record of this row is susner . Output:
[ "eq { hop { nth_argmax { all_rows ; number of electorates ( 2009 ) ; 2 } ; name } ; susner }" ]
task210-05363d629aae4c62ae20ac175dd3ddf5
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 opponent record fuzzily matches to lee hasdell . take the round record of this row . select the rows whose opponent record fuzzily matches to zabir elbiev . take the round record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; opponent ; lee hasdell } ; round } ; hop { filter_eq { all_rows ; opponent ; zabir elbiev } ; round } }" ]
task210-09a736af4ae64f9fb34226159b31c832
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 bronze record is equal to 1 . the number of such rows is 3 . Output:
[ "eq { count { filter_eq { all_rows ; bronze ; 1 } } ; 3 }" ]
task210-75756e878c7d4a23bbaa909d7febfebd
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 jermaine o'neal . there is only one such row in the table . the team record of this unqiue row is new orleans . Output:
[ "and { only { filter_eq { all_rows ; high points ; jermaine o'neal } } ; eq { hop { filter_eq { all_rows ; high points ; jermaine o'neal } ; team } ; new orleans } }" ]
task210-746b4ff4123a42ff967414c604430f54
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 playoffs record fuzzily matches to league finals . there is only one such row in the table . the year record of this unqiue row is 1978 . Output:
[ "and { only { filter_eq { all_rows ; playoffs ; league finals } } ; eq { hop { filter_eq { all_rows ; playoffs ; league finals } ; year } ; 1978 } }" ]
task210-7f20d9f86a434ce5a0c0dabd74fe989b
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 built year record of all rows is 2nd minimum . the warship record of this row is covadonga . Output:
[ "eq { hop { nth_argmin { all_rows ; built year ; 2 } ; warship } ; covadonga }" ]
task210-42b7d43598fb498fa5c36e9bafbb3bba
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 prothrombin time records of all rows , most of them fuzzily match to unaffected . Output:
[ "most_eq { all_rows ; prothrombin time ; unaffected }" ]
task210-a9e7e5ed44ad442ea9fd0db55d438b0a
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 prize records of all rows , most of them are greater than 500,000 . Output:
[ "most_greater { all_rows ; prize ; 500,000 }" ]
task210-d3475bbcb343433bbb748995bbe7da32
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 cd & v . among these rows , select the rows whose name record fuzzily matches to yves leterme . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { filter_eq { all_rows ; party ; cd & v } ; name ; yves leterme } } ; 2 }" ]
task210-c0cbc21836f74de898cc0ac9ce514dec
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 score record of all rows is 143 . Output:
[ "round_eq { avg { all_rows ; score } ; 143 }" ]
task210-610c63ea49c24e3eb4eccd38425da5bc
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 elevation ( m ) record of all rows is maximum . the peak record of this row is galdhøpiggen . Output:
[ "eq { hop { argmax { all_rows ; elevation ( m ) } ; peak } ; galdhøpiggen }" ]
task210-6111808dab6c43459495eb356182206c
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 institution record fuzzily matches to boise state university . take the enrollment record of this row . select the rows whose institution record fuzzily matches to california state university , bakersfield . take the enrollment record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; institution ; boise state university } ; enrollment } ; hop { filter_eq { all_rows ; institution ; california state university , bakersfield } ; enrollment } }" ]
task210-0538efb384e04f9cb0f58dc825d2512c
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 opponent in the final record fuzzily matches to vasilis mazarakis . there is only one such row in the table . the date record of this unqiue row is 20 march 2007 . Output:
[ "and { only { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } ; date } ; 20 march 2007 } }" ]
task210-4feeb46cab5048e8b584feef1e723380
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 score record of all rows is 139 . Output:
[ "round_eq { avg { all_rows ; score } ; 139 }" ]
task210-2da29124d1aa403c889d114da3702e48
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 gold record of all rows is maximum . the nation record of this row is netherlands ( ned ) . Output:
[ "eq { hop { argmax { all_rows ; gold } ; nation } ; netherlands ( ned ) }" ]
task210-336b8e71a8c1444d94fec89cacba6d55
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 region record fuzzily matches to canada . there is only one such row in the table . the catalog record of this unqiue row is b001150702 . Output:
[ "and { only { filter_eq { all_rows ; region ; canada } } ; eq { hop { filter_eq { all_rows ; region ; canada } ; catalog } ; b001150702 } }" ]
task210-493db1bb4ab0479bb3be3bef0ece5c51
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 does not match to united states . there is only one such row in the table . the player record of this unqiue row is bob charles . Output:
[ "and { only { filter_not_eq { all_rows ; country ; united states } } ; eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; bob charles } }" ]
task210-81429ec8da644f45a5e13b51eecb86c1
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 october . the sum of the attendance record of these rows is 245,093 . Output:
[ "round_eq { sum { filter_eq { all_rows ; date ; october } ; attendance } ; 245,093 }" ]
task210-23e1215d7ea0422fa2ca68705cd4afaf
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 paul pierce . the number of such rows is 5 . Output:
[ "eq { count { filter_eq { all_rows ; high points ; paul pierce } } ; 5 }" ]
task210-94832740acaf471f9e391490105e940e
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 assists record fuzzily matches to kevin garnett . there is only one such row in the table . the date record of this unqiue row is december 21 . the team record of this unqiue row is new york . Output:
[ "and { only { filter_eq { all_rows ; high assists ; kevin garnett } } ; and { eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; date } ; december 21 } ; eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; team } ; new york } } }" ]
task210-70ec631be9dd4827b4795489f16711f3
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 result record fuzzily matches to selected . there is only one such row in the table . the week record of this unqiue row is wild card . Output:
[ "and { only { filter_eq { all_rows ; result ; selected } } ; eq { hop { filter_eq { all_rows ; result ; selected } ; week } ; wild card } }" ]
task210-02b204ce0424482c93001ba8f7addb7f
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 of villages record is less than 5 . there is only one such row in the table . the district record of this unqiue row is boe . Output:
[ "and { only { filter_less { all_rows ; no of villages ; 5 } } ; eq { hop { filter_less { all_rows ; no of villages ; 5 } ; district } ; boe } }" ]
task210-bd02f043b43e45de8dbdcdf0ddd8d15d
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 time record fuzzily matches to 12:00 pm . the number of such rows is 3 . Output:
[ "eq { count { filter_eq { all_rows ; time ; 12:00 pm } } ; 3 }" ]
task210-91f4d82435cc48ba87d662ed72c46481
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 name record of this row is pieter van den hoogenband . Output:
[ "eq { hop { nth_argmin { all_rows ; time ; 2 } ; name } ; pieter van den hoogenband }" ]
task210-c708bf9f16b540a19984338072081066
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 school colors record fuzzily matches to white . the number of such rows is 4 . Output:
[ "eq { count { filter_eq { all_rows ; school colors ; white } } ; 4 }" ]
task210-3c802a37a6e947deacf1ad1a08f6806e
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 born - died record of all rows is 2nd minimum . the name record of this row is sali berisha . Output:
[ "eq { hop { nth_argmin { all_rows ; born - died ; 2 } ; name } ; sali berisha }" ]
task210-057037a72c2242ccaca64d8295fc64dd
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 winnings record of all rows is maximum . the year record of this row is 2004 . Output:
[ "eq { hop { argmax { all_rows ; winnings } ; year } ; 2004 }" ]
task210-2d6e6839323a46299f440497ec4a75e2
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 maximum . the player record of this row is hal sutton . Output:
[ "eq { hop { argmax { all_rows ; total } ; player } ; hal sutton }" ]
task210-c5d07f3d36dd484b87a22a76e1528136
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 5th minimum track record of all rows is 5 . the song title record of the row with 5th minimum track record is crazy arms . Output:
[ "and { eq { nth_min { all_rows ; track ; 5 } ; 5 } ; eq { hop { nth_argmin { all_rows ; track ; 5 } ; song title } ; crazy arms } }" ]
task210-d9297aad0fa040cdab01c9ad5ae60bcc
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 guest record fuzzily matches to garry trudeau . there is only one such row in the table . the episode record of this unqiue row is 806 . Output:
[ "and { only { filter_eq { all_rows ; guest ; garry trudeau } } ; eq { hop { filter_eq { all_rows ; guest ; garry trudeau } ; episode } ; 806 } }" ]
task210-c5b15a007baa49d2a21ae182f4420cbf
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 school / club team record fuzzily matches to brigham young university . there is only one such row in the table . the player record of this unqiue row is tevita ofahengaue . Output:
[ "and { only { filter_eq { all_rows ; school / club team ; brigham young university } } ; eq { hop { filter_eq { all_rows ; school / club team ; brigham young university } ; player } ; tevita ofahengaue } }" ]
task210-2ae6d3d7feb54e1aa2a11a03e2f8ce62
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 candidate record fuzzily matches to ron strynadka . take the votes record of this row . select the rows whose candidate record fuzzily matches to patricia cordner . take the votes record of this row . the first record is less than the second record . Output:
[ "less { hop { filter_eq { all_rows ; candidate ; ron strynadka } ; votes } ; hop { filter_eq { all_rows ; candidate ; patricia cordner } ; votes } }" ]
task210-0bf2d24e95984358b4f1782229964fb1
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 embankment . the maximum height ( m ) record of these rows is 67.0 . Output:
[ "eq { max { filter_eq { all_rows ; type ; embankment } ; height ( m ) } ; 67.0 }" ]
task210-dd2d7f52c41e46a9a48526b2df4d7592
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 april . Output:
[ "all_eq { all_rows ; date ; april }" ]
task210-cc957ce737904a6296067e7457d26661
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 ( equipo ) record fuzzily matches to sporting san miguelito . take the won ( pg ) record of this row . select the rows whose team ( equipo ) record fuzzily matches to alianza . take the won ( pg ) record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; team ( equipo ) ; sporting san miguelito } ; won ( pg ) } ; hop { filter_eq { all_rows ; team ( equipo ) ; alianza } ; won ( pg ) } }" ]
task210-5f8918414b5a417390b80dd75f6f4144
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 outcome record fuzzily matches to runner - up . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; outcome ; runner - up } } ; 2 }" ]
task210-3479a5beba5c4e89ba56173f11001cc6
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 wins record is equal to 4 . among these rows , select the rows whose draws record is less than 4 . the number of such rows is 2 . Output:
[ "eq { count { filter_less { filter_eq { all_rows ; wins ; 4 } ; draws ; 4 } } ; 2 }" ]
task210-93a3d394d5744719a10c46ed8ed30284
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 club record fuzzily matches to swansea uplands rfc . take the tries for record of this row . select the rows whose club record fuzzily matches to trebanos rfc . take the tries for record of this row . the first record is less than the second record . Output:
[ "less { hop { filter_eq { all_rows ; club ; swansea uplands rfc } ; tries for } ; hop { filter_eq { all_rows ; club ; trebanos rfc } ; tries for } }" ]
task210-61435d6b3a0648c09768b0fc6150ddbb
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 private . the number of such rows is 12 . Output:
[ "eq { count { filter_eq { all_rows ; type ; private } } ; 12 }" ]
task210-3b4174bc22314176b5b2cdb914891fce
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 surface record fuzzily matches to clay . among these rows , select the rows whose week record fuzzily matches to may . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { filter_eq { all_rows ; surface ; clay } ; week ; may } } ; 2 }" ]
task210-ace77520f0ed4d0083380bb87ba304e5
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 gary springer . take the pick record of this row . select the rows whose player record fuzzily matches to rich congo . take the pick record of this row . the first record is less than the second record . Output:
[ "less { hop { filter_eq { all_rows ; player ; gary springer } ; pick } ; hop { filter_eq { all_rows ; player ; rich congo } ; pick } }" ]
task210-4c8fbf535b664d2f8b48e5ca7298e061
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 shuji kondo record fuzzily matches to kondo ( 0:33 ) . there is only one such row in the table . the block a record of this unqiue row is ryuji hijikata . Output:
[ "and { only { filter_eq { all_rows ; shuji kondo ; kondo ( 0:33 ) } } ; eq { hop { filter_eq { all_rows ; shuji kondo ; kondo ( 0:33 ) } ; block a } ; ryuji hijikata } }" ]
task210-eac23d4a2a714269bd09aeaedb33846b
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 ( s ) won record of all rows is maximum . the player record of this row is tiger woods . Output:
[ "eq { hop { argmax { all_rows ; year ( s ) won } ; player } ; tiger woods }" ]
task210-151d2f29d1274a36b8bc45a31a6c2562
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 10 . Output:
[ "eq { count { filter_all { all_rows ; name } } ; 10 }" ]
task210-982fc25ed1df4b4e8f3bbc25ae6690bc
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 kj choi . take the reset points record of this row . select the rows whose player record fuzzily matches to charles howell iii . take the reset points record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; player ; kj choi } ; reset points } ; hop { filter_eq { all_rows ; player ; charles howell iii } ; reset points } }" ]
task210-0c7a3c3526a84c55a984f3fc9be667d5
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 pts record of all rows is maximum . the entrant record of this row is leyton house march racing team . Output:
[ "eq { hop { argmax { all_rows ; pts } ; entrant } ; leyton house march racing team }" ]
task210-7bf7d6c3bfd6419cad710fff79043b25
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 owner record fuzzily matches to royal thai army . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; owner ; royal thai army } } ; 2 }" ]
task210-da0279742b4f41e5aaf8533698b2f503
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 vuelta record of all rows is 1.67 . Output:
[ "round_eq { avg { all_rows ; vuelta } ; 1.67 }" ]
task210-db0b5ce0d2604f8b8b952c5650fda1d5
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 maximum . the driver record of this row is toni teittinen . Output:
[ "eq { hop { argmax { all_rows ; year } ; driver } ; toni teittinen }" ]
task210-3e80ce39bb5a43f3900e293fe0d7ee9c
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 attendance record of all rows is 6999 . Output:
[ "round_eq { avg { all_rows ; attendance } ; 6999 }" ]
task210-15f0e16fcad849cbbacc0b6047a865c4