inputs stringlengths 2.3k 3.85k | targets stringlengths 43 473 | _template_idx int64 0 9 | _task_source stringclasses 1
value | _task_name stringclasses 1
value | _template_type stringclasses 2
values |
|---|---|---|---|---|---|
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 wheth... | for the year records of all rows , most of them are greater than 1900 . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose club record fuzzily matches to real oviedo . take the wins record of this row . select the rows whose club record fuzzily matches to ca osasuna . take the wins record of this row . the first record is greater than the second record . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose home team score record is greater than 4 . among these rows , select the rows whose venue record fuzzily matches to brunswick street oval . there is only one such row in the table . the home team record of this unqiue row is fitzroy .
| 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
TASK 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. on... | select the rows whose competition record fuzzily matches to friendly match . the number of such rows is 5 .
| 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the row whose individual record of all rows is 2nd minimum . the event record of this row is 2004 oberhof . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification . there is only one such row in the table . the date record of this unqiue row is 28 july 2011 .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | the average of the rebounds record of all rows is 269 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the rows whose winning driver record fuzzily matches to harry schell . the number of such rows is 2 . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
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.
H... | select the rows whose featuring record fuzzily matches to tractators . the minimum released record of these rows is february 2010 . | 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose featuring record fuzzily matches to tractators . the minimum released record of these rows is february 2010 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the championships records of all rows , most of them are greater than or equal to 1 .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the height record of all rows is 198.77 .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
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... | select the rows whose founding university record fuzzily matches to barnard college . there is only one such row in the table . the organization record of this unqiue row is alpha epsilon phi 2 . | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose lost record is equal to 1 . the number of such rows is 5 . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose score record fuzzily matches to w . there is only one such row in the table . the date record of this unqiue row is april 20 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the sum of the votes record of all rows is 65680 . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose surface record fuzzily matches to grass . there is only one such row in the table . the date record of this unqiue row is 19 june 2005 . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Part 1. 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. ... | select the rows whose position record fuzzily matches to catcher . the number of such rows is 2 . | 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Part 1. 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. ... | select the rows whose artist record fuzzily matches to ann breen . take the points record of this row . select the rows whose artist record fuzzily matches to fran meen . take the points record of this row . the first record is 14 larger than the second record . the song record of the first row is oh , darling . the so... | 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the visitor records of all rows , most of them fuzzily match to warriors .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose entry date record of all rows is minimum . the single record of this row is meet me halfway .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose surface record fuzzily matches to grass . there is only one such row in the table . the date record of this unqiue row is 19 june 2005 .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose championship record fuzzily matches to wimbledon . take the year record of this row . select the rows whose championship record fuzzily matches to australian championships . take the year record of this row . the first record is less than the second record . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose lost record is equal to 1 . the number of such rows is 5 .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose score record of all rows is 4th minimum . the player record of this row is geoff ogilvy .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
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... | select the row whose mccain record of all rows is maximum . the county record of this row is eureka . | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose mccain record of all rows is maximum . the county record of this row is eureka .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
TASK 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. on... | select the rows whose winning driver record fuzzily matches to roberval andrade . the number of such rows is 4 .
| 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the party records of all rows , most of them fuzzily match to democrat .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose championship record fuzzily matches to wimbledon . take the year record of this row . select the rows whose championship record fuzzily matches to australian championships . take the year record of this row . the first record is less than the second record .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the position records of all rows , most of them fuzzily match to defence . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the party records of all rows , most of them fuzzily match to democrat . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | the average of the points record of all rows is 34 . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose viewers millions record of all rows is maximum . the title record of this row is about face . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose notes record fuzzily matches to not published in book form . the number of such rows is 9 . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose womens singles record fuzzily matches to li xuerui . take the year record of this row . select the rows whose womens singles record fuzzily matches to juliane schenk . take the year record of this row . the first record is greater than the second record . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Part 1. 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. ... | the average of the viewers record of all rows is 44 . | 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the population records of all rows , most of them are less than 1000 .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the attendance record of all rows is 22526 . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose episodes record of all rows is 4th maximum . the series record of this row is 1 . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | select the row whose episodes record of all rows is 4th maximum . the series record of this row is 1 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose date introduced record fuzzily matches to june . the number of such rows is 5 .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: select the row whose population record of all rows is 3rd maximum . the city record of this row is beijing . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Part 1. 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. ... | the 2nd minimum date record of all rows is jun 25 . the score record of the row with 2nd minimum date record is 2 3 . | 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: select the rows whose aggregate score record fuzzily matches to 0 . there is only one such row in the table . the opposition record of this unqiue row is fc köln . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Detailed Instructions: 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
... | select the rows whose series record is arbitrary . the number of such rows is 7 . | 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose cause of destruction record fuzzily matches to still in existence . there is only one such row in the table . the name record of this unqiue row is great pyramid of giza .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Detailed Instructions: 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
... | select the rows whose event record fuzzily matches to butterfly . there is only one such row in the table . the venue record of this unqiue row is rio de janeiro . | 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the bronze record of all rows is 1.67 .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
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.
H... | select the rows whose location record fuzzily matches to borisov . there is only one such row in the table . the team record of this unqiue row is bate . | 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose finish record is equal to 10 . there is only one such row in the table . the year record of this unqiue row is 1972 . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | for the date records of all rows , all of them fuzzily match to 31 july 1954 . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | select the rows whose name record fuzzily matches to arg . the number of such rows is 2 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Part 1. 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. ... | for the city of license records of all rows , all of them fuzzily match to massachusetts . | 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: select the row whose losses record of all rows is 2nd maximum . the club record of this row is club sestao . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the home team score record of all rows is 17.67 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the maidens record of all rows is 2 . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the frequency records of all rows , most of them are greater than 1.5 ghz .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the matches record of all rows is 8 .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | for the country records of all rows , most of them fuzzily match to soviet union . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose pos record fuzzily matches to dnf . the number of such rows is 4 . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Part 1. 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. ... | select the rows whose viewers households in millions record is less than 18 . the number of such rows is 3 . | 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: for the date records of all rows , all of them fuzzily match to 31 july 1954 .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose name record fuzzily matches to cavendish ex sibyl . take the launched record of this row . select the rows whose name record fuzzily matches to caesar ex ranger . take the launched record of this row . the first record is greater than the second record .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose model record fuzzily matches to aptus ii 10 . take the seconds frame record of this row . select the rows whose model record fuzzily matches to aptus ii 12 . take the seconds frame record of this row . the first record is less than the second record .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: select the row whose place record of all rows is minimum . the player record of this row is chris dimarco .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
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... | select the row whose deaths record of all rows is maximum . the year record of this row is 1867 . | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | the average of the original air date record of all rows is 2009 . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose name english record fuzzily matches to alliance 90 the greens . take the votes 2011 record of this row . select the rows whose name english record fuzzily matches to free democratic party . take the votes 2011 record of this row . the first record is greater than the second record .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose english name record fuzzily matches to capital region of denmark . take the population january 1 , 2008 record of this row . select the rows whose english name record fuzzily matches to region of southern denmark . take the population january 1 , 2008 record of this row . the first record is g... | 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose gp gs record is equal to 14 . there is only one such row in the table . the season record of this unqiue row is 2009 .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the sum of the points record of all rows is 1,357 .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Detailed Instructions: 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
... | select the rows whose event record fuzzily matches to championship test . among these rows , select the rows whose horse record fuzzily matches to donna dm . there is only one such row in the table . the athlete record of this unqiue row is sabine peters . | 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose date record fuzzily matches to 19 november 1997 . take the score record of this row . select the rows whose date record fuzzily matches to 19 november 2003 . take the score record of this row . the first record is greater than the second record . the score record of the first row is 1 0 . the sco... | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: select the row whose goals record of all rows is 3rd maximum . the name record of this row is dean windass . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose original air date record of all rows is minimum . the nick prod record of this row is 1001 .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose date record fuzzily matches to 12 june 1937 . among these rows , select the rows whose crowd record is greater than 20000 . there is only one such row in the table . the home team record of this unqiue row is richmond . the away team record of this unqiue row is carlton . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose weight lbs record of all rows is maximum . the name record of this row is joseph barksdale .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose college junior club team league record fuzzily matches to london knights ohl . the number of such rows is 2 . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: the average of the crowd record of all rows is 17128 . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose first elected record is equal to 1793 . there is only one such row in the table . the incumbent record of this unqiue row is john nicholas . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose position record fuzzily matches to forward . the number of such rows is 3 .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the conditions of access records of all rows , all of them fuzzily match to visa free .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the scored record of all rows is .23 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose number name record fuzzily matches to naval store no 161 . take the date record of this row . select the rows whose number name record fuzzily matches to briggs , dundee no 20 . take the date record of this row . the first record is equal to the second record . the date record of the first row i... | 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose first elected record is equal to 1793 . there is only one such row in the table . the incumbent record of this unqiue row is john nicholas .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose capacity record of all rows is 2nd minimum . the stadium record of this row is stadio italia .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose player record fuzzily matches to sam torrance . take the to par record of this row . select the rows whose player record fuzzily matches to ben crenshaw . take the to par record of this row . the first record is less than the second record . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the races record of all rows is 14.4 .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | select the rows whose club team record fuzzily matches to brisbane broncos . take the established record of this row . select the rows whose club team record fuzzily matches to brisbane bandits . take the established record of this row . the first record is less than the second record .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose score record fuzzily matches to did not play . there is only one such row in the table . the year record of this unqiue row is 1924 .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the date of successors formal installation records of all rows , most of them fuzzily match to elected . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose time record of all rows is minimum . the nationality record of this row is zimbabwe .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose wins record is equal to 7 . there is only one such row in the table . the driver record of this unqiue row is sébastien loeb .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose tournament record fuzzily matches to us open . take the events record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the events record of this row . the first record is greater than the second record .
| 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose class record fuzzily matches to d . among these rows , select the rows whose frequency mhz record is less than 90.0 . the number of such rows is 2 . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the date of successors formal installation records of all rows , most of them fuzzily match to elected .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | select the rows whose first issue record fuzzily matches to august 2008 . the number of such rows is 5 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose new adherents per year record is greater than 0 . for the growth rate records of these rows , most of them are greater than 1.00 .
| 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the rows whose first issue record fuzzily matches to august 2008 . the number of such rows is 5 . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.