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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the 1st minimum us release date record of all rows is 27 june 2006 . the title record of the row with 1st minimum us release date record is galaxy angel .
Output:
|
[
"and { eq { nth_min { all_rows ; us release date ; 1 } ; 27 june 2006 } ; eq { hop { nth_argmin { all_rows ; us release date ; 1 } ; title } ; galaxy angel } }"
] |
task210-662f4935b92a43eeada34a91af0c7d90
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 game site records of all rows , most of them fuzzily match to mile high stadium .
Output:
|
[
"most_eq { all_rows ; game site ; mile high stadium }"
] |
task210-6439104aad8e443c8c1c9e13fe85dc60
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose year record of all rows is 2nd maximum . the category record of this row is favorite tv actress - leading role in a drama .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; year ; 2 } ; category } ; favorite tv actress - leading role in a drama }"
] |
task210-811b3796554e4614ba4cc2738952c81d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose time record of all rows is 2nd maximum . the wrestler record of this row is chris masters .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; time ; 2 } ; wrestler } ; chris masters }"
] |
task210-329c07e3cb994bfb95447dd9b1c2e8e6
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose total ( kg ) record is greater than or equal to 330 . among these rows , select the rows whose snatch record is less than 150 . there is only one such row in the table . the name record of this unqiue row is juan quiterio ( dom ) .
Output:
|
[
"and { only { filter_less { filter_greater_eq { all_rows ; total ( kg ) ; 330 } ; snatch ; 150 } } ; eq { hop { filter_less { filter_greater_eq { all_rows ; total ( kg ) ; 330 } ; snatch ; 150 } ; name } ; juan quiterio ( dom ) } }"
] |
task210-d63be1427f78411a89b18a98cd49f2ee
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 age record of all rows is minimum . the candidate record of this row is samuel sam hooper .
Output:
|
[
"eq { hop { argmin { all_rows ; age } ; candidate } ; samuel sam hooper }"
] |
task210-d2eb9252b76741b0b4524c81740c5703
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 jon koncak . take the years in orlando record of this row . select the rows whose player record fuzzily matches to tim kempton . take the years in orlando record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; player ; jon koncak } ; years in orlando } ; hop { filter_eq { all_rows ; player ; tim kempton } ; years in orlando } }"
] |
task210-fa26557bfea94d2aa198a11fb3aae755
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 portland trail blazers . take the date record of this row . select the rows whose team record fuzzily matches to detroit pistons . take the date record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; team ; portland trail blazers } ; date } ; hop { filter_eq { all_rows ; team ; detroit pistons } ; date } }"
] |
task210-85ee777f346e46cb9ce575676efc864b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 division record record fuzzily matches to 4-2 . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; division record ; 4-2 } } ; 2 }"
] |
task210-f90967589a8341f0a42e93cfb7f5401d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the crowd records of all rows , most of them are less than 20000 .
Output:
|
[
"most_less { all_rows ; crowd ; 20000 }"
] |
task210-07d9d08e7af741e0b7982bddac4b5e8d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 treaty of cession records of all rows , most of them fuzzily match to 28 may 1956 .
Output:
|
[
"most_eq { all_rows ; treaty of cession ; 28 may 1956 }"
] |
task210-1a7d93a36e81452895bec9dcfb48a5f7
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose school record fuzzily matches to perry central . take the size record of this row . select the rows whose school record fuzzily matches to springs valley . take the size record of this row . the first record is 15 larger than the second record .
Output:
|
[
"eq { diff { hop { filter_eq { all_rows ; school ; perry central } ; size } ; hop { filter_eq { all_rows ; school ; springs valley } ; size } } ; 15 }"
] |
task210-90e439869aff42e78f7a331c1536eb81
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 last aired record of all rows is 2nd minimum . the show record of this row is high rollers .
Output:
|
[
"eq { hop { nth_argmin { all_rows ; last aired ; 2 } ; show } ; high rollers }"
] |
task210-bad70b0d6884488cbd6ee1517710efc0
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 ends records of all rows , all of them are equal to 2008 .
Output:
|
[
"all_eq { all_rows ; ends ; 2008 }"
] |
task210-f90217b03895437ea007d9623cba045d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 tribunal record fuzzily matches to coimbra . take the executions in persona record of this row . select the rows whose tribunal record fuzzily matches to goa . take the executions in persona record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; tribunal ; coimbra } ; executions in persona } ; hop { filter_eq { all_rows ; tribunal ; goa } ; executions in persona } }"
] |
task210-4c8853e1da6b468b8c49ff3931923179
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose result record fuzzily matches to 2nd . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; result ; 2nd } } ; 2 }"
] |
task210-bc9cbab398674131a0dc49806b91f95b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose result record fuzzily matches to w . the number of such rows is 5 .
Output:
|
[
"eq { count { filter_eq { all_rows ; result ; w } } ; 5 }"
] |
task210-4eb367191ac04f3c86d0d97dd09e0d72
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 sent record of all rows is minimum . the constellation record of this row is delphinus .
Output:
|
[
"eq { hop { argmin { all_rows ; date sent } ; constellation } ; delphinus }"
] |
task210-2b7c185bc8144f53ac43cd92caa8c3de
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 change records of all rows , most of them fuzzily match to died .
Output:
|
[
"most_eq { all_rows ; reason for change ; died }"
] |
task210-487cf4736aec4a3d9e827414ffa5b65a
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 ( i ) . there is only one such row in the table .
Output:
|
[
"only { filter_eq { all_rows ; surface ; hard ( i ) } }"
] |
task210-0bcdbf7bf9394de28d7dce61e5906567
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 party records of all rows , most of them fuzzily match to democratic .
Output:
|
[
"most_eq { all_rows ; party ; democratic }"
] |
task210-90aa3ae4af3844f4bd74e632e3f2fa09
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 ends records of all rows , most of them are equal to 2010 .
Output:
|
[
"most_eq { all_rows ; ends ; 2010 }"
] |
task210-2d5ac6fe55a94b5b9d50f05f260f62f0
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 . there is only one such row in the table . the home team record of this unqiue row is essendon . the away team record of this unqiue row is st kilda .
Output:
|
[
"and { only { filter_eq { all_rows ; venue ; windy hill } } ; and { eq { hop { filter_eq { all_rows ; venue ; windy hill } ; home team } ; essendon } ; eq { hop { filter_eq { all_rows ; venue ; windy hill } ; away team } ; st kilda } } }"
] |
task210-1caa6e2d5bd04598a2492a40fe422286
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 driver record fuzzily matches to mike spence . take the laps record of this row . select the rows whose driver record fuzzily matches to jo bonnier . take the laps record of this row . the first record is 1 larger than the second record .
Output:
|
[
"eq { diff { hop { filter_eq { all_rows ; driver ; mike spence } ; laps } ; hop { filter_eq { all_rows ; driver ; jo bonnier } ; laps } } ; 1 }"
] |
task210-5d33122bf1014d13983e5598e26ccf23
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 year records of all rows , most of them are less than 1960 .
Output:
|
[
"most_less { all_rows ; year ; 1960 }"
] |
task210-7d4f2ab5e82946cc8a9bb8321c7f3b46
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 laps record of all rows is maximum . the year record of this row is 1989 .
Output:
|
[
"eq { hop { argmax { all_rows ; laps } ; year } ; 1989 }"
] |
task210-482d52d916b24f07adc3b6488799b77c
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose population record of all rows is maximum . the municipality record of this row is malmö .
Output:
|
[
"eq { hop { argmax { all_rows ; population } ; municipality } ; malmö }"
] |
task210-644bafb64848485eaa1efe3da422812d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 polyunsaturated fat record fuzzily matches to 3 % . there is only one such row in the table . the total fat record of this unqiue row is 94 g .
Output:
|
[
"and { only { filter_eq { all_rows ; polyunsaturated fat ; 3 % } } ; eq { hop { filter_eq { all_rows ; polyunsaturated fat ; 3 % } ; total fat } ; 94 g } }"
] |
task210-8a6af175874e41fcb296db16f11ffb32
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 team record fuzzily matches to latvia . take the outcome record of this row . select the rows whose opponent team record fuzzily matches to iceland . take the outcome record of this row . the first record fuzzily matches to the second record . the outcome record of the first row is winner . the outcome record of the second row is winner .
Output:
|
[
"and { eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } } ; and { eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; winner } ; eq { hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } ; winner } } }"
] |
task210-0e743f7e36574304885573a844a206d5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose no built record is greater than 20 . the number of such rows is 6 .
Output:
|
[
"eq { count { filter_greater { all_rows ; no built ; 20 } } ; 6 }"
] |
task210-f3b86f5f06364a9582d1040b482f7743
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 petr kelner . take the round record of this row . select the rows whose opponent record fuzzily matches to andrej bregar . take the round record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; opponent ; petr kelner } ; round } ; hop { filter_eq { all_rows ; opponent ; andrej bregar } ; round } }"
] |
task210-bb5d31bd7a1248e8904bf7d9a101fa88
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to lost . there is only one such row in the table . the incumbent record of this unqiue row is dan crane .
Output:
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[
"and { only { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; lost } } ; eq { hop { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; lost } ; incumbent } ; dan crane } }"
] |
task210-1fc0ef142f2942f2a7d6fd01da2cb9b7
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose place record of all rows is minimum . the player record of this row is davis love iii .
Output:
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[
"eq { hop { argmin { all_rows ; place } ; player } ; davis love iii }"
] |
task210-4bfa7a383d1243c7becba9751e517f63
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose away team score record is less than 10 . among these rows , select the rows whose crowd record is greater than or equal to 23000 . the number of such rows is 3 .
Output:
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[
"eq { count { filter_greater_eq { filter_less { all_rows ; away team score ; 10 } ; crowd ; 23000 } } ; 3 }"
] |
task210-ec58f1e502ee4838bde036cacf256868
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose season record is equal to 2002 . select the row whose points record of these rows is maximum . the series record of this row is british formula three .
Output:
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[
"eq { hop { argmax { filter_eq { all_rows ; season ; 2002 } ; points } ; series } ; british formula three }"
] |
task210-a9f04bc6667143c3834b335804d2d8db
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose wins record of all rows is maximum . the player record of this row is tom kite .
Output:
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[
"eq { hop { argmax { all_rows ; wins } ; player } ; tom kite }"
] |
task210-1290b7d0d5824eb795b2b86c1dddddc9
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose position record fuzzily matches to defensive end . select the row whose pick record of these rows is 2nd minimum . the player record of this row is leif larsen .
Output:
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[
"eq { hop { nth_argmin { filter_eq { all_rows ; position ; defensive end } ; pick ; 2 } ; player } ; leif larsen }"
] |
task210-e2ba9baba2ee46e285f2987443993397
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose country record fuzzily matches to burma . there is only one such row in the table . the city record of this unqiue row is yangon .
Output:
|
[
"and { only { filter_eq { all_rows ; country ; burma } } ; eq { hop { filter_eq { all_rows ; country ; burma } ; city } ; yangon } }"
] |
task210-13567a4c80ab42f18afe82132b9ecf78
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose result record of all rows is 3rd minimum . the year record of this row is 2007 .
Output:
|
[
"eq { hop { nth_argmin { all_rows ; result ; 3 } ; year } ; 2007 }"
] |
task210-8d011f9043aa4ae1b13f571afc31816f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose home team record fuzzily matches to essendon . take the crowd record of this row . select the rows whose home team record fuzzily matches to footscray . take the crowd record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; home team ; essendon } ; crowd } ; hop { filter_eq { all_rows ; home team ; footscray } ; crowd } }"
] |
task210-2336eabb8d584bbab40e7f6ba67d9eac
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 town ships record is equal to 18 . there is only one such row in the table . the state / region record of this unqiue row is kachin state .
Output:
|
[
"and { only { filter_eq { all_rows ; town ships ; 18 } } ; eq { hop { filter_eq { all_rows ; town ships ; 18 } ; state / region } ; kachin state } }"
] |
task210-cda90a3fda864c098b74167ac54f4d5f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose time / retired record of all rows is maximum . the rider record of this row is dani pedrosa .
Output:
|
[
"eq { hop { argmax { all_rows ; time / retired } ; rider } ; dani pedrosa }"
] |
task210-b6d08639f95a43a19611eb51c50d8398
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the high points records of all rows , most of them fuzzily match to lebron james .
Output:
|
[
"most_eq { all_rows ; high points ; lebron james }"
] |
task210-f96b62e18d3e46e9935d40159e9ed28e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose country record fuzzily matches to australia . there is only one such row in the table . the player record of this unqiue row is mark hensby .
Output:
|
[
"and { only { filter_eq { all_rows ; country ; australia } } ; eq { hop { filter_eq { all_rows ; country ; australia } ; player } ; mark hensby } }"
] |
task210-49bbd1f8e1ef4d3c928057695178c276
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 attendance records of all rows , most of them are greater than 40000 .
Output:
|
[
"most_greater { all_rows ; attendance ; 40000 }"
] |
task210-9bba755325c64d8db82687674cc1b233
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the points records of all rows , most of them are greater than or equal to 9 .
Output:
|
[
"most_greater_eq { all_rows ; points ; 9 }"
] |
task210-53b9fc243b1f42c9a05730a3c21e1c7f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the crowd record of all rows is 25185 .
Output:
|
[
"round_eq { avg { all_rows ; crowd } ; 25185 }"
] |
task210-dfef680e909f48a3934abc287e71d2dd
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose high rebounds record fuzzily matches to a horford . select the row whose location attendance record of these rows is maximum . the date record of this row is december 8 .
Output:
|
[
"eq { hop { argmax { filter_eq { all_rows ; high rebounds ; a horford } ; location attendance } ; date } ; december 8 }"
] |
task210-c311892c8090454193d8257ce75763d9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 6th . there is only one such row in the table . the year record of this unqiue row is 2005 .
Output:
|
[
"and { only { filter_eq { all_rows ; position ; 6th } } ; eq { hop { filter_eq { all_rows ; position ; 6th } ; year } ; 2005 } }"
] |
task210-8500aa92533647afa9d1207d6fe79fff
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 nba draft records of all rows , most of them fuzzily match to 1st round .
Output:
|
[
"most_eq { all_rows ; nba draft ; 1st round }"
] |
task210-497f8ea1cedc4557bbfa8044975e3504
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the crowd records of all rows , all of them are greater than or equal to 8000 .
Output:
|
[
"all_greater_eq { all_rows ; crowd ; 8000 }"
] |
task210-46df640213a94cdd983792a07ff9c2d5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 president record fuzzily matches to chris maclean . there is only one such row in the table . the year record of this unqiue row is 2013 .
Output:
|
[
"and { only { filter_eq { all_rows ; president ; chris maclean } } ; eq { hop { filter_eq { all_rows ; president ; chris maclean } ; year } ; 2013 } }"
] |
task210-95dffffa6b594268b42259b8b7dc123c
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 west germany . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; venue ; west germany } } ; 2 }"
] |
task210-5ac2f9ca4bf14c52ae81f6ff3b59ebb1
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 1980 . take the top team in regular season ( points ) record of this row . select the rows whose year record fuzzily matches to 1982 . take the top team in regular season ( points ) record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; year ; 1980 } ; top team in regular season ( points ) } ; hop { filter_eq { all_rows ; year ; 1982 } ; top team in regular season ( points ) } }"
] |
task210-8edde0fd6e414632abc404e056449950
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 built record is less than 1960 . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_less { all_rows ; year built ; 1960 } } ; 4 }"
] |
task210-420d136b8e4a49a8af4318acef6e82b7
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose date record fuzzily matches to october . the number of such rows is 8 .
Output:
|
[
"eq { count { filter_eq { all_rows ; date ; october } } ; 8 }"
] |
task210-27f75f592c604073bcc945cd92c6f023
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 china . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; location ; china } } ; 3 }"
] |
task210-1a77b7abba984ec78475a3fb43807b67
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the total points records of all rows , most of them are less than 2000 .
Output:
|
[
"most_less { all_rows ; total points ; 2000 }"
] |
task210-4ec52ce9662a44a4b01ec7d3582ce403
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 does not match to ma . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_not_eq { all_rows ; location ; ma } } ; 2 }"
] |
task210-aa04d4d2c9d541ccb88594c5e7ad0737
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 floors record is equal to 32 . there is only one such row in the table . the name record of this unqiue row is at & t building .
Output:
|
[
"and { only { filter_eq { all_rows ; floors ; 32 } } ; eq { hop { filter_eq { all_rows ; floors ; 32 } ; name } ; at & t building } }"
] |
task210-0405c45a1aaf483f95b1af0e5810fb77
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 viewing figure record of all rows is 6.73 million .
Output:
|
[
"round_eq { avg { all_rows ; viewing figure } ; 6.73 million }"
] |
task210-ba83e21e94fb488cbe1da5b3ff11a4e9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 locomotive type record fuzzily matches to steam . select the row whose withdrawn record of these rows is 1st minimum . the number record of this row is 1 .
Output:
|
[
"eq { hop { nth_argmin { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1 } ; number } ; 1 }"
] |
task210-fd49efdd1702415095d0f8c9fa83923b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 score record fuzzily matches to 8 - . there is only one such row in the table . the date record of this unqiue row is february 22 .
Output:
|
[
"and { only { filter_eq { all_rows ; score ; 8 - } } ; eq { hop { filter_eq { all_rows ; score ; 8 - } ; date } ; february 22 } }"
] |
task210-137eca9fefa243f99e17f5b18fb2d0de
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 unemployment rate record of all rows is maximum . the county record of this row is schoharie .
Output:
|
[
"eq { hop { argmax { all_rows ; unemployment rate } ; county } ; schoharie }"
] |
task210-7f55aa1e0d1245f9adca3b42058c95e0
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 nation record fuzzily matches to australia ( aus ) . take the silver record of this row . select the rows whose nation record fuzzily matches to japan ( jpn ) . take the silver record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; nation ; australia ( aus ) } ; silver } ; hop { filter_eq { all_rows ; nation ; japan ( jpn ) } ; silver } }"
] |
task210-0e9ce4ac49564c0ba82045d3594e0f40
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 score records of all rows , most of them are equal to 1 .
Output:
|
[
"most_eq { all_rows ; score ; 1 }"
] |
task210-4ffc51e19cc443da8c80ebb91fe958d1
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose result record fuzzily matches to drew . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; result ; drew } } ; 2 }"
] |
task210-d9a04a1224274807b030754705c44833
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose wins record is equal to 10 . there is only one such row in the table . the club record of this unqiue row is deportivo alavés .
Output:
|
[
"and { only { filter_eq { all_rows ; wins ; 10 } } ; eq { hop { filter_eq { all_rows ; wins ; 10 } ; club } ; deportivo alavés } }"
] |
task210-209cc37cf9cc408bb0bca29121a20df7
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 new channel ( s ) record fuzzily matches to same channel as original . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; new channel ( s ) ; same channel as original } } ; 3 }"
] |
task210-4c55c28c275049798757b4b4649862f0
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose total record is greater than 100 . there is only one such row in the table . the nation record of this unqiue row is united states .
Output:
|
[
"and { only { filter_greater { all_rows ; total ; 100 } } ; eq { hop { filter_greater { all_rows ; total ; 100 } ; nation } ; united states } }"
] |
task210-619dc655ae094f49a69d496cd07749ce
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 points record of all rows is 265 .
Output:
|
[
"round_eq { avg { all_rows ; points } ; 265 }"
] |
task210-20908048ef5644b784f3a34bb616654c
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the sum of the total record of all rows is 111 .
Output:
|
[
"round_eq { sum { all_rows ; total } ; 111 }"
] |
task210-0dceaeb75c274dc5ac529e248b7977a2
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose date of commissioning record of all rows is maximum . the unit number record of this row is 8 .
Output:
|
[
"eq { hop { argmax { all_rows ; date of commissioning } ; unit number } ; 8 }"
] |
task210-2f9433f1ff134ed5aad56f61facf6c40
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose attempts record of all rows is 2nd maximum . the name record of this row is anthony thomas .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; attempts ; 2 } ; name } ; anthony thomas }"
] |
task210-ee7e6d84056e40b0ab46eeebc09e8979
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose 1st party record fuzzily matches to liberal . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_eq { all_rows ; 1st party ; liberal } } ; 4 }"
] |
task210-7184a9a2199f485383f175df1168fc1f
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose sport record fuzzily matches to baseball . there is only one such row in the table . the sportsperson record of this unqiue row is albert pujols .
Output:
|
[
"and { only { filter_eq { all_rows ; sport ; baseball } } ; eq { hop { filter_eq { all_rows ; sport ; baseball } ; sportsperson } ; albert pujols } }"
] |
task210-de5cfd92b9c44f728f521e5f369355ce
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the maximum score record of all rows is 5 - 0 .
Output:
|
[
"eq { max { all_rows ; score } ; 5 - 0 }"
] |
task210-93c99ac07c0f4da4ae48e8424ea43634
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 director records of all rows , all of them fuzzily match to robert alvarez .
Output:
|
[
"all_eq { all_rows ; director ; robert alvarez }"
] |
task210-b448dae4e44e449a9523d95cc21a0455
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 listed record fuzzily matches to 1997 . for the built records of these rows , most of them fuzzily match to 1894 .
Output:
|
[
"most_eq { filter_eq { all_rows ; listed ; 1997 } ; built ; 1894 }"
] |
task210-5bb447ca40d04a648516a9b79f9eae5e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 high points record of all rows is maximum . the date record of this row is june 20 .
Output:
|
[
"eq { hop { argmax { all_rows ; high points } ; date } ; june 20 }"
] |
task210-155d715ac67049e6892df6598cc2f893
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 score record of all rows is maximum . the game record of this row is 5 .
Output:
|
[
"eq { hop { argmax { all_rows ; score } ; game } ; 5 }"
] |
task210-5bc5ce865cb24e20b607f8bee3f0609b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the crowd record of all rows is 13333 .
Output:
|
[
"round_eq { avg { all_rows ; crowd } ; 13333 }"
] |
task210-dab19efe6a4845e8b718d62f102e6643
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 municipality record fuzzily matches to tecate . take the area ( km2 ) record of this row . select the rows whose municipality record fuzzily matches to tijuana . take the area ( km2 ) record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; municipality ; tecate } ; area ( km2 ) } ; hop { filter_eq { all_rows ; municipality ; tijuana } ; area ( km2 ) } }"
] |
task210-b044b4d7643b4680bc421f996b57b291
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 directed by record fuzzily matches to andy cadiff . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; directed by ; andy cadiff } } ; 3 }"
] |
task210-a032012da5844b0c8663f118891d7400
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose date record fuzzily matches to november . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_eq { all_rows ; date ; november } } ; 4 }"
] |
task210-ba6ddf00766948d98f6dd532d50324f9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose opponent in the final record fuzzily matches to adriano panatta . there is only one such row in the table . the championship record of this unqiue row is bologna , italy .
Output:
|
[
"and { only { filter_eq { all_rows ; opponent in the final ; adriano panatta } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; adriano panatta } ; championship } ; bologna , italy } }"
] |
task210-50a5c5a308584609ad9a4abd8369a0bd
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 poland . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; country ; poland } } ; 2 }"
] |
task210-83566342f4f34edbacd4b16a0d56b7c5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 laps record of all rows is 200 .
Output:
|
[
"round_eq { avg { all_rows ; laps } ; 200 }"
] |
task210-1bfa0f959ca944b583f611f4f0fc41dd
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 amy van dyken . take the time record of this row . select the rows whose name record fuzzily matches to vivienne rignall . take the time record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; name ; amy van dyken } ; time } ; hop { filter_eq { all_rows ; name ; vivienne rignall } ; time } }"
] |
task210-cba4df45916b4510b3fabd2e2f2edc62
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 affiliation record fuzzily matches to private christian . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; affiliation ; private christian } } ; 2 }"
] |
task210-44af383ad83a491b877a128422975353
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 duration ( days ) record of all rows is 56.37 .
Output:
|
[
"round_eq { avg { all_rows ; duration ( days ) } ; 56.37 }"
] |
task210-4b729cc3ed1049929a38ccadfe0714f1
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 unit record is equal to 23 . there is only one such row in the table .
Output:
|
[
"only { filter_eq { all_rows ; unit ; 23 } }"
] |
task210-595e702e3f7a4d29b06526dd8949770e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 format record fuzzily matches to vinyl record . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; format ; vinyl record } } ; 2 }"
] |
task210-01cc82ba7560428a926416bc3264af1a
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 writer ( s ) record fuzzily matches to joseph kuhr . among these rows , select the rows whose us original airdate record fuzzily matches to march . the number of such rows is 1 .
Output:
|
[
"eq { count { filter_eq { filter_eq { all_rows ; writer ( s ) ; joseph kuhr } ; us original airdate ; march } } ; 1 }"
] |
task210-f7d0c4bfe11040a3b5248b0d12fc053b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record 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 status records of all rows , most of them fuzzily match to nominated .
Output:
|
[
"most_eq { all_rows ; status ; nominated }"
] |
task210-c458db86be284367ab3e3480e484c204
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 is arbitrary . the number of such rows is 11 .
Output:
|
[
"eq { count { filter_all { all_rows ; player } } ; 11 }"
] |
task210-0015e52d687041c389c3ebb774fdc12f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the team records of all rows , most of them fuzzily match to motopark academy .
Output:
|
[
"most_eq { all_rows ; team ; motopark academy }"
] |
task210-5c11096c7dc3411186664a85ec4ba1d7
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 260 . there is only one such row in the table . the name record of this unqiue row is andreas kofler .
Output:
|
[
"and { only { filter_less { all_rows ; points ; 260 } } ; eq { hop { filter_less { all_rows ; points ; 260 } ; name } ; andreas kofler } }"
] |
task210-4a8902d7b1254a6fb43ba6445444a457
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this 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 june 11 . take the high assists record of this row . select the rows whose date record fuzzily matches to june 10 . take the high assists record of this row . the first record fuzzily matches to the second record .
Output:
|
[
"eq { hop { filter_eq { all_rows ; date ; june 11 } ; high assists } ; hop { filter_eq { all_rows ; date ; june 10 } ; high assists } }"
] |
task210-092d619439584a96b2c8afca7273f7e8
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose school type record fuzzily matches to public . among these rows , select the rows whose joined acc record fuzzily matches to 197 . there is only one such row in the table . the institution record of this unqiue row is georgia tech .
Output:
|
[
"and { only { filter_eq { filter_eq { all_rows ; school type ; public } ; joined acc ; 197 } } ; eq { hop { filter_eq { filter_eq { all_rows ; school type ; public } ; joined acc ; 197 } ; institution } ; georgia tech } }"
] |
task210-b2c41b15bf644a27a808882c552832d0
|
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