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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 { hop { nth_argmin { filter_eq { all_rows ; coach ; brian noble } ; main article ; 4 } ; lost } ; 7 } = true
Output:
| [
"select the rows whose coach record fuzzily matches to brian noble . select the row whose main article record of these rows is 4th minimum . the lost record of this row is 7 ."
] | task110-906fc1006bcd4a3db48229882e46d266 |
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 ; no built } ; 84 } = true
Output:
| [
"the sum of the no built record of all rows is 84 ."
] | task110-5e7efc30dce64345a2537b02f982d9d3 |
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 ; react ; 5 } ; name } ; christopher williams } = true
Output:
| [
"select the row whose react record of all rows is 5th minimum . the name record of this row is christopher williams ."
] | task110-8a2c9808418644878c22e82df285c7e8 |
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 ; location attendance ; 1 } ; date } ; december 27 } = true
Output:
| [
"select the row whose location attendance record of all rows is 1st maximum . the date record of this row is december 27 ."
] | task110-1cd81832dd23432a8b9e14dbf6b731b0 |
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 ; time / retired ; engine } } ; eq { hop { filter_eq { all_rows ; time / retired ; engine } ; driver } ; jo bonnier } } = true
Output:
| [
"select the rows whose time retired record fuzzily matches to engine . there is only one such row in the table . the driver record of this unqiue row is jo bonnier ."
] | task110-6b90968ef280491bae421c1a4ac32344 |
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 ; points 1 ; 30 } = true
Output:
| [
"for the points 1 records of all rows , most of them are greater than or equal to 30 ."
] | task110-2707910916974fa9949905c23559eaad |
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 ; torque ( nm ) / rpm } ; model / engine } ; 2.0 duratec he } = true
Output:
| [
"select the row whose torque nm rpm record of all rows is maximum . the model engine record of this row is 2.0 duratec he ."
] | task110-1259195233c14061ae43628df33109b5 |
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 ; tries for } ; 475 } = true
Output:
| [
"the sum of the tries for record of all rows is 475 ."
] | task110-0ba099402f46471c9d938e482a7d4711 |
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 ; assists } ; 54 } = true
Output:
| [
"the sum of the assists record of all rows is 54 ."
] | task110-4bc22a4b06f74c27b12659734a54a3bc |
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 } ; 1.67 } = true
Output:
| [
"the average of the score record of all rows is 1.67 ."
] | task110-c1d7582bf14a4db0b5454e2f5828a1d3 |
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 ; cartridge ; .357 sig } ; max pressure } ; hop { filter_eq { all_rows ; cartridge ; .380 acp } ; max pressure } } = true
Output:
| [
"select the rows whose cartridge record fuzzily matches to .357 sig . take the max pressure record of this row . select the rows whose cartridge record fuzzily matches to .380 acp . take the max pressure record of this row . the first record is greater than the second record ."
] | task110-c2f6cfeaae8946249e4a3d06d1e407a4 |
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 ; team ; rothmans honda } = true
Output:
| [
"for the team records of all rows , most of them fuzzily match to rothmans honda ."
] | task110-9de5d7d36e074edd9ee3a61f90de0672 |
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 ; position ; 1 } ; draws } ; hop { filter_eq { all_rows ; position ; 2 } ; draws } } = true
Output:
| [
"select the rows whose position record fuzzily matches to 1 . take the draws record of this row . select the rows whose position record fuzzily matches to 2 . take the draws record of this row . the first record is greater than the second record ."
] | task110-66aff45cd1394f0695da77e8579b29a3 |
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 ; college ; miami ( fla ) } } ; 2 } = true
Output:
| [
"select the rows whose college record fuzzily matches to miami fla . the number of such rows is 2 ."
] | task110-160234c447194bff854b79442870f903 |
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 ; country ; united states } } ; 12 } = true
Output:
| [
"select the rows whose country record fuzzily matches to united states . the number of such rows is 12 ."
] | task110-6060a0082d9249ec94fdc7c755d2eb2f |
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 ; maidens } ; 2 } = true
Output:
| [
"the average of the maidens record of all rows is 2 ."
] | task110-334f0b1d89bd4ee8ad5f21bfaf1f772c |
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 } ; 56 } = true
Output:
| [
"the sum of the points record of all rows is 56 ."
] | task110-2e40cbe314314183a8f5c6bda3fd4cd9 |
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 ; date ; march } } ; eq { hop { filter_eq { all_rows ; date ; march } ; goal } ; 3 } } = true
Output:
| [
"select the rows whose date record fuzzily matches to march . there is only one such row in the table . the goal record of this unqiue row is 3 ."
] | task110-c0756de418364764bdedb5aece887976 |
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 ; car ; 2 } ; player } ; john ritcher } = true
Output:
| [
"select the row whose car record of all rows is 2nd maximum . the player record of this row is john ritcher ."
] | task110-525160d5b82a4099886f3fea0a80eac1 |
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 ; of seats won ; 10 } } ; eq { hop { filter_less { all_rows ; of seats won ; 10 } ; election } ; 1993 } } = true
Output:
| [
"select the rows whose of seats won record is less than 10 . there is only one such row in the table . the election record of this unqiue row is 1993 ."
] | task110-fded0791ef53429988acae1a40de861c |
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 { min { filter_eq { all_rows ; game site ; rfk stadium } ; date } ; september 13 , 1987 } = true
Output:
| [
"select the rows whose game site record fuzzily matches to rfk stadium . the minimum date record of these rows is september 13 , 1987 ."
] | task110-6b572278cd524e9b97021d0324cfd483 |
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 ; event ; ifc wc 13 - warriors challenge } } ; 2 } = true
Output:
| [
"select the rows whose event record fuzzily matches to ifc wc 13 warriors challenge . the number of such rows is 2 ."
] | task110-323a46f5f043442f82074584fe36baa7 |
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 ; agg } ; team 1 } ; canon yaoundé } = true
Output:
| [
"select the row whose agg record of all rows is maximum . the team 1 record of this row is canon yaoundé ."
] | task110-5c9dd299c5d642d49cb9d740d806b248 |
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 ; overall pick ; 3 } ; player } ; dennis byrd } = true
Output:
| [
"select the row whose overall pick record of all rows is 3rd minimum . the player record of this row is dennis byrd ."
] | task110-390dcc0608f041b7b0b2e631f88587cc |
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 ; score ; 68 } = true
Output:
| [
"for the score records of all rows , most of them are equal to 68 ."
] | task110-661b05489fd74b90bba8b095f15e3cd2 |
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 { diff { hop { filter_eq { all_rows ; ship name ; ashantian } ; tonnage ( grt ) } ; hop { filter_eq { all_rows ; ship name ; manchester brigade } ; tonnage ( grt ) } } ; -1125 } = true
Output:
| [
"select the rows whose ship name record fuzzily matches to ashantian . take the tonnage grt record of this row . select the rows whose ship name record fuzzily matches to manchester brigade . take the tonnage grt record of this row . the second record is 1125 larger than the first record ."
] | task110-5ebdca4aa31f4b098899ee45f3790371 |
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 { eq { max { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; 65551 } ; eq { hop { argmax { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; date } ; november 11 , 1979 } } = true
Output:
| [
"select the rows whose opponent record fuzzily matches to san francisco 49ers . the maximum attendance record of these rows is 65551 . the date record of the row with superlative attendance record is november 11 , 1979 ."
] | task110-4be0f0ff015e4e62a4a6ccfa7cf3fe1e |
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 ; notes ; short film } = true
Output:
| [
"for the notes records of all rows , most of them fuzzily match to short film ."
] | task110-339cda0f39a84263872d64d241daea06 |
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 { filter_eq { all_rows ; date ; june 11 } ; high assists } ; hop { filter_eq { all_rows ; date ; june 10 } ; high assists } } = true
Output:
| [
"select the rows whose date record fuzzily matches to june 11 . take the high assists record of this row . select the rows whose date record fuzzily matches to june 10 . take the high assists record of this row . the first record fuzzily matches to the second record ."
] | task110-7a5f7770cf95407d8833280bb6a3b317 |
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 ; place ; 5 } ; result ; 30 % } } ; 2 } = true
Output:
| [
"select the rows whose place record is less than 5 . among these rows , select the rows whose result record is greater than 30 . the number of such rows is 2 ."
] | task110-c2006d0d531a4c3dafc4bdae3fb6014b |
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 ; nation ; sweden } ; silver } ; hop { filter_eq { all_rows ; nation ; denmark } ; silver } } = true
Output:
| [
"select the rows whose nation record fuzzily matches to sweden . take the silver record of this row . select the rows whose nation record fuzzily matches to denmark . take the silver record of this row . the first record is greater than the second record ."
] | task110-36cc1574e27d4360af537556097ab469 |
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 ; livery ; fragonset black } } ; 3 } = true
Output:
| [
"select the rows whose livery record fuzzily matches to fragonset black . the number of such rows is 3 ."
] | task110-8d8e73cdc434449bbb55c398513b8139 |
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 ; season ; 2003 / 04 } ; goals } ; hop { filter_eq { all_rows ; season ; 2004 / 05 } ; goals } } = true
Output:
| [
"select the rows whose season record fuzzily matches to 2003 04 . take the goals record of this row . select the rows whose season record fuzzily matches to 2004 05 . take the goals record of this row . the first record is greater than the second record ."
] | task110-98b941aa95634f00a328a6e8a398b5a2 |
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 ; date ; september 25 } ; attendance } ; hop { filter_eq { all_rows ; date ; september 18 } ; attendance } } = true
Output:
| [
"select the rows whose date record fuzzily matches to september 25 . take the attendance record of this row . select the rows whose date record fuzzily matches to september 18 . take the attendance record of this row . the first record is greater than the second record ."
] | task110-eaa85de7333f45899afa27e73d8bfc2a |
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 ; high points ; 20 } = true
Output:
| [
"for the high points records of all rows , most of them are greater than 20 ."
] | task110-a5a00202ad3b4fe39d345cf87ff00bf8 |
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 ; nationality ; canada } } ; 2 } = true
Output:
| [
"select the rows whose nationality record fuzzily matches to canada . the number of such rows is 2 ."
] | task110-e2236278d05a46af82eea76862e01512 |
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 ; season ; 5 } ; team } ; runcorn highfield } = true
Output:
| [
"select the row whose season record of all rows is 5th minimum . the team record of this row is runcorn highfield ."
] | task110-7c3ccc72a7734176a2094777d4a62367 |
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 ; high points ; eric gordon } = true
Output:
| [
"for the high points records of all rows , most of them fuzzily match to eric gordon ."
] | task110-9f789b5191e7451287fab732a5a2fbdb |
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 ; total } ; 284.5 } = true
Output:
| [
"the average of the total record of all rows is 284.5 ."
] | task110-3f15e5e92cc144ea85f6002f3c21e025 |
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 ; china } } ; 6 } = true
Output:
| [
"select the rows whose location record fuzzily matches to china . the number of such rows is 6 ."
] | task110-d0ac0f2127e34595a97da14098b576b1 |
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_eq { all_rows ; country ; united states } ; score ; 67 } } ; 5 } = true
Output:
| [
"select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record is greater than 67 . the number of such rows is 5 ."
] | task110-0aacccdc1467495eac8fe788d1314b44 |
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 ; founded ; 1800 } } ; eq { hop { filter_less { all_rows ; founded ; 1800 } ; institution } ; university of louisville } } = true
Output:
| [
"select the rows whose founded record is less than 1800 . there is only one such row in the table . the institution record of this unqiue row is university of louisville ."
] | task110-9cbe982ccc6d4cad9085f7ccf43f35c9 |
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 { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } } ; and { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; friendly } ; eq { hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } ; friendly } } } = true
Output:
| [
"select the rows whose date record fuzzily matches to 16 august 2000 . take the competition record of this row . select the rows whose date record fuzzily matches to 22 august 2007 . take the competition record of this row . the first record fuzzily matches to the second record . the competition record of the first row is friendly . the competition record of the second row is friendly ."
] | task110-53bd607c281743739d9cedfec13a30a5 |
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 ; rider ; steve plater } ; speed } ; hop { filter_eq { all_rows ; rider ; denver robb } ; speed } } = true
Output:
| [
"select the rows whose rider record fuzzily matches to steve plater . take the speed record of this row . select the rows whose rider record fuzzily matches to denver robb . take the speed record of this row . the first record is greater than the second record ."
] | task110-d30e4cdd10024e40a86c690cac202b36 |
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 ; time } ; name } ; tyson gay } = true
Output:
| [
"select the row whose time record of all rows is minimum . the name record of this row is tyson gay ."
] | task110-ef4365b691b04f0fb633c8a2e5a3967a |
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 ; rnd ; 3 } ; date } ; 1 march } = true
Output:
| [
"select the row whose rnd record of all rows is 3rd minimum . the date record of this row is 1 march ."
] | task110-60a6db4181f74213a5316bbce8a1ca13 |
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: only { filter_eq { all_rows ; athlete ; tony geal } } = true
Output:
| [
"select the rows whose athlete record fuzzily matches to tony geal . there is only one such row in the table ."
] | task110-a9c1d9b65d7d42d1aa0cb848a46169b1 |
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 ; date ; sunday , november 16 } ; attendance } ; hop { filter_eq { all_rows ; date ; monday , december 22 } ; attendance } } = true
Output:
| [
"select the rows whose date record fuzzily matches to sunday , november 16 . take the attendance record of this row . select the rows whose date record fuzzily matches to monday , december 22 . take the attendance record of this row . the first record is greater than the second record ."
] | task110-551f75d6aeb5430da6dea33668e8c23e |
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 ; crowd } ; 80962 } = true
Output:
| [
"the sum of the crowd record of all rows is 80962 ."
] | task110-b3ea63f386a74ecb92e55b956d84f508 |
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 ; drawn } ; 2.55 } = true
Output:
| [
"the average of the drawn record of all rows is 2.55 ."
] | task110-1ab4694bbb3d478cac9f701642c4b896 |
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 { diff { hop { filter_eq { all_rows ; name ; benito lorenzi } ; rank } ; hop { filter_eq { all_rows ; name ; christian vieri } ; rank } } ; -2 } = true
Output:
| [
"select the rows whose name record fuzzily matches to benito lorenzi . take the rank record of this row . select the rows whose name record fuzzily matches to christian vieri . take the rank record of this row . the second record is 2 larger than the first record ."
] | task110-e834439eeea0423a93e734e4104ec23d |
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 { eq { nth_min { all_rows ; year ; 2 } ; 1974 } ; eq { hop { nth_argmin { all_rows ; year ; 2 } ; partner } ; roscoe tanner } } = true
Output:
| [
"the 2nd minimum year record of all rows is 1974 . the partner record of the row with 2nd minimum year record is roscoe tanner ."
] | task110-3d8f9e9a43b14ccb90ecb55f2e983f9b |
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 ; country ; japan } } ; eq { hop { filter_eq { all_rows ; country ; japan } ; rank } ; 4 } } = true
Output:
| [
"select the rows whose country record fuzzily matches to japan . there is only one such row in the table . the rank record of this unqiue row is 4 ."
] | task110-fece932f51f045bc97a5d497351dd1ac |
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 ; population ( 2011 - 01 - 01 ) ; 511840 } = true
Output:
| [
"for the population 2011 01 01 records of all rows , most of them are greater than 511840 ."
] | task110-ca386681dc62412ea907a52ba45406a4 |
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 ; points ; 0 } } ; eq { hop { filter_eq { all_rows ; points ; 0 } ; artist } ; photogenique } } = true
Output:
| [
"select the rows whose points record is equal to 0 . there is only one such row in the table . the artist record of this unqiue row is photogenique ."
] | task110-0a7e99ca81d046a88f7ba772cf9873f2 |
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 ; notes ; not published in book form } } ; 9 } = true
Output:
| [
"select the rows whose notes record fuzzily matches to not published in book form . the number of such rows is 9 ."
] | task110-6d181e31aab84545be9852ce3c867a6a |
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 ; category ; best actress in a musical } = true
Output:
| [
"for the category records of all rows , most of them fuzzily match to best actress in a musical ."
] | task110-5254406577ad46a1b6b450638739efe2 |
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 ; imports } ; country } ; china } = true
Output:
| [
"select the row whose imports record of all rows is maximum . the country record of this row is china ."
] | task110-6813f6e91beb412482640ffdd8ac349e |
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 ; competition ; european championships } = true
Output:
| [
"for the competition records of all rows , most of them fuzzily match to european championships ."
] | task110-2a3fd8b2dbcf418686292f18235e4a9c |
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 ; nominee ; raymond massey } ; year } ; hop { filter_eq { all_rows ; nominee ; anthony hopkins } ; year } } = true
Output:
| [
"select the rows whose nominee record fuzzily matches to raymond massey . take the year record of this row . select the rows whose nominee record fuzzily matches to anthony hopkins . take the year record of this row . the first record is less than the second record ."
] | task110-3cea75e5230e47ccbf8c3f6bffa4e6ec |
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 ; 11 } ; field } ; cawley memorial stadium } = true
Output:
| [
"select the row whose date record of all rows is 11th minimum . the field record of this row is cawley memorial stadium ."
] | task110-f04a02e81db8471bb83ed28052df727b |
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 ; 1st round ; 2 - 0 } } ; 3 } = true
Output:
| [
"select the rows whose 1st round record fuzzily matches to 2 0 . the number of such rows is 3 ."
] | task110-193e6727b4014c199484170c34ab7824 |
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 ; result ; loss } = true
Output:
| [
"for the result records of all rows , most of them fuzzily match to loss ."
] | task110-41ce4ae216b648c68d27a91b907a6c54 |
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 ; points ; 1 } ; club } ; pentyrch rfc } = true
Output:
| [
"select the row whose points record of all rows is 1st maximum . the club record of this row is pentyrch rfc ."
] | task110-937db46580ea4a2bb1e10ccb0b126047 |
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_greater { filter_greater { all_rows ; elevation ( m ) ; 3000 } ; prominence ( m ) ; 2400 } = true
Output:
| [
"select the rows whose elevation m record is greater than 3000 . for the prominence m records of these rows , all of them are greater than 2400 ."
] | task110-9949b91b122b4de3b2e773a23cf8691b |
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 { less { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } } ; and { eq { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; january 8 , 2003 } ; eq { hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } ; may 19 , 2008 } } } = true
Output:
| [
"select the rows whose winner record fuzzily matches to ryan sutter . take the premiered record of this row . select the rows whose winner record fuzzily matches to jesse csincsak . take the premiered record of this row . the first record is less than the second record . the premiered record of the first row is january 8 , 2003 . the premiered record of the second row is may 19 , 2008 ."
] | task110-4ac3fedcf44a42c2bce1dff7ac428cf2 |
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 ; fedor dmitriev } ; year born } ; hop { filter_eq { all_rows ; player ; anton ponkrashov } ; year born } } = true
Output:
| [
"select the rows whose player record fuzzily matches to fedor dmitriev . take the year born record of this row . select the rows whose player record fuzzily matches to anton ponkrashov . take the year born record of this row . the first record is less than the second record ."
] | task110-6bdfc2ef0ddf4e19aa4e8758a8b69b80 |
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 ; crowd ; 15000 } } ; 3 } = true
Output:
| [
"select the rows whose crowd record is equal to 15000 . the number of such rows is 3 ."
] | task110-f63dbc398905460e967a0485023c9633 |
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 ; school ; emmanuel christian school } ; size } ; hop { filter_eq { all_rows ; school ; wabash high school } ; size } } = true
Output:
| [
"select the rows whose school record fuzzily matches to emmanuel christian school . take the size record of this row . select the rows whose school record fuzzily matches to wabash high school . take the size record of this row . the first record is less than the second record ."
] | task110-4b4897eb9cd942a1abe13ad303b68e7e |
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 { filter_eq { all_rows ; date ; october } ; attendance ; 50000 } = true
Output:
| [
"select the rows whose date record fuzzily matches to october . for the attendance records of these rows , most of them are greater than 50000 ."
] | task110-ff79a75bfa8b4a25bc93ecc091bf230b |
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 ; date ; december } ; game site ; rich stadium } } ; 2 } = true
Output:
| [
"select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to rich stadium . the number of such rows is 2 ."
] | task110-52329e960468430b9b1ca8e3f9b206a3 |
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 ; runs } ; batsmen } ; graham gooch ken mcewan } = true
Output:
| [
"select the row whose runs record of all rows is maximum . the batsmen record of this row is graham gooch ken mcewan ."
] | task110-f77a5bf5a19441c2bd7f2b1641e600e7 |
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 ; 1st ship delivery date ; 2 } ; yard name } ; pendleton shipyards corp } = true
Output:
| [
"select the row whose 1st ship delivery date record of all rows is 2nd maximum . the yard name record of this row is pendleton shipyards corp ."
] | task110-20ff16d1d88e4b68be00ab392f80ff93 |
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 ; air date ; 2006 } = true
Output:
| [
"for the air date records of all rows , all of them fuzzily match to 2006 ."
] | task110-a213697644974cf98a3c60fced4ea968 |
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 ; ceased to be duchess ; husband 's execution } } ; eq { hop { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } ; name } ; louise marie adélaïde de bourbon } } = true
Output:
| [
"select the rows whose ceased to be duchess record fuzzily matches to husband s execution . there is only one such row in the table . the name record of this unqiue row is louise marie adélaïde de bourbon ."
] | task110-07740c61ba90425bb9eca9d4f02d0c84 |
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 ; nation ; romania } ; bronze } ; hop { filter_eq { all_rows ; nation ; soviet union } ; bronze } } = true
Output:
| [
"select the rows whose nation record fuzzily matches to romania . take the bronze record of this row . select the rows whose nation record fuzzily matches to soviet union . take the bronze record of this row . the first record is greater than the second record ."
] | task110-83d425a9d18a41ce807b1a30c926029f |
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 ; pick } ; nhl team } ; hartford whalers } = true
Output:
| [
"select the row whose pick record of all rows is minimum . the nhl team record of this row is hartford whalers ."
] | task110-1273bf9879a649d89e03a024279ca3b3 |
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 ; matches ; 2 } ; name } ; glenn mcgrath } = true
Output:
| [
"select the row whose matches record of all rows is 2nd maximum . the name record of this row is glenn mcgrath ."
] | task110-cd012be285494aaabbb9e9b22b2c9332 |
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 ; state / territory ; queensland } } ; 6 } = true
Output:
| [
"select the rows whose state territory record fuzzily matches to queensland . the number of such rows is 6 ."
] | task110-4badd89d39d94a04bf19e1eb6a10a5e2 |
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 ; crowd } ; 129,800 } = true
Output:
| [
"the sum of the crowd record of all rows is 129,800 ."
] | task110-428e7764109b46ff92b899091d2932f1 |
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 ; first elected ; 1 } ; incumbent } ; dale alford } = true
Output:
| [
"select the row whose first elected record of all rows is 1st maximum . the incumbent record of this row is dale alford ."
] | task110-8c5ebd6dac714eff955bb9ca4453fd36 |
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 } ; 43174 } = true
Output:
| [
"the average of the attendance record of all rows is 43174 ."
] | task110-ffddd17ce8ef47ecbeb265a6c593785b |
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 ; pick } ; 94 } = true
Output:
| [
"the average of the pick record of all rows is 94 ."
] | task110-c114dcfc279c4c8d9a095526e10b5463 |
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 ; laps } ; 19 } = true
Output:
| [
"the average of the laps record of all rows is 19 ."
] | task110-855a14f6ffbb4d0eae929b5851b6eeab |
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 ; curtis hunt } ; rd } ; hop { filter_eq { all_rows ; player ; carl valimont } ; rd } } = true
Output:
| [
"select the rows whose player record fuzzily matches to curtis hunt . take the rd record of this row . select the rows whose player record fuzzily matches to carl valimont . take the rd record of this row . the first record is less than the second record ."
] | task110-41942c7bdcc74fac8091496a2804ad18 |
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 ; opponent ; dallas cowboys } ; attendance } ; hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; attendance } } = true
Output:
| [
"select the rows whose opponent record fuzzily matches to dallas cowboys . take the attendance record of this row . select the rows whose opponent record fuzzily matches to philadelphia eagles . take the attendance record of this row . the first record is greater than the second record ."
] | task110-aa4fc26be5f04c25933b68fa43a63c6a |
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 ; location ; brazil } } ; eq { hop { filter_eq { all_rows ; location ; brazil } ; race name } ; tour de santa catarina } } = true
Output:
| [
"select the rows whose location record fuzzily matches to brazil . there is only one such row in the table . the race name record of this unqiue row is tour de santa catarina ."
] | task110-8a52ce53a55f47e49f72738df8e399c5 |
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 ; entrant ; tyrrell racing organisation } } ; eq { hop { filter_eq { all_rows ; entrant ; tyrrell racing organisation } ; year } ; 1966 } } = true
Output:
| [
"select the rows whose entrant record fuzzily matches to tyrrell racing organisation . there is only one such row in the table . the year record of this unqiue row is 1966 ."
] | task110-4e9f35a407224dd39e0598db632f960d |
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 ; year ; 4 } ; song title } ; hrudayam ekkadunnadi } = true
Output:
| [
"select the row whose year record of all rows is 4th minimum . the song title record of this row is hrudayam ekkadunnadi ."
] | task110-9f96555e1fe3411c805d087e98815e2e |
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 ; passengers } ; city } ; atlanta , ga } = true
Output:
| [
"select the row whose passengers record of all rows is maximum . the city record of this row is atlanta , ga ."
] | task110-91b05f99a55947109fe4dc0a20a46e00 |
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 ; 1st party ; liberal } } ; 4 } = true
Output:
| [
"select the rows whose 1st party record fuzzily matches to liberal . the number of such rows is 4 ."
] | task110-4e09e423f4da450b96a7f84b4605abfd |
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 ; away team score } ; 11.36 } = true
Output:
| [
"the average of the away team score record of all rows is 11.36 ."
] | task110-bd6cbcfa6c7c4f55aca9c8016fbc4de9 |
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 ; crowd ; 2 } ; venue } ; lake oval } = true
Output:
| [
"select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is lake oval ."
] | task110-212a518ec9aa49ccbefc6ea89d6d02ed |
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 ; away captain ; joe darling } = true
Output:
| [
"for the away captain records of all rows , all of them fuzzily match to joe darling ."
] | task110-601ca3b067e34973aaa2fa0ba4b7d498 |
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 ; college ; san diego state } } ; eq { hop { filter_eq { all_rows ; college ; san diego state } ; name } ; freddie keiaho } } = true
Output:
| [
"select the rows whose college record fuzzily matches to san diego state . there is only one such row in the table . the name record of this unqiue row is freddie keiaho ."
] | task110-559e6aa0de174bed936011236547a25e |
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 ; negotiable debt at mid - 2005 ( us dollar bn equivalent ) ; 2 } ; currency } ; us dollar } = true
Output:
| [
"select the row whose negotiable debt at mid 2005 us dollar bn equivalent record of all rows is 2nd maximum . the currency record of this row is us dollar ."
] | task110-bed4f42068c3408da3a856067e403aa3 |
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 ; result ; final } ; jury votes } ; 29 } = true
Output:
| [
"select the rows whose result record fuzzily matches to final . the sum of the jury votes record of these rows is 29 ."
] | task110-77082477168b473794a160a610e1bb29 |
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 { all_rows ; crowd ; 20000 } ; home team score ; 10 } } ; 2 } = true
Output:
| [
"select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose home team score record is greater than 10 . the number of such rows is 2 ."
] | task110-e31a8671ceb94850be883b8ac051431b |