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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is melbourne . Output:
[ "eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; melbourne }" ]
task210-92824f2584944ad2887c53b32e64bdea
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 carpet . there is only one such row in the table . the date record of this unqiue row is 28 october 2007 . Output:
[ "and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; 28 october 2007 } }" ]
task210-7b741e475f634dc297435f827f61efb8
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 manner of departure record fuzzily matches to resigned . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; manner of departure ; resigned } } ; 2 }" ]
task210-29da5ee86e0c400fa69b977f97a07a1e
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 athlete record of this row is yane marques . Output:
[ "eq { hop { argmax { all_rows ; total } ; athlete } ; yane marques }" ]
task210-f31289c2aa874ad7ac80096c05a4d4fa
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 introduced record fuzzily matches to june . the number of such rows is 5 . Output:
[ "eq { count { filter_eq { all_rows ; date introduced ; june } } ; 5 }" ]
task210-e3992c9c9a45464d9dd4d0e3e77c1093
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 2nd venue record fuzzily matches to mexico city . there is only one such row in the table . the year record of this unqiue row is 2007 . Output:
[ "and { only { filter_eq { all_rows ; 2nd venue ; mexico city } } ; eq { hop { filter_eq { all_rows ; 2nd venue ; mexico city } ; year } ; 2007 } }" ]
task210-ddc598c811924ebab56922c869db1743
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 opponent record of this row is denver broncos . Output:
[ "eq { hop { argmax { all_rows ; attendance } ; opponent } ; denver broncos }" ]
task210-b09ec4befc104162b31c43a3d46c56e8
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 designer , year records of all rows , most of them are less than 1950 . Output:
[ "most_less { all_rows ; designer , year ; 1950 }" ]
task210-4d75ee39452c47eaae5f9ed928e4e852
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose weight ( kg ) record is equal to 53 . there is only one such row in the table . Output:
[ "only { filter_eq { all_rows ; weight ( kg ) ; 53 } }" ]
task210-409bf329a1f54c4889e322c7f851078a
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the maximum score record of all rows is l 83 - 74 . the date record of the row with superlative score record is february 5 . Output:
[ "and { eq { max { all_rows ; score } ; l 83 - 74 } ; eq { hop { argmax { all_rows ; score } ; date } ; february 5 } }" ]
task210-1fdbbeccc7794851bece89ae58c5e38d
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 parishes record is greater than 60 . among these rows , select the rows whose high schools record is less than 5 . the number of such rows is 2 . Output:
[ "eq { count { filter_less { filter_greater { all_rows ; parishes ; 60 } ; high schools ; 5 } } ; 2 }" ]
task210-fd42acd88e5e4ab2a34c63f20809b870
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 is arbitrary . the number of such rows is 17 . Output:
[ "eq { count { filter_all { all_rows ; institution } } ; 17 }" ]
task210-819c09bf7af24fde8904d23ed9cfba00
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 newcomer . there is only one such row in the table . the year record of this unqiue row is 2008 . the result record of this unqiue row is won . Output:
[ "and { only { filter_eq { all_rows ; category ; newcomer } } ; and { eq { hop { filter_eq { all_rows ; category ; newcomer } ; year } ; 2008 } ; eq { hop { filter_eq { all_rows ; category ; newcomer } ; result } ; won } } }" ]
task210-a7c53a57c80740d1b698f4045ed54fe6
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 nominated / won record fuzzily matches to won . the 2nd minimum year record of these rows is 2008 . Output:
[ "eq { nth_min { filter_eq { all_rows ; nominated / won ; won } ; year ; 2 } ; 2008 }" ]
task210-82f28a82f42b49189aae78ec45ee6751
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose venue record fuzzily matches to home . the number of such rows is 4 . Output:
[ "eq { count { filter_eq { all_rows ; venue ; home } } ; 4 }" ]
task210-eeb4a340c6674ec7b9329565ca664230
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 location attendance record of all rows is maximum . the date record of this row is january 11 . Output:
[ "eq { hop { argmax { all_rows ; location attendance } ; date } ; january 11 }" ]
task210-7c9c219d5b1447848b33204271ecab59
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose first member record fuzzily matches to john ivatt briscoe . take the election record of this row . select the rows whose first member record fuzzily matches to peter john locke king . take the election record of this row . the first record is less than the second record . Output:
[ "less { hop { filter_eq { all_rows ; first member ; john ivatt briscoe } ; election } ; hop { filter_eq { all_rows ; first member ; peter john locke king } ; election } }" ]
task210-c3cc0157d05e49088261ec7e5da3c141
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose population record of all rows is 3rd maximum . the english name record of this row is suibin county . Output:
[ "eq { hop { nth_argmax { all_rows ; population ; 3 } ; english name } ; suibin county }" ]
task210-b6f404e065884456830e2187336e7854
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose round record is equal to 2 . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; round ; 2 } } ; 2 }" ]
task210-3358c6d3f0c74d8c966271110a113a2b
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 nationality record fuzzily matches to united states . there is only one such row in the table . Output:
[ "only { filter_eq { all_rows ; nationality ; united states } }" ]
task210-eaa90e8cf061423d992924d259743e6f
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 studio host record fuzzily matches to craig mustard . the number of such rows is 5 . Output:
[ "eq { count { filter_eq { all_rows ; studio host ; craig mustard } } ; 5 }" ]
task210-5c09ff32930c4c43a66212579443f71f
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the total records of all rows , most of them are less than 300 . Output:
[ "most_less { all_rows ; total ; 300 }" ]
task210-faf782885c524d1ba6fd1d4f5959be0e
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 ty warren . take the round record of this row . select the rows whose player record fuzzily matches to dan klecko . take the round record of this row . the first record is less than the second record . Output:
[ "less { hop { filter_eq { all_rows ; player ; ty warren } ; round } ; hop { filter_eq { all_rows ; player ; dan klecko } ; round } }" ]
task210-4799befad93144b28a311163e40c84fc
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 jeff urban . take the pick record of this row . select the rows whose player record fuzzily matches to chris george . take the pick record of this row . the first record is greater than the second record . the pick record of the first row is 41 . the pick record of the second row is 31 . Output:
[ "and { greater { hop { filter_eq { all_rows ; player ; jeff urban } ; pick } ; hop { filter_eq { all_rows ; player ; chris george } ; pick } } ; and { eq { hop { filter_eq { all_rows ; player ; jeff urban } ; pick } ; 41 } ; eq { hop { filter_eq { all_rows ; player ; chris george } ; pick } ; 31 } } }" ]
task210-9761ddb1712e40e5a045b85e3e3c56d9
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 first season record of all rows is maximum . the club record of this row is godoy cruz . Output:
[ "eq { hop { argmax { all_rows ; first season } ; club } ; godoy cruz }" ]
task210-74ddd7a4d9fa444faf697d1ef3ea9819
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 chassis record of this row is ags jh25b ags jh27 . Output:
[ "eq { hop { argmax { all_rows ; year } ; chassis } ; ags jh25b ags jh27 }" ]
task210-c6543c889544454fb6d91a5e187389d4
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 position records of all rows , most of them fuzzily match to tackle . Output:
[ "most_eq { all_rows ; position ; tackle }" ]
task210-26ccecce5f0d44ef9ab0788c4a0c39e5
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 races record is equal to 20 . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; races ; 20 } } ; 2 }" ]
task210-4c66bcc172794f80936864fd1bd5a3df
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 fatalities record of all rows is maximum . the name record of this row is 1990 manjil - rudbar earthquake . Output:
[ "eq { hop { argmax { all_rows ; fatalities } ; name } ; 1990 manjil - rudbar earthquake }" ]
task210-e4c9a2b9c2684780b44a7a2fb424a0e9
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose crowd record of all rows is maximum . the home team record of this row is carlton . the away team record of this row is richmond . Output:
[ "and { eq { hop { argmax { all_rows ; crowd } ; home team } ; carlton } ; eq { hop { argmax { all_rows ; crowd } ; away team } ; richmond } }" ]
task210-65c2beb199a04029b8d54add98f21ad5
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 first elected record of all rows is 1996 . Output:
[ "round_eq { avg { all_rows ; first elected } ; 1996 }" ]
task210-6a3b56aa06044dd7b7100531524c0222
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose position record fuzzily matches to cornerback . the average of the overall record of these rows is 41 . Output:
[ "round_eq { avg { filter_eq { all_rows ; position ; cornerback } ; overall } ; 41 }" ]
task210-2121f42ce1634a36a78948500f708c38
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose us viewers ( million ) record is equal to 5.5 . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; us viewers ( million ) ; 5.5 } } ; 2 }" ]
task210-25bda9b9ca7244639028aa468d7b3e7a
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 from record of all rows is 1st minimum . the player record of this row is jim pollard . Output:
[ "eq { hop { nth_argmin { all_rows ; from ; 1 } ; player } ; jim pollard }" ]
task210-61ffd2e9f1fe47e8995bbb93cdea1452
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 rank record is less than or equal to 3 . the average of the time record of these rows is 7:30.63 . Output:
[ "round_eq { avg { filter_less_eq { all_rows ; rank ; 3 } ; time } ; 7:30.63 }" ]
task210-38c1827687904760914729d07fa90791
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 eternacom . there is only one such row in the table . the frequency record of this unqiue row is 103.5 fm . Output:
[ "and { only { filter_eq { all_rows ; owner ; eternacom } } ; eq { hop { filter_eq { all_rows ; owner ; eternacom } ; frequency } ; 103.5 fm } }" ]
task210-9c66e600efa742189db5c75003a9bb86
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 goals record is equal to 23 . there is only one such row in the table . the player record of this unqiue row is mehmet yılmaz . Output:
[ "and { only { filter_eq { all_rows ; goals ; 23 } } ; eq { hop { filter_eq { all_rows ; goals ; 23 } ; player } ; mehmet yılmaz } }" ]
task210-f0e6cc1c150a4ea685a301908d25f80c
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 hastings college . there is only one such row in the table . the player record of this unqiue row is adam kossack . Output:
[ "and { only { filter_eq { all_rows ; college ; hastings college } } ; eq { hop { filter_eq { all_rows ; college ; hastings college } ; player } ; adam kossack } }" ]
task210-605535a5f58345bb8d0a9774c835588c
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 fitzroy . take the home team score record of this row . select the rows whose home team record fuzzily matches to north melbourne . take the home team score record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; home team ; fitzroy } ; home team score } ; hop { filter_eq { all_rows ; home team ; north melbourne } ; home team score } }" ]
task210-b04ced7a52044b60823e11bca328dc0b
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 equal to 0 . Output:
[ "most_eq { all_rows ; points ; 0 }" ]
task210-4cd902597c5a4f98a398ed6d4b2cde29
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 july 2010 . there is only one such row in the table . Output:
[ "only { filter_eq { all_rows ; date ; july 2010 } }" ]
task210-1358eb12a13340479c0ecaa960a51d71
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose venue record fuzzily matches to roker park . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; venue ; roker park } } ; 2 }" ]
task210-015f34822ed746a49bdbc7bf8e5fb9cc
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 floors record of all rows is 24.6 . Output:
[ "round_eq { avg { all_rows ; floors } ; 24.6 }" ]
task210-d7214288a70f43e6af07179a0f5f0ae0
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 arkansas state . there is only one such row in the table . the name record of this unqiue row is robert speer . Output:
[ "and { only { filter_eq { all_rows ; college ; arkansas state } } ; eq { hop { filter_eq { all_rows ; college ; arkansas state } ; name } ; robert speer } }" ]
task210-4e35defea30a4173a1fde4412b32ad36
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 crowd record of all rows is 22250 . Output:
[ "round_eq { avg { all_rows ; crowd } ; 22250 }" ]
task210-1ac29c4c850f48059e8491dee0686617
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose first aired record fuzzily matches to or . there is only one such row in the table . the episode title record of this unqiue row is the great american melting pot . Output:
[ "and { only { filter_eq { all_rows ; first aired ; or } } ; eq { hop { filter_eq { all_rows ; first aired ; or } ; episode title } ; the great american melting pot } }" ]
task210-b9679f75b45843d58b7f1a467482d2ff
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 airdate record fuzzily matches to may . there is only one such row in the table . the episode title record of this unqiue row is secret soviet bases . Output:
[ "and { only { filter_eq { all_rows ; original airdate ; may } } ; eq { hop { filter_eq { all_rows ; original airdate ; may } ; episode title } ; secret soviet bases } }" ]
task210-c168bc9deace491d9fa1bb54671bb522
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 summary record fuzzily matches to runners - up . among these rows , select the rows whose losses record is equal to 11 . there is only one such row in the table . the year record of this unqiue row is 2012 . Output:
[ "and { only { filter_eq { filter_eq { all_rows ; summary ; runners - up } ; losses ; 11 } } ; eq { hop { filter_eq { filter_eq { all_rows ; summary ; runners - up } ; losses ; 11 } ; year } ; 2012 } }" ]
task210-c852413f7a19477aacca780ca453f6e3
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 game site record fuzzily matches to rca dome . select the row whose date record of these rows is 4th minimum . the attendance record of this row is 56860 . Output:
[ "eq { hop { nth_argmin { filter_eq { all_rows ; game site ; rca dome } ; date ; 4 } ; attendance } ; 56860 }" ]
task210-656048441f1a486fb73c1b6fbcc4e1b3
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 0 . the number of such rows is 4 . Output:
[ "eq { count { filter_eq { all_rows ; gold ; 0 } } ; 4 }" ]
task210-735512ea55e441f1ba6b6294e0a153ae
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 crowd record of all rows is 18,333.33 . Output:
[ "round_eq { avg { all_rows ; crowd } ; 18,333.33 }" ]
task210-b4f5a2ae62c94abebd5f7cb7364fd5b6
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 frequency records of all rows , most of them fuzzily match to 00 9 . Output:
[ "most_eq { all_rows ; frequency ; 00 9 }" ]
task210-fe510bf6fd954439a74a4508b5c39933
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 title record fuzzily matches to family quarrel . take the air date record of this row . select the rows whose title record fuzzily matches to the award . take the air date record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; title ; family quarrel } ; air date } ; hop { filter_eq { all_rows ; title ; the award } ; air date } }" ]
task210-24c607501a444048b5fafe4b29fb2f62
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 may . for the directed by records of these rows , most of them fuzzily match to gary halvorson . Output:
[ "most_eq { filter_eq { all_rows ; original air date ; may } ; directed by ; gary halvorson }" ]
task210-6e5edfbd1f1d4eaca47f2cf4377e53d7
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 wins record of all rows is 1.43 . Output:
[ "round_eq { avg { all_rows ; wins } ; 1.43 }" ]
task210-805580314e204139a8cdd85dea400215
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 opened record of all rows is maximum . the name record of this row is ben 10 - ultimate mission . Output:
[ "eq { hop { argmax { all_rows ; opened } ; name } ; ben 10 - ultimate mission }" ]
task210-0dea4ade168b4097bd47d46355a2cd54
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 constructor record fuzzily matches to minardi - cosworth . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; constructor ; minardi - cosworth } } ; 2 }" ]
task210-370d129c17e74258b4e9d0653ee74672
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 adam voges . take the runs record of this row . select the rows whose player record fuzzily matches to callum ferguson . take the runs record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; player ; adam voges } ; runs } ; hop { filter_eq { all_rows ; player ; callum ferguson } ; runs } }" ]
task210-330b040ed842460cb8c9be369e78c8e3
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 maynard evans hs . there is only one such row in the table . the player record of this unqiue row is darryl dawkins . Output:
[ "and { only { filter_eq { all_rows ; school / club team ; maynard evans hs } } ; eq { hop { filter_eq { all_rows ; school / club team ; maynard evans hs } ; player } ; darryl dawkins } }" ]
task210-42a96e53f7ac49d0bb939a4de77f2193
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 director record fuzzily matches to hassard short . there is only one such row in the table . the date record of this unqiue row is june 3 , 1931 . Output:
[ "and { only { filter_eq { all_rows ; director ; hassard short } } ; eq { hop { filter_eq { all_rows ; director ; hassard short } ; date } ; june 3 , 1931 } }" ]
task210-c9947250bb2d4bd098bf1d5db6dea49e
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 2006 - 10 record is equal to 0.29 . the number of such rows is 3 . Output:
[ "eq { count { filter_eq { all_rows ; 2006 - 10 ; 0.29 } } ; 3 }" ]
task210-7943f0669d1b4bc8963f315fdd55467d
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 september . the sum of the attendance record of these rows is under 200,000 . Output:
[ "round_eq { sum { filter_eq { all_rows ; date ; september } ; attendance } ; under 200,000 }" ]
task210-8aa97e432969418f90806e4587446afd
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 annual payroll ( 1000 ) record of all rows is 3,521,267,581 . Output:
[ "round_eq { sum { all_rows ; annual payroll ( 1000 ) } ; 3,521,267,581 }" ]
task210-965520ad931946829facdd906e82cf72
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 prize money ( usd ) record is less than 25000 . there is only one such row in the table . the name record of this unqiue row is jan kodeå ¡ . Output:
[ "and { only { filter_less { all_rows ; prize money ( usd ) ; 25000 } } ; eq { hop { filter_less { all_rows ; prize money ( usd ) ; 25000 } ; name } ; jan kodeå ¡ } }" ]
task210-efaed0cfa9e7488abdc32fe80ec63b53
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 14 . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { all_rows ; wins ; 14 } } ; 2 }" ]
task210-4277da7a221c4945a9f72cd21a29a790
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the high assists records of all rows , most of them fuzzily match to lebron james . Output:
[ "most_eq { all_rows ; high assists ; lebron james }" ]
task210-d9456d85a85b4039a2b3561e0ffc5689
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 2nd evening record fuzzily matches to n / a . the number of such rows is 3 . Output:
[ "eq { count { filter_eq { all_rows ; 2nd evening ; n / a } } ; 3 }" ]
task210-ab51e9b1fbcc4019ac1f15a49fe770b0
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 capacity record is equal to 15042 . there is only one such row in the table . the home venue record of this unqiue row is sangju civic stadium . Output:
[ "and { only { filter_eq { all_rows ; capacity ; 15042 } } ; eq { hop { filter_eq { all_rows ; capacity ; 15042 } ; home venue } ; sangju civic stadium } }" ]
task210-cfce6b3b0ac84434aff4231ea38faec6
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 td 's record is greater than or equal to 3 . the number of such rows is 4 . Output:
[ "eq { count { filter_greater_eq { all_rows ; td 's ; 3 } } ; 4 }" ]
task210-5c915ef5dddf4382b4a2770ea1d1794e
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose winner record fuzzily matches to rangers . for the score records of these rows , most of them are greater than 0 . Output:
[ "most_greater { filter_eq { all_rows ; winner ; rangers } ; score ; 0 }" ]
task210-54c92d3d8c814828905955b78c6fcccc
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose first audition date record fuzzily matches to september . there is only one such row in the table . Output:
[ "only { filter_eq { all_rows ; first audition date ; september } }" ]
task210-db05357141f14fdcb5a1ac1e645ea8c7
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose venue record fuzzily matches to stuttgart , west germany . take the year record of this row . select the rows whose venue record fuzzily matches to seoul , south korea . take the year record of this row . the second record is 2 years larger than the first record . Output:
[ "eq { diff { hop { filter_eq { all_rows ; venue ; stuttgart , west germany } ; year } ; hop { filter_eq { all_rows ; venue ; seoul , south korea } ; year } } ; -2 years }" ]
task210-5427a31d381f4995ac3a023fed74a71e
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose population record of all rows is minimum . the english name record of this row is zhangping city . Output:
[ "eq { hop { argmin { all_rows ; population } ; english name } ; zhangping city }" ]
task210-528290d34be84efbb6aa2709c40453f6
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose total record of all rows is 2nd maximum . the nation record of this row is japan ( jpn ) . Output:
[ "eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; japan ( jpn ) }" ]
task210-7eda96435f5c401a8ad426c1ae9a4b08
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 area km 2 record of all rows is maximum . the official name record of this row is salisbury . Output:
[ "eq { hop { argmax { all_rows ; area km 2 } ; official name } ; salisbury }" ]
task210-1959bd8204174891bb5838cd310ef72f
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 congress record fuzzily matches to 111th congress . among these rows , select the rows whose date introduced record fuzzily matches to april . the number of such rows is 2 . Output:
[ "eq { count { filter_eq { filter_eq { all_rows ; congress ; 111th congress } ; date introduced ; april } } ; 2 }" ]
task210-0d59830363594544bbefc7c20a669de3
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 model record fuzzily matches to amd 800 chipset series . take the tdp ( w ) record of this row . select the rows whose model record fuzzily matches to amd 700 chipset series . take the tdp ( w ) record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; model ; amd 800 chipset series } ; tdp ( w ) } ; hop { filter_eq { all_rows ; model ; amd 700 chipset series } ; tdp ( w ) } }" ]
task210-350eb04f03314246a0a29dfd7a9ebc40
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 class records of all rows , all of them fuzzily match to d . Output:
[ "all_eq { all_rows ; class ; d }" ]
task210-2f8a575421d24df387c43b71b6ddd6d0
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 8th minimum round record of all rows is 7 . the player record of the row with 8th minimum round record is bob chandler . Output:
[ "and { eq { nth_min { all_rows ; round ; 8 } ; 7 } ; eq { hop { nth_argmin { all_rows ; round ; 8 } ; player } ; bob chandler } }" ]
task210-e37dd44c712e4901bb2ae21c913dafe4
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 opponent record of this row is buffalo bills . Output:
[ "eq { hop { argmax { all_rows ; attendance } ; opponent } ; buffalo bills }" ]
task210-5fdeb9ce7d3b4b00b1f384a5f538cace
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: for the high points records of all rows , most of them fuzzily match to r pierce . Output:
[ "most_eq { all_rows ; high points ; r pierce }" ]
task210-ce9bdbde3b5748c08ccb24dc13936510
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 . for the result records of these rows , all of them fuzzily match to w . Output:
[ "all_eq { filter_eq { all_rows ; date ; october } ; result ; w }" ]
task210-0ce271b3056e4da498720cb77e06f170
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 home team score record of all rows is maximum . the away team score record of this row is 13.14 ( 92 ) . Output:
[ "eq { hop { argmax { all_rows ; home team score } ; away team score } ; 13.14 ( 92 ) }" ]
task210-06580614d73a4a759de8a102f2baad15
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 played record of all rows is maximum . the manager record of this row is juan carlos chávez . Output:
[ "eq { hop { argmax { all_rows ; played } ; manager } ; juan carlos chávez }" ]
task210-03598b25ece649aaa3deb88dddf3b178
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the rows whose year record fuzzily matches to 2001 . take the races record of this row . select the rows whose year record fuzzily matches to 2003 . take the races record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; year ; 2001 } ; races } ; hop { filter_eq { all_rows ; year ; 2003 } ; races } }" ]
task210-5eea8be438e44f8db27ad3e5161ce126
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 is arbitrary . the number of such rows is 6 . Output:
[ "eq { count { filter_all { all_rows ; party } } ; 6 }" ]
task210-5b48579a60914ddda30f64e302d2fe0f
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 crowd records of all rows , most of them are greater than or equal to 10000 . Output:
[ "most_greater_eq { all_rows ; crowd ; 10000 }" ]
task210-1e739f077d0f47dc9f77698ecaf0731d
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 isolation record of all rows is maximum . the mountain peak record of this row is mount rainier . Output:
[ "eq { hop { argmax { all_rows ; isolation } ; mountain peak } ; mount rainier }" ]
task210-db720c084d1e4bedb7f4711f347f2e16
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 title record fuzzily matches to gandhi . take the gross record of this row . select the rows whose title record fuzzily matches to the dark crystal . take the gross record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; title ; gandhi } ; gross } ; hop { filter_eq { all_rows ; title ; the dark crystal } ; gross } }" ]
task210-f242e8fda68b4bc0affce8a156194c07
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose crowd record of all rows is maximum . the venue record of this row is punt road oval . Output:
[ "eq { hop { argmax { all_rows ; crowd } ; venue } ; punt road oval }" ]
task210-09767fbca1a34703a230d3b1a33234f1
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 laps record is equal to 39 . there is only one such row in the table . the year record of this unqiue row is 1949 . Output:
[ "and { only { filter_eq { all_rows ; laps ; 39 } } ; eq { hop { filter_eq { all_rows ; laps ; 39 } ; year } ; 1949 } }" ]
task210-e828742aef4f4ef8a52b8926995a9577
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 winner record of all rows is maximum . the episode record of this row is 2x10 . Output:
[ "eq { hop { argmax { all_rows ; winner } ; episode } ; 2x10 }" ]
task210-b20dde58d45c431ab17b31d2bda861fa
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: select the row whose crowd record of all rows is maximum . the venue record of this row is vfl park . Output:
[ "eq { hop { argmax { all_rows ; crowd } ; venue } ; vfl park }" ]
task210-5be3de220328480c9cc03255ba593df8
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 overall nt points record of all rows is 375.6 . Output:
[ "round_eq { avg { all_rows ; overall nt points } ; 375.6 }" ]
task210-6fb4fb58f32a4afaa4ac6eb6b937d54b
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 tournaments records of all rows , most of them are equal to 12 . Output:
[ "most_eq { all_rows ; tournaments ; 12 }" ]
task210-4392b85adc404f899b932d27eee7cea8
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 fuzzily matches to eclair . take the launched record of this row . select the rows whose name record fuzzily matches to derwent . take the launched record of this row . the first record is greater than the second record . Output:
[ "greater { hop { filter_eq { all_rows ; name ; eclair } ; launched } ; hop { filter_eq { all_rows ; name ; derwent } ; launched } }" ]
task210-2d1e310b483048f28848373fea8e32b6
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 2nd minimum date record of all rows is jun 25 . the score record of the row with 2nd minimum date record is 2 - 3 . Output:
[ "and { eq { nth_min { all_rows ; date ; 2 } ; jun 25 } ; eq { hop { nth_argmin { all_rows ; date ; 2 } ; score } ; 2 - 3 } }" ]
task210-56bd2fb883364c09a8a5d654ba3ad4fd
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 pick record of all rows is maximum . the player record of this row is james campbell . Output:
[ "eq { hop { argmax { all_rows ; pick } ; player } ; james campbell }" ]
task210-d2671ef868d947178c7a293fb0ad238f
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 against record of all rows is 21 . Output:
[ "round_eq { avg { all_rows ; against } ; 21 }" ]
task210-f2764a3fca874beb8e127dae49d4eed4
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command: 1. count: returns the number of rows in the view. 2. only: returns whether there is exactly one row in the view. 3. hop: returns the value under the header column of the row. 4. and: returns the boolean operation result of two arguments. 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 7. argmax/argmin: returns the row with the max/min value in header column. 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 9. eq/not_eq: returns if the two arguments are equal. 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 11. greater/less: returns if the first argument is greater/less than the second argument. 12. diff: returns the difference between two arguments. 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 16. filter_all: returns the view itself for the case of describing the whole table 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument. Positive Example 1 - Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06. Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } Positive Example 2 - Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard. Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } Negative Example 1 - Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united } Negative Example 2 - Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india. Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } Now complete the following example - Input: the maximum release price ( usd ) record of all rows is 97 . Output:
[ "eq { max { all_rows ; release price ( usd ) } ; 97 }" ]
task210-3769081e8de64a1ab8230e36d93d1c8b