input
stringlengths 3.68k
4.11k
| output
listlengths 1
1
| id
stringlengths 40
40
|
|---|---|---|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 ends won record is less than 50 . the 1st maximum stolen ends record of these rows is 14 . the locale record of the row with 1st maximum stolen ends record is germany .
Output:
|
[
"and { eq { nth_max { filter_less { all_rows ; ends won ; 50 } ; stolen ends ; 1 } ; 14 } ; eq { hop { nth_argmax { filter_less { all_rows ; ends won ; 50 } ; stolen ends ; 1 } ; locale } ; germany } }"
] |
task210-e81e2286464a4b5f89e95c4561f95087
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 february . the number of such rows is 6 .
Output:
|
[
"eq { count { filter_eq { all_rows ; date ; february } } ; 6 }"
] |
task210-444df7f2d0f34b3ab94c81c55b219de5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 ground record fuzzily matches to football park . among these rows , select the rows whose crowd record is less than 16000 . the number of such rows is 1 .
Output:
|
[
"eq { count { filter_less { filter_eq { all_rows ; ground ; football park } ; crowd ; 16000 } } ; 1 }"
] |
task210-d2fd7ff76a244fe1b0d37de7478685d5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose year record is equal to 1967 . the sum of the points record of these rows is 2 .
Output:
|
[
"round_eq { sum { filter_eq { all_rows ; year ; 1967 } ; points } ; 2 }"
] |
task210-ba92407e8b294afdb78f0fbc65f01de9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 authority record fuzzily matches to state integrated . there is only one such row in the table . the name record of this unqiue row is st joseph 's catholic school .
Output:
|
[
"and { only { filter_eq { all_rows ; authority ; state integrated } } ; eq { hop { filter_eq { all_rows ; authority ; state integrated } ; name } ; st joseph 's catholic school } }"
] |
task210-f00f766786ab403da0b7b93e6b82d18b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 wins records of all rows , all of them are equal to 0 .
Output:
|
[
"all_eq { all_rows ; wins ; 0 }"
] |
task210-eabee92752bc4e259c98e77fa973e8c6
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose round record of all rows is 3rd minimum . the player record of this row is glen irwin .
Output:
|
[
"eq { hop { nth_argmin { all_rows ; round ; 3 } ; player } ; glen irwin }"
] |
task210-ff0d8abe58154551b47023c8644239d1
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 profits ( billion ) record of all rows is 2nd maximum . the company record of this row is royal dutch shell .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; profits ( billion ) ; 2 } ; company } ; royal dutch shell }"
] |
task210-4e08d8e1a73d4ac2951e34d5b137f781
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 away team score records of all rows , most of them are greater than 10 .
Output:
|
[
"most_greater { all_rows ; away team score ; 10 }"
] |
task210-feb0923026c44ebba592c1c15d4e845e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 7 . the average of the overall record of these rows is 245 .
Output:
|
[
"round_eq { avg { filter_eq { all_rows ; round ; 7 } ; overall } ; 245 }"
] |
task210-d354803c26014e07a4478142328f9427
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 ceased to be duchess record fuzzily matches to husband 's execution . there is only one such row in the table . the name record of this unqiue row is louise marie adélaïde de bourbon .
Output:
|
[
"and { only { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } } ; eq { hop { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } ; name } ; louise marie adélaïde de bourbon } }"
] |
task210-019f2a7d83fd4b259fce544ef996a478
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the results records of all rows , all of them fuzzily match to re - elected .
Output:
|
[
"all_eq { all_rows ; results ; re - elected }"
] |
task210-009bbedfd0a640b0b3d7ac86a5b11e9d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 casualties record of all rows is maximum . the date record of this row is 2009 - 09 - 16 .
Output:
|
[
"eq { hop { argmax { all_rows ; casualties } ; date } ; 2009 - 09 - 16 }"
] |
task210-4fa065c0e378444581ce17ad67b9f51f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose team record fuzzily matches to golden state . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; team ; golden state } } ; 2 }"
] |
task210-99a58846fa4142b89201bc7426444b87
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose height record of all rows is maximum . the name record of this row is rodrigo santana .
Output:
|
[
"eq { hop { argmax { all_rows ; height } ; name } ; rodrigo santana }"
] |
task210-728dca179d2e4580b99c402f4249b3bd
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose location attendance record fuzzily matches to fedexforum . there is only one such row in the table . the date record of this unqiue row is march 7 .
Output:
|
[
"and { only { filter_eq { all_rows ; location attendance ; fedexforum } } ; eq { hop { filter_eq { all_rows ; location attendance ; fedexforum } ; date } ; march 7 } }"
] |
task210-fd88b097b4934107a9895d3fee00d9a3
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 episode summary record fuzzily matches to richard is made into boyfriend material . take the premier date record of this row . select the rows whose episode summary record fuzzily matches to lawryn is made into a bmx biker . take the premier date record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; episode summary ; richard is made into boyfriend material } ; premier date } ; hop { filter_eq { all_rows ; episode summary ; lawryn is made into a bmx biker } ; premier date } }"
] |
task210-8cc5d71cd9834878aacee279347d74ea
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 height records of all rows , most of them fuzzily match to 6 - .
Output:
|
[
"most_eq { all_rows ; height ; 6 - }"
] |
task210-752daeb6a8324588b206080ed79b86b6
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 2nd run records of all rows , most of them are less than 40 .
Output:
|
[
"most_less { all_rows ; 2nd run ; 40 }"
] |
task210-1e1a11555c7a4bd2a24f1b0335cc6ebd
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose country record fuzzily matches to united states . the average of the to par record of these rows is 9.67 .
Output:
|
[
"round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; 9.67 }"
] |
task210-19ca3c76eeba4da19f2a6d629d3df261
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose points record is less than 10 . for the difference records of these rows , most of them fuzzily match to - .
Output:
|
[
"most_eq { filter_less { all_rows ; points ; 10 } ; difference ; - }"
] |
task210-c21275b1f664448e954f1da7fb47c42e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 fuzzily matches to 3 . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; rank ; 3 } } ; 3 }"
] |
task210-13b946f7be8c49d884a5af22a9cb1d43
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 air date record fuzzily matches to july 4 , 1987 . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; first air date ; july 4 , 1987 } } ; 2 }"
] |
task210-72cbfb074d7f4ba9af8f9d77a8aa6be0
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 mark record of all rows is 47.05 .
Output:
|
[
"round_eq { avg { all_rows ; mark } ; 47.05 }"
] |
task210-d9d52c7c9d0f43ffbd518dda6c52990c
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the score in the final record of all rows is 6 .
Output:
|
[
"round_eq { avg { all_rows ; score in the final } ; 6 }"
] |
task210-b1a907b4640f421a8c22177a1cc511a9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 against record is less than 10 . among these rows , select the rows whose status record fuzzily matches to tour match . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { filter_less { all_rows ; against ; 10 } ; status ; tour match } } ; 2 }"
] |
task210-ce1719704977476088a96993b49166c9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 runs record is less than 3000 . there is only one such row in the table . the record of this unqiue row is chris pringle .
Output:
|
[
"and { only { filter_less { all_rows ; runs ; 3000 } } ; eq { hop { filter_less { all_rows ; runs ; 3000 } ; } ; chris pringle } }"
] |
task210-e1e1c09fbc464e4792cb1faed5c24291
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 maximum revenue in usd record of all rows is 469.2 billion . the company record of the row with 2nd maximum revenue in usd record is walmart .
Output:
|
[
"and { eq { nth_max { all_rows ; revenue in usd ; 2 } ; 469.2 billion } ; eq { hop { nth_argmax { all_rows ; revenue in usd ; 2 } ; company } ; walmart } }"
] |
task210-48c44f4e84d844f392dd76b15db03bb4
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 12 .
Output:
|
[
"eq { count { filter_all { all_rows ; institution } } ; 12 }"
] |
task210-e0712030366b4168a1afd68f2dddee70
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 date record of all rows is 2nd maximum . the tournament record of this row is cincinnati , united states .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; date ; 2 } ; tournament } ; cincinnati , united states }"
] |
task210-5411d2fe3d4f4201bd69bb853cfab3f6
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 53.5 . there is only one such row in the table . the race record of this unqiue row is sir rupert clarke stakes .
Output:
|
[
"and { only { filter_eq { all_rows ; weight ( kg ) ; 53.5 } } ; eq { hop { filter_eq { all_rows ; weight ( kg ) ; 53.5 } ; race } ; sir rupert clarke stakes } }"
] |
task210-aaf1ce92622644e6a67b82dc359164e5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 gold record of all rows is 2.67 .
Output:
|
[
"round_eq { avg { all_rows ; gold } ; 2.67 }"
] |
task210-88143b7f8b6648bfa0e25c007fa23d58
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 greater than 0 . there is only one such row in the table . the tournament record of this unqiue row is masters tournament .
Output:
|
[
"and { only { filter_greater { all_rows ; wins ; 0 } } ; eq { hop { filter_greater { all_rows ; wins ; 0 } ; tournament } ; masters tournament } }"
] |
task210-96390f54ea894d38a4eae9dff5bb42fb
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 to par record fuzzily matches to + 6 . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; to par ; + 6 } } ; 3 }"
] |
task210-824cd178f4584ea7ab8e58278914ef3a
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 1965 . take the overall record record of this row . select the rows whose year record fuzzily matches to 1959 . take the overall record record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; year ; 1965 } ; overall record } ; hop { filter_eq { all_rows ; year ; 1959 } ; overall record } }"
] |
task210-853d27050c9d47ad8d94c72891e08bf2
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 three darts challenge record fuzzily matches to jermaine jackson . take the episode number record of this row . select the rows whose three darts challenge record fuzzily matches to meat loaf . take the episode number record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; three darts challenge ; jermaine jackson } ; episode number } ; hop { filter_eq { all_rows ; three darts challenge ; meat loaf } ; episode number } }"
] |
task210-123c36cb280f4893b90dbb09f7571e13
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 apparent magnitude record of all rows is maximum . the ngc number record of this row is 5003 .
Output:
|
[
"eq { hop { argmax { all_rows ; apparent magnitude } ; ngc number } ; 5003 }"
] |
task210-f51feab79312480898424f6237412c8e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose time / retired record fuzzily matches to accident . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; time / retired ; accident } } ; 2 }"
] |
task210-e8aa4bab85e74d60b49a365461b908b8
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 release date record fuzzily matches to 2004 . there is only one such row in the table . the version record of this unqiue row is 4.10 .
Output:
|
[
"and { only { filter_eq { all_rows ; release date ; 2004 } } ; eq { hop { filter_eq { all_rows ; release date ; 2004 } ; version } ; 4.10 } }"
] |
task210-127b7bba522b4d0cab4adad635b51e1b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 trainer record fuzzily matches to d wayne lukas . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; trainer ; d wayne lukas } } ; 2 }"
] |
task210-3c297389c48046eb8a97c80956ef7f68
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose location record fuzzily matches to virginia beach . there is only one such row in the table . the goal record of this unqiue row is 2 .
Output:
|
[
"and { only { filter_eq { all_rows ; location ; virginia beach } } ; eq { hop { filter_eq { all_rows ; location ; virginia beach } ; goal } ; 2 } }"
] |
task210-2cfb12c6320f4caf9ab40b0a657b5c14
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 hard . the number of such rows is 7 .
Output:
|
[
"eq { count { filter_eq { all_rows ; surface ; hard } } ; 7 }"
] |
task210-11faf912334449e2bcb21842531f5990
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 brunswick street oval . there is only one such row in the table . the home team record of this unqiue row is fitzroy . the away team record of this unqiue row is collingwood .
Output:
|
[
"and { only { filter_eq { all_rows ; venue ; brunswick street oval } } ; and { eq { hop { filter_eq { all_rows ; venue ; brunswick street oval } ; home team } ; fitzroy } ; eq { hop { filter_eq { all_rows ; venue ; brunswick street oval } ; away team } ; collingwood } } }"
] |
task210-812c08d3a5cf4753bb46c59fa18b7294
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the attendance record of all rows is 60644 .
Output:
|
[
"round_eq { avg { all_rows ; attendance } ; 60644 }"
] |
task210-4248179fa7474b049bc0fe53fe112f93
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 capacity record of all rows is maximum . the location record of this row is minsk .
Output:
|
[
"eq { hop { argmax { all_rows ; capacity } ; location } ; minsk }"
] |
task210-f5de960a82684a1ab6d72631fd7ef8cb
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 yvert records of all rows , most of them are equal to 0 .
Output:
|
[
"most_eq { all_rows ; yvert ; 0 }"
] |
task210-fe94619ac059404f9f602433f511f8c6
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose time record is less than 22.2 . there is only one such row in the table . the athlete record of this unqiue row is veronica campbell - brown .
Output:
|
[
"and { only { filter_less { all_rows ; time ; 22.2 } } ; eq { hop { filter_less { all_rows ; time ; 22.2 } ; athlete } ; veronica campbell - brown } }"
] |
task210-a6262e72a29540e4845b35947b3c2d6e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 fate record fuzzily matches to sunk . among these rows , select the rows whose nationality record fuzzily matches to great britain . the number of such rows is 9 .
Output:
|
[
"eq { count { filter_eq { filter_eq { all_rows ; fate ; sunk } ; nationality ; great britain } } ; 9 }"
] |
task210-ff788aca60454413b94a44c82e2cc75e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 1996 . take the length record of this row . select the rows whose year record fuzzily matches to 2000 . take the length record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; year ; 1996 } ; length } ; hop { filter_eq { all_rows ; year ; 2000 } ; length } }"
] |
task210-c03f0618781548d8b76febc09de1f0e3
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 livery record fuzzily matches to br rail blue . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_eq { all_rows ; livery ; br rail blue } } ; 4 }"
] |
task210-51d7bcf695494edaac91ae72503afd89
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 elected record of all rows is 1st minimum . the incumbent record of this row is thomas j bliley , jr .
Output:
|
[
"eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; thomas j bliley , jr }"
] |
task210-29e56c1896f644c5a295f452d56c4875
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 fuzzily matches to norbert sturny ( sui ) . take the year record of this row . select the rows whose gold record fuzzily matches to malcolm cooper ( gbr ) . take the year record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; gold ; norbert sturny ( sui ) } ; year } ; hop { filter_eq { all_rows ; gold ; malcolm cooper ( gbr ) } ; year } }"
] |
task210-fb5819df4f834d118207d8e3613f8fe8
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 running back . among these rows , select the rows whose round record is greater than 4 . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_greater { filter_eq { all_rows ; position ; running back } ; round ; 4 } } ; 3 }"
] |
task210-26dd5a9218ef4bdaaac1a28139688c50
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 height records of all rows , most of them are less than 190 .
Output:
|
[
"most_less { all_rows ; height ; 190 }"
] |
task210-4325a115ab4b41a1b8300b1f30909dda
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 method record fuzzily matches to draw . there is only one such row in the table . the res record of this unqiue row is draw .
Output:
|
[
"and { only { filter_eq { all_rows ; method ; draw } } ; eq { hop { filter_eq { all_rows ; method ; draw } ; res } ; draw } }"
] |
task210-1e9d4813f3d540679e72c65a231ec2f2
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 rank record of all rows is minimum . the airline record of this row is tam .
Output:
|
[
"eq { hop { argmin { all_rows ; rank } ; airline } ; tam }"
] |
task210-58088028b5df4acfb322c2c7ccf9cbd2
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 socket record fuzzily matches to socket m socket p bga479 . there is only one such row in the table . the model ( list ) record of this unqiue row is t5xxx t7xxx .
Output:
|
[
"and { only { filter_eq { all_rows ; socket ; socket m socket p bga479 } } ; eq { hop { filter_eq { all_rows ; socket ; socket m socket p bga479 } ; model ( list ) } ; t5xxx t7xxx } }"
] |
task210-287c0d1ab6ca470099633ce46108f319
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 outcome records of all rows , most of them fuzzily match to runner - up .
Output:
|
[
"most_eq { all_rows ; outcome ; runner - up }"
] |
task210-83e1270086d7400c98693258becb4b99
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the date records of all rows , most of them are greater than 1980 .
Output:
|
[
"most_greater { all_rows ; date ; 1980 }"
] |
task210-429b56afab7f4da9aea7cb940c090762
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 199 . for the performance records of these rows , most of them fuzzily match to triple jump .
Output:
|
[
"most_eq { filter_eq { all_rows ; year ; 199 } ; performance ; triple jump }"
] |
task210-ddc6bcb813c349b59028498ebd5f73fc
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 qual 1 records of all rows , most of them are less than 1:18:000 .
Output:
|
[
"most_less { all_rows ; qual 1 ; 1:18:000 }"
] |
task210-da6a0980de3941d19bb3e51682a76dec
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 mass ( kg ) record of all rows is maximum . the satellite record of this row is echo 2 .
Output:
|
[
"eq { hop { argmax { all_rows ; mass ( kg ) } ; satellite } ; echo 2 }"
] |
task210-e8cc5c53ac4a44558ddb9af16ecf43a9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose championship record fuzzily matches to wimbledon . select the row whose year record of these rows is minimum . the opponent in the final record of this row is wilhelm bungert .
Output:
|
[
"eq { hop { argmin { filter_eq { all_rows ; championship ; wimbledon } ; year } ; opponent in the final } ; wilhelm bungert }"
] |
task210-00c28b5333bc4ce88f2f70d5ce84d4c2
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 .
Output:
|
[
"only { filter_eq { all_rows ; surface ; carpet } }"
] |
task210-9eb2546c17ca4ecb8f63edf00333e35b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose opponent record fuzzily matches to st louis cardinals . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; opponent ; st louis cardinals } } ; 2 }"
] |
task210-f382bf65489f42069bc665c3208bec6b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 losses record of all rows is 1st maximum . the team record of this row is new york liberty .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; losses ; 1 } ; team } ; new york liberty }"
] |
task210-2363171f1bff4156a558eca7cd7d6805
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 manager record fuzzily matches to bob didier . there is only one such row in the table . the year record of this unqiue row is 1977 .
Output:
|
[
"and { only { filter_eq { all_rows ; manager ; bob didier } } ; eq { hop { filter_eq { all_rows ; manager ; bob didier } ; year } ; 1977 } }"
] |
task210-05f51526e3b24ffa973cac33ccb7e825
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 rd record is greater than or equal to 4 . select the row whose pick record of these rows is 2nd minimum . the player record of this row is matt butcher .
Output:
|
[
"eq { hop { nth_argmin { filter_greater_eq { all_rows ; rd ; 4 } ; pick ; 2 } ; player } ; matt butcher }"
] |
task210-5dc46d2c3dc04999ba2b960b35d8925d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 hard . select the row whose date record of these rows is minimum . the opponent in the final record of this row is andre agassi .
Output:
|
[
"eq { hop { argmin { filter_eq { all_rows ; surface ; hard } ; date } ; opponent in the final } ; andre agassi }"
] |
task210-700f4bcd53994b8488b75cfc26f9711e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 charleston southerns head coach records of all rows , most of them fuzzily match to jay mills .
Output:
|
[
"most_eq { all_rows ; charleston southerns head coach ; jay mills }"
] |
task210-4113d2ffda81472585f722b3158dbd37
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 rank record of all rows is minimum . the athlete record of this row is alan campbell .
Output:
|
[
"eq { hop { argmin { all_rows ; rank } ; athlete } ; alan campbell }"
] |
task210-fb44b091e5b74248bd13c7fa594cfe99
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 bong hawkins . take the season record of this row . select the rows whose name record fuzzily matches to bakari hendrix . take the season record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; name ; bong hawkins } ; season } ; hop { filter_eq { all_rows ; name ; bakari hendrix } ; season } }"
] |
task210-7f1e14e1be0b4af3bd02db97d3a18aad
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose height record is less than 6-0 . there is only one such row in the table . the player record of this unqiue row is myles mack .
Output:
|
[
"and { only { filter_less { all_rows ; height ; 6-0 } } ; eq { hop { filter_less { all_rows ; height ; 6-0 } ; player } ; myles mack } }"
] |
task210-12ddeb8ad5364064a8471fcc5cb8eb36
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 reason for termination records of all rows , most of them fuzzily match to death .
Output:
|
[
"most_eq { all_rows ; reason for termination ; death }"
] |
task210-e602fafcf8e3442db1aca9ddb39c10c8
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 under - 13 record fuzzily matches to emily park . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; under - 13 ; emily park } } ; 2 }"
] |
task210-f432929c1e3146adb768e6dcd2f6cccc
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 box score records of all rows , most of them fuzzily match to w .
Output:
|
[
"most_eq { all_rows ; box score ; w }"
] |
task210-7e04f2f08d8b47ab945e35b5cdb30393
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 entries record of all rows is 1st maximum . the driver record of this row is michael schumacher .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; entries ; 1 } ; driver } ; michael schumacher }"
] |
task210-d71088785e90454cb36a64b010464876
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 type records of all rows , most of them fuzzily match to mountain .
Output:
|
[
"most_eq { all_rows ; type ; mountain }"
] |
task210-4df200dbbee14cf3b5c9c048d34df630
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 album record fuzzily matches to come on over . take the weeks at number one record of this row . select the rows whose album record fuzzily matches to let 's talk about love . take the weeks at number one record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; album ; come on over } ; weeks at number one } ; hop { filter_eq { all_rows ; album ; let 's talk about love } ; weeks at number one } }"
] |
task210-9b29e57013c84ebea95ccfc63b106f4d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 viewers record of all rows is 7.42 .
Output:
|
[
"round_eq { avg { all_rows ; viewers } ; 7.42 }"
] |
task210-1fdb2569c5dc477c836fc490be1ea860
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 black knights points record of all rows is maximum . the date record of this row is oct 13 .
Output:
|
[
"eq { hop { argmax { all_rows ; black knights points } ; date } ; oct 13 }"
] |
task210-b16fcf575417401ab42ac8b5d08c14f3
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 object type records of all rows , most of them fuzzily match to spiral galaxy .
Output:
|
[
"most_eq { all_rows ; object type ; spiral galaxy }"
] |
task210-7be5401df6c243d18a6e0860c192f800
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose points record of all rows is maximum . the team record of this row is soviet union .
Output:
|
[
"eq { hop { argmax { all_rows ; points } ; team } ; soviet union }"
] |
task210-8e81e2d1225f419b81ec3afad25bedef
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 technology record fuzzily matches to wifi . there is only one such row in the table .
Output:
|
[
"only { filter_eq { all_rows ; technology ; wifi } }"
] |
task210-f1cf8ae93c8c486e9b329e09becf1819
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 builder record fuzzily matches to beyer peacock & co . the average of the builder 's no record of these rows is 3442 .
Output:
|
[
"round_eq { avg { filter_eq { all_rows ; builder ; beyer peacock & co } ; builder 's no } ; 3442 }"
] |
task210-20e92a3cb32d4775bfac420f68a70b16
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the sum of the gold record of all rows is 14 .
Output:
|
[
"round_eq { sum { all_rows ; gold } ; 14 }"
] |
task210-f2ea7bdd990848ba81d58e6c2b9ffd14
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 max processors record fuzzily matches to 1 ultrasparc t1 . select the row whose max memory record of these rows is 1st minimum . the model record of this row is t1000 .
Output:
|
[
"eq { hop { nth_argmin { filter_eq { all_rows ; max processors ; 1 ultrasparc t1 } ; max memory ; 1 } ; model } ; t1000 }"
] |
task210-99cc33c67bf84759b903e4a9e22c840d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 record fuzzily matches to 69 . take the score record of this row . select the rows whose game record fuzzily matches to 66 . take the score record of this row . the first record is greater than the second record . the opponent record of the first row is boston bruins . the opponent record of the second row is boston bruins .
Output:
|
[
"and { greater { hop { filter_eq { all_rows ; game ; 69 } ; score } ; hop { filter_eq { all_rows ; game ; 66 } ; score } } ; and { eq { hop { filter_eq { all_rows ; game ; 69 } ; opponent } ; boston bruins } ; eq { hop { filter_eq { all_rows ; game ; 66 } ; opponent } ; boston bruins } } }"
] |
task210-566e625cacee4bcc9d196ede6446ab15
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 zandro limpot , jr . take the pick record of this row . select the rows whose player record fuzzily matches to richard bachmann . take the pick record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; player ; zandro limpot , jr } ; pick } ; hop { filter_eq { all_rows ; player ; richard bachmann } ; pick } }"
] |
task210-ef76201d8a5140e490dab60386dc7b29
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 running back . there is only one such row in the table . the player record of this unqiue row is tom moore .
Output:
|
[
"and { only { filter_eq { all_rows ; position ; running back } } ; eq { hop { filter_eq { all_rows ; position ; running back } ; player } ; tom moore } }"
] |
task210-ff2f820deddb42d7b947c30e11385870
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 laps records of all rows , most of them are equal to 27 .
Output:
|
[
"most_eq { all_rows ; laps ; 27 }"
] |
task210-38eb81c900b4458fb7a4cbda9b1eb92c
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 events record is greater than 10 . among these rows , select the rows whose top - 10 record is equal to 2 . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { filter_greater { all_rows ; events ; 10 } ; top - 10 ; 2 } } ; 2 }"
] |
task210-34320de34664422181de203bbece9624
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 windy hill . take the crowd record of this row . select the rows whose venue record fuzzily matches to princes park . take the crowd record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; venue ; windy hill } ; crowd } ; hop { filter_eq { all_rows ; venue ; princes park } ; crowd } }"
] |
task210-6430b09f20444fcb9418592a66d306ff
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 silver record of all rows is 2nd maximum . the nation record of this row is cyprus .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; silver ; 2 } ; nation } ; cyprus }"
] |
task210-a0b84e10a3af44feb7684b05560a0c41
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 premiere record fuzzily matches to 14 august . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_eq { all_rows ; premiere ; 14 august } } ; 4 }"
] |
task210-bb38bfcad3b2409e977a5c75651ff2ea
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 goals record of all rows is 15 .
Output:
|
[
"round_eq { avg { all_rows ; goals } ; 15 }"
] |
task210-5ccdfe1f924d40e9961d4d23448f9a14
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 gross record of all rows is 5th maximum . the title record of this row is the color purple . the director record of this row is steven spielberg .
Output:
|
[
"and { eq { hop { nth_argmax { all_rows ; gross ; 5 } ; title } ; the color purple } ; eq { hop { nth_argmax { all_rows ; gross ; 5 } ; director } ; steven spielberg } }"
] |
task210-e6d8405773ca41ef91104b001d8564bc
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose points record is greater than 100 . the number of such rows is 6 .
Output:
|
[
"eq { count { filter_greater { all_rows ; points ; 100 } } ; 6 }"
] |
task210-ece478af06704c83a4e41ec49eb52dd1
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 seats record of all rows is 55 .
Output:
|
[
"round_eq { avg { all_rows ; seats } ; 55 }"
] |
task210-274e97453fe5445cbc0509a73b1a7778
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 nat record fuzzily matches to slovakia . there is only one such row in the table . the name record of this unqiue row is filip šebo .
Output:
|
[
"and { only { filter_eq { all_rows ; nat ; slovakia } } ; eq { hop { filter_eq { all_rows ; nat ; slovakia } ; name } ; filip šebo } }"
] |
task210-d663f3f21bbb487992c766b10ea54405
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.