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Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { filter_greater_eq { all_rows ; year left ; 1970 } ; conference joined ; hoosier heartland } } ; 2 } = true
Output:
| [
"select the rows whose year left record is greater than or equal to 1970 . among these rows , select the rows whose conference joined record fuzzily matches to hoosier heartland . the number of such rows is 2 ."
] | task110-c8515ab096f04746abc54c7571dbc2ab |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_less { all_rows ; time ; 21.0 } = true
Output:
| [
"for the time records of all rows , most of them are less than 21.0 ."
] | task110-c31f2d2e49194b76a36f7169ca5ba098 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_greater { all_rows ; erp / power w ; 5000 } } ; 3 } = true
Output:
| [
"select the rows whose erp power w record is greater than 5000 . the number of such rows is 3 ."
] | task110-a523aa3ec14b4bd99014ffbe1158c483 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; points } ; team } ; paulistano } = true
Output:
| [
"select the row whose points record of all rows is maximum . the team record of this row is paulistano ."
] | task110-32c275b6d94344f3a447d93616b3909b |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { filter_eq { all_rows ; nation ; united states } ; fastest time ( s ) } ; 66.98 s } = true
Output:
| [
"select the rows whose nation record fuzzily matches to united states . the sum of the fastest time s record of these rows is 66.98 s ."
] | task110-3618d5764fde4f50a15a91795d77d825 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: all_eq { all_rows ; date ; 19 april 1975 } = true
Output:
| [
"for the date records of all rows , all of them fuzzily match to 19 april 1975 ."
] | task110-daaa9cde065c4984ab869b7c8696d932 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; victor ; stalemate } } ; 2 } = true
Output:
| [
"select the rows whose victor record fuzzily matches to stalemate . the number of such rows is 2 ."
] | task110-dcfdbea1392340cd9f9615e08ef083d5 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; score } ; 2.375 } = true
Output:
| [
"the average of the score record of all rows is 2.375 ."
] | task110-57ba6306c4094c3788c1a36003c5564c |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_less { all_rows ; crowd ; 10000 } } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; geelong } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; away team } ; north melbourne } ; eq { hop { filter_less { all_rows ; crowd ; 10000 } ; venue } ; kardinia park } } } } = true
Output:
| [
"select the rows whose crowd record is less than 10000 . there is only one such row in the table . the home team record of this unqiue row is geelong . the away team record of this unqiue row is north melbourne . the venue record of this unqiue row is kardinia park ."
] | task110-7cb9cfc39a9a4813a2b0398f35f2783a |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmin { all_rows ; start } ; year } ; 1952 } = true
Output:
| [
"select the row whose start record of all rows is minimum . the year record of this row is 1952 ."
] | task110-ac77416c81d44ab29681a95ce14f426d |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: greater { hop { filter_eq { all_rows ; venue ; punt road oval } ; crowd } ; hop { filter_eq { all_rows ; venue ; glenferrie oval } ; crowd } } = true
Output:
| [
"select the rows whose venue record fuzzily matches to punt road oval . take the crowd record of this row . select the rows whose venue record fuzzily matches to glenferrie oval . take the crowd record of this row . the first record is greater than the second record ."
] | task110-a395db8653b74c13a332916080060fbb |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { filter_eq { all_rows ; event ; wc beijing } ; rank points } ; 23 } = true
Output:
| [
"select the rows whose event record fuzzily matches to wc beijing . the sum of the rank points record of these rows is 23 ."
] | task110-a764597ccac245d180d4daefce056849 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; wins } ; club } ; warrnambool } = true
Output:
| [
"select the row whose wins record of all rows is maximum . the club record of this row is warrnambool ."
] | task110-306064f7ac9a40338532a2155c571663 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; country ; belgium } ; total } ; hop { filter_eq { all_rows ; country ; brazil } ; total } } = true
Output:
| [
"select the rows whose country record fuzzily matches to belgium . take the total record of this row . select the rows whose country record fuzzily matches to brazil . take the total record of this row . the first record is less than the second record ."
] | task110-8409c93e3d6a4c09a2c7ed6b0daac634 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; club ; landskrona bois } ; first season of current spell } ; hop { filter_eq { all_rows ; club ; ängelholms ff } ; first season of current spell } } = true
Output:
| [
"select the rows whose club record fuzzily matches to landskrona bois . take the first season of current spell record of this row . select the rows whose club record fuzzily matches to ängelholms ff . take the first season of current spell record of this row . the first record is less than the second record ."
] | task110-75f051ba8d964377b4306b23e2cc77ee |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { all_rows ; runs ; 2 } ; player } ; dene hills } = true
Output:
| [
"select the row whose runs record of all rows is 2nd maximum . the player record of this row is dene hills ."
] | task110-a4f1ac1aec8a4a7a9db0d4b80cfcdfe9 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_all { all_rows ; region } } ; 5 } = true
Output:
| [
"select the rows whose region record is arbitrary . the number of such rows is 5 ."
] | task110-261deb4d8f544f2e95e8bac85a4d78a0 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_greater_eq { all_rows ; us viewers ( million ) ; 1.0 } = true
Output:
| [
"for the us viewers million records of all rows , most of them are greater than or equal to 1.0 ."
] | task110-219a069cd4fb4f60958579e56510173f |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { all_rows ; wins ; 18 } } ; eq { hop { filter_eq { all_rows ; wins ; 18 } ; club } ; rc celta de vigo } } = true
Output:
| [
"select the rows whose wins record is equal to 18 . there is only one such row in the table . the club record of this unqiue row is rc celta de vigo ."
] | task110-f39d94653f8d4d14b64df600dc43de8a |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { all_rows ; capacity ( mw ) ; 1 } ; wind farm } ; codling } = true
Output:
| [
"select the row whose capacity mw record of all rows is 1st maximum . the wind farm record of this row is codling ."
] | task110-da4b84a5b0d047628e6cf3902dc1d068 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { all_rows ; played ; 16 } = true
Output:
| [
"for the played records of all rows , most of them are equal to 16 ."
] | task110-8f0a27c3c0774daa98c771a1548b8b2f |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { filter_eq { all_rows ; constructor ; cooper - climax } ; circuit ; goodwood } } ; eq { hop { filter_eq { filter_eq { all_rows ; constructor ; cooper - climax } ; circuit ; goodwood } ; date } ; 30 march } } = true
Output:
| [
"select the rows whose constructor record fuzzily matches to cooper climax . among these rows , select the rows whose circuit record fuzzily matches to goodwood . there is only one such row in the table . the date record of this unqiue row is 30 march ."
] | task110-ae9bbdbe7184489a8a9ca5418fca20f8 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; location ; japan } } ; 8 } = true
Output:
| [
"select the rows whose location record fuzzily matches to japan . the number of such rows is 8 ."
] | task110-5293eb3615874ff49a99edfcdc3d4185 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_less { all_rows ; population ( 2010 census ) ; 5000 } } ; eq { hop { filter_less { all_rows ; population ( 2010 census ) ; 5000 } ; district } ; intramuros } } = true
Output:
| [
"select the rows whose population 2010 census record is less than 5000 . there is only one such row in the table . the district record of this unqiue row is intramuros ."
] | task110-5dede8555d3e4e0d92ce9060490e73c5 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; location ; seattle } } ; 3 } = true
Output:
| [
"select the rows whose location record fuzzily matches to seattle . the number of such rows is 3 ."
] | task110-a78b2d892cb1482ca0ce64fbd9f3877f |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; size } ; school } ; mitchell } = true
Output:
| [
"select the row whose size record of all rows is maximum . the school record of this row is mitchell ."
] | task110-2a2c631169d34e0aba6825498beb2a3c |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; team ( s ) ; stegell motorsports } } ; 4 } = true
Output:
| [
"select the rows whose team s record fuzzily matches to stegell motorsports . the number of such rows is 4 ."
] | task110-07847cdf250a4da9a001f28a6119cf58 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } ; title } ; pilot } } = true
Output:
| [
"select the rows whose us viewers million record is greater than 9.0 . there is only one such row in the table . the title record of this unqiue row is pilot ."
] | task110-64eeb4a9590c4d5e851f2492f099e200 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; to par } ; -2.19 } = true
Output:
| [
"the average of the to par record of all rows is 2.19 ."
] | task110-4047b5a23b604f819fe365b654e61691 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmin { all_rows ; rank ; 3 } ; name } ; matuzalém } = true
Output:
| [
"select the row whose rank record of all rows is 3rd minimum . the name record of this row is matuzalém ."
] | task110-ece66e1fdca64a2abbea8c74b8f81530 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; 1st leg } ; team 1 } ; flamengo } = true
Output:
| [
"select the row whose 1st leg record of all rows is maximum . the team 1 record of this row is flamengo ."
] | task110-07b4fff5c49b4b02b3c8ac4309aee235 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; points } ; 16.88 } = true
Output:
| [
"the average of the points record of all rows is 16.88 ."
] | task110-6cc8f2b1346342e1bbe771c1f6e40d3a |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: greater { hop { filter_eq { all_rows ; no in season ; 1 / 2 } ; us viewers ( million ) } ; hop { filter_eq { all_rows ; no in season ; 16 } ; us viewers ( million ) } } = true
Output:
| [
"select the rows whose no in season record fuzzily matches to 1 2 . take the us viewers million record of this row . select the rows whose no in season record fuzzily matches to 16 . take the us viewers million record of this row . the first record is greater than the second record ."
] | task110-1220f89cef924876a278fea0fefb1c5a |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { filter_eq { all_rows ; opponents ; fulham } ; result ; 1-1 } } ; 2 } = true
Output:
| [
"select the rows whose opponents record fuzzily matches to fulham . among these rows , select the rows whose result record fuzzily matches to 11 . the number of such rows is 2 ."
] | task110-443a4e5420574c929affa93de2ffd353 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_greater { filter_less { all_rows ; home team score ; 15 } ; crowd ; 15000 } } ; 3 } = true
Output:
| [
"select the rows whose home team score record is less than 15 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 3 ."
] | task110-54a9e950fc174766bfbe2c9206c0afec |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; bleeding time ; unaffected } } ; 6 } = true
Output:
| [
"select the rows whose bleeding time record fuzzily matches to unaffected . the number of such rows is 6 ."
] | task110-0d1fc64a55d54f4390c6d7bc1772ab25 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { filter_eq { all_rows ; outcome ; winner } ; surface ; clay } } ; 4 } = true
Output:
| [
"select the rows whose outcome record fuzzily matches to winner . among these rows , select the rows whose surface record fuzzily matches to clay . the number of such rows is 4 ."
] | task110-0d846f33e1e94b51a0d61493441f4ea8 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmin { all_rows ; date ; 2 } ; venue } ; bahrain national stadium , manama } = true
Output:
| [
"select the row whose date record of all rows is 2nd minimum . the venue record of this row is bahrain national stadium , manama ."
] | task110-ed33826163564c49b7dd3bf069eadc5e |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; name ; yogyakarta documentary film festival } ; est } ; hop { filter_eq { all_rows ; name ; vibgyor international film festival } ; est } } = true
Output:
| [
"select the rows whose name record fuzzily matches to yogyakarta documentary film festival . take the est record of this row . select the rows whose name record fuzzily matches to vibgyor international film festival . take the est record of this row . the first record is less than the second record ."
] | task110-dfd27942136b4f02bcb00ed6a25c3b36 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_greater { filter_greater_eq { all_rows ; date ; december 3 , 1989 } ; attendance ; 10000 } } ; 3 } = true
Output:
| [
"select the rows whose date record is greater than or equal to december 3 , 1989 . among these rows , select the rows whose attendance record is greater than 10000 . the number of such rows is 3 ."
] | task110-e1099d349b924c0bb57f962c834088a9 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { all_rows ; issue price } ; 395.1 } = true
Output:
| [
"the sum of the issue price record of all rows is 395.1 ."
] | task110-e07b697a107e4f29b226e18707be6615 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; total } ; nation } ; east germany ( gdr ) } = true
Output:
| [
"select the row whose total record of all rows is maximum . the nation record of this row is east germany gdr ."
] | task110-4e041e5bbea74c23a8f50714d3ccf557 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; points } ; club } ; gilfach goch rfc } = true
Output:
| [
"select the row whose points record of all rows is maximum . the club record of this row is gilfach goch rfc ."
] | task110-c4cd2ecbc5be42009ecb079191c096fa |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_greater_eq { filter_eq { all_rows ; laps ; 64 } ; points ; 15 } = true
Output:
| [
"select the rows whose laps record is equal to 64 . for the points records of these rows , most of them are greater than or equal to 15 ."
] | task110-b60e45b8a9804bedaf9513416c98868a |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_greater_eq { all_rows ; number of electorates ( 2009 ) ; 140000 } = true
Output:
| [
"for the number of electorates 2009 records of all rows , most of them are greater than or equal to 140000 ."
] | task110-7eaed0445c5e40a5ba73ac5e17bac5e2 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; leading scorer } ; 28.5 } = true
Output:
| [
"the average of the leading scorer record of all rows is 28.5 ."
] | task110-9792692e0a0448d6be1bc08c43176bd1 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { max { filter_eq { all_rows ; position ; guard } ; height in ft } ; 6 - 8 } = true
Output:
| [
"select the rows whose position record fuzzily matches to guard . the maximum height in ft record of these rows is 6 8 ."
] | task110-cd8f1b6139044af7b3bfeb496ee23447 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; weeks on top } ; 3 } = true
Output:
| [
"the average of the weeks on top record of all rows is 3 ."
] | task110-07a0063077634073a924a48654b20714 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { filter_eq { all_rows ; dutch cup ; finalist } ; postseason ; champion } = true
Output:
| [
"select the rows whose dutch cup record fuzzily matches to finalist . for the postseason records of these rows , most of them fuzzily match to champion ."
] | task110-155c03fbbb614a47afe9c43ed06d2f92 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { all_rows ; date ; april } = true
Output:
| [
"for the date records of all rows , most of them fuzzily match to april ."
] | task110-4887d8488c864817b7722092777d3ab1 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; attendance } ; 20240 } = true
Output:
| [
"the average of the attendance record of all rows is 20240 ."
] | task110-27607bd703634ac0b4da4225a12204aa |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; host ; kettering } } ; 2 } = true
Output:
| [
"select the rows whose host record fuzzily matches to kettering . the number of such rows is 2 ."
] | task110-1f52f0a1d60a42a88bc1eecf4073af3f |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; notes ; enid } ; built } ; hop { filter_eq { all_rows ; notes ; snowdon } ; built } } = true
Output:
| [
"select the rows whose notes record fuzzily matches to enid . take the built record of this row . select the rows whose notes record fuzzily matches to snowdon . take the built record of this row . the first record is less than the second record ."
] | task110-494c356cea91437c8dbaf08b66ec5cda |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { all_rows ; club team ; plymouth whalers ( ohl ) } } ; eq { hop { filter_eq { all_rows ; club team ; plymouth whalers ( ohl ) } ; player } ; stefan noesen } } = true
Output:
| [
"select the rows whose club team record fuzzily matches to plymouth whalers ohl . there is only one such row in the table . the player record of this unqiue row is stefan noesen ."
] | task110-c76a435a3f22450eb8d4b2b2bee19412 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; points ; 67 } } ; 2 } = true
Output:
| [
"select the rows whose points record is equal to 67 . the number of such rows is 2 ."
] | task110-c64cb63dacce49fb9fbaadaf770b18a8 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { all_rows ; directed by ; guy bee } } ; eq { hop { filter_eq { all_rows ; directed by ; guy bee } ; title } ; family matters } } = true
Output:
| [
"select the rows whose directed by record fuzzily matches to guy bee . there is only one such row in the table . the title record of this unqiue row is family matters ."
] | task110-1ebd70544253497d814d78920ce9a4a1 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; points } ; november } ; 29 } = true
Output:
| [
"select the row whose points record of all rows is maximum . the november record of this row is 29 ."
] | task110-7f61eae809b645d6808cb867028c306d |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { filter_eq { all_rows ; visitor ; spurs } ; attendance ; 1 } ; home } ; jazz } = true
Output:
| [
"select the rows whose visitor record fuzzily matches to spurs . select the row whose attendance record of these rows is 1st maximum . the home record of this row is jazz ."
] | task110-66abe54dbe5e49b9a0a91ae807918834 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { filter_greater { all_rows ; december ; 15 } ; score ; 4-2 } } ; 2 } = true
Output:
| [
"select the rows whose december record is greater than 15 . among these rows , select the rows whose score record fuzzily matches to 42 . the number of such rows is 2 ."
] | task110-d13515fd2c4e47519b0983281d31626e |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { filter_eq { all_rows ; year ; 1967 } ; points } ; 2 } = true
Output:
| [
"select the rows whose year record is equal to 1967 . the sum of the points record of these rows is 2 ."
] | task110-2b2116c6597a4c7db96ebf153a70e70c |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { max { all_rows ; laps } ; 325 } = true
Output:
| [
"the maximum laps record of all rows is 325 ."
] | task110-58863646030f49ab8fe59349ed5154e0 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { all_rows ; viewers ( millions ) } ; 54.22 million } = true
Output:
| [
"the sum of the viewers millions record of all rows is 54.22 million ."
] | task110-fec2036aa7e34cedb231d9f6c55a96aa |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; number of electorates ( 2003 ) } ; name } ; niwari } = true
Output:
| [
"select the row whose number of electorates 2003 record of all rows is maximum . the name record of this row is niwari ."
] | task110-a02047d7118d456f9ba86f6193f041c4 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; score } ; 100 } = true
Output:
| [
"the average of the score record of all rows is 100 ."
] | task110-8e3eb8882d5a463cb701833eb7bcebbf |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; average ratings } ; romaji title } ; densha otoko } = true
Output:
| [
"select the row whose average ratings record of all rows is maximum . the romaji title record of this row is densha otoko ."
] | task110-562634995e7a45e79e08a0856c19aa65 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; time / retired ; +1 lap } } ; 3 } = true
Output:
| [
"select the rows whose time retired record fuzzily matches to +1 lap . the number of such rows is 3 ."
] | task110-6414c9ff74544e9a822df7cd7531d767 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { all_rows ; reason for change ; resigned } = true
Output:
| [
"for the reason for change records of all rows , most of them fuzzily match to resigned ."
] | task110-8ad679d210ae404994927b1ba35a7d6b |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; maximum seating capacity ; unknown } } ; 4 } = true
Output:
| [
"select the rows whose maximum seating capacity record fuzzily matches to unknown . the number of such rows is 4 ."
] | task110-b5485c5140fd487bb17df700c2e5baa8 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; january 19 } = true
Output:
| [
"select the row whose attendance record of all rows is 1st maximum . the date record of this row is january 19 ."
] | task110-c08361cb0a8d4686b1b04d295d4a637c |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { all_rows ; capacity ; 2 } ; stadium } ; sydney sports ground } = true
Output:
| [
"select the row whose capacity record of all rows is 2nd maximum . the stadium record of this row is sydney sports ground ."
] | task110-ea51279d934b41dea38e7c04f6f30542 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; attendance } ; opponent } ; new york giants } = true
Output:
| [
"select the row whose attendance record of all rows is maximum . the opponent record of this row is new york giants ."
] | task110-677e332a422e49b2815dc863b309727c |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; season ; 2009 } ; giant slalom } ; hop { filter_eq { all_rows ; season ; 2011 } ; giant slalom } } = true
Output:
| [
"select the rows whose season record fuzzily matches to 2009 . take the giant slalom record of this row . select the rows whose season record fuzzily matches to 2011 . take the giant slalom record of this row . the first record is less than the second record ."
] | task110-87da7fad48cb4ee691571c77dd882366 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { all_rows ; school / club team ; wisconsin } } ; eq { hop { filter_eq { all_rows ; school / club team ; wisconsin } ; player } ; todd nelson } } = true
Output:
| [
"select the rows whose school club team record fuzzily matches to wisconsin . there is only one such row in the table . the player record of this unqiue row is todd nelson ."
] | task110-5817860dc65f4f829d09dacfd9fe8386 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmin { all_rows ; date of successors formal installation } ; successor } ; john parker hale ( r ) } = true
Output:
| [
"select the row whose date of successors formal installation record of all rows is minimum . the successor record of this row is john parker hale r ."
] | task110-14d864f3809b4e9aad4d264dd08270e6 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { all_rows ; episodes ; 11 } = true
Output:
| [
"for the episodes records of all rows , most of them are equal to 11 ."
] | task110-7db0f27f479a40d79a1ea2b1769e4e53 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; wins } ; .12 } = true
Output:
| [
"the average of the wins record of all rows is .12 ."
] | task110-4be27f00978543cb892d265bb1924d4b |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; channel ; rai 2 } ; launch date } ; hop { filter_eq { all_rows ; channel ; canale 5 } ; launch date } } = true
Output:
| [
"select the rows whose channel record fuzzily matches to rai 2 . take the launch date record of this row . select the rows whose channel record fuzzily matches to canale 5 . take the launch date record of this row . the first record is less than the second record ."
] | task110-fd7d48d4205545a587341535105ec44b |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: all_eq { all_rows ; surface ; clay } = true
Output:
| [
"for the surface records of all rows , all of them fuzzily match to clay ."
] | task110-06a9b058cd4b4f46bdcd7922c0b6bde5 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; position ; m } } ; 4 } = true
Output:
| [
"select the rows whose position record fuzzily matches to m . the number of such rows is 4 ."
] | task110-19c20e4c1b3a4c1494521dad4e6c3092 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; name ; sally foster } ; time } ; hop { filter_eq { all_rows ; name ; anne poleska } ; time } } = true
Output:
| [
"select the rows whose name record fuzzily matches to sally foster . take the time record of this row . select the rows whose name record fuzzily matches to anne poleska . take the time record of this row . the first record is less than the second record ."
] | task110-ec7c5de90a6948c196d229c59d932d6c |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; ceased to be consort ; husband 's death } } ; 3 } = true
Output:
| [
"select the rows whose ceased to be consort record fuzzily matches to husband s death . the number of such rows is 3 ."
] | task110-d68a9c7da55e4a44973747a1ba764206 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; venue ; glasgow } } ; 6 } = true
Output:
| [
"select the rows whose venue record fuzzily matches to glasgow . the number of such rows is 6 ."
] | task110-93c97a106ec54a91b4a362169bbb95da |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { all_rows ; kit maker ; erreà } } ; eq { hop { filter_eq { all_rows ; kit maker ; erreà } ; team } ; middlesbrough } } = true
Output:
| [
"select the rows whose kit maker record fuzzily matches to erreà . there is only one such row in the table . the team record of this unqiue row is middlesbrough ."
] | task110-a3fd1eb7ef3d4f15a5a897cb82d63ffe |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_all { all_rows ; player } } ; 5 } = true
Output:
| [
"select the rows whose player record is arbitrary . the number of such rows is 5 ."
] | task110-50e1796cb21d4d58be07d9ae64ee6f10 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_less { all_rows ; year ; 2010 } } ; 3 } = true
Output:
| [
"select the rows whose year record is less than 2010 . the number of such rows is 3 ."
] | task110-40c0e2305703400cbd72558e4604aaec |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; points ; 0 } } ; 3 } = true
Output:
| [
"select the rows whose points record is equal to 0 . the number of such rows is 3 ."
] | task110-0af1920f7a2c4e2c96963ed9bb88e73b |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_greater_eq { all_rows ; gold ; 1 } = true
Output:
| [
"for the gold records of all rows , most of them are greater than or equal to 1 ."
] | task110-73186de644874e869d5a19b7a4365dfb |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; skip ; xu xiaoming } ; season } ; hop { filter_eq { all_rows ; skip ; wang fengchun } ; season } } = true
Output:
| [
"select the rows whose skip record fuzzily matches to xu xiaoming . take the season record of this row . select the rows whose skip record fuzzily matches to wang fengchun . take the season record of this row . the first record is less than the second record ."
] | task110-b73e99a9b64840c6b17974301c0d9237 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; number } ; unit numbers } ; 254001 - 254032 } = true
Output:
| [
"select the row whose number record of all rows is maximum . the unit numbers record of this row is 254001 254032 ."
] | task110-fa1853475ed0414c8ebe673cd226bec2 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { filter_eq { all_rows ; year ; 1985 } ; points } ; 8 } = true
Output:
| [
"select the rows whose year record is equal to 1985 . the sum of the points record of these rows is 8 ."
] | task110-82e953a25b6442e2bed685d1801002bf |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_less { all_rows ; age ; 25 } } ; 2 } = true
Output:
| [
"select the rows whose age record is less than 25 . the number of such rows is 2 ."
] | task110-c9c690d9722d48139e7002359a38a374 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_less { all_rows ; points ; 15 } } ; eq { hop { filter_less { all_rows ; points ; 15 } ; club ( city / town ) } ; santel 's ( santa elena ) } } = true
Output:
| [
"select the rows whose points record is less than 15 . there is only one such row in the table . the club city town record of this unqiue row is santel s santa elena ."
] | task110-39908549116d4f99a8b57b2fe6e2c0d8 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_greater { all_rows ; crowd ; 10,000 } = true
Output:
| [
"for the crowd records of all rows , most of them are greater than 10,000 ."
] | task110-5d8ce802e01345ddae782106e23158ba |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { all_rows ; winning amount ; rs 10 , 00000 } = true
Output:
| [
"for the winning amount records of all rows , most of them fuzzily match to rs 10 , 00000 ."
] | task110-c410726f7a5448bb8cc9a08707e373cc |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_greater_eq { all_rows ; points ; 20 } } ; 3 } = true
Output:
| [
"select the rows whose points record is greater than or equal to 20 . the number of such rows is 3 ."
] | task110-aef4b9bcf777429fb97fbb798ea9a0b2 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; player ; sam torrance } ; to par } ; hop { filter_eq { all_rows ; player ; ben crenshaw } ; to par } } = true
Output:
| [
"select the rows whose player record fuzzily matches to sam torrance . take the to par record of this row . select the rows whose player record fuzzily matches to ben crenshaw . take the to par record of this row . the first record is less than the second record ."
] | task110-b07b7a70817b48ec92c05213a46be5cb |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: all_eq { all_rows ; played ; 30 } = true
Output:
| [
"for the played records of all rows , all of them are equal to 30 ."
] | task110-20fb629af5164cc5bcc6078499fd27bf |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_greater { all_rows ; crowd ; 20000 } } ; 4 } = true
Output:
| [
"select the rows whose crowd record is greater than 20000 . the number of such rows is 4 ."
] | task110-3dcfd8a87a404148bd87f30922b6b3fe |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { all_rows ; points } ; 490 } = true
Output:
| [
"the sum of the points record of all rows is 490 ."
] | task110-b0076754e50d4bca9e17cb5342be3f85 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; total dismissals } ; no } ; 13 } = true
Output:
| [
"select the row whose total dismissals record of all rows is maximum . the no record of this row is 13 ."
] | task110-1caa1f57051a4507a848cab61821cb5c |