Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Formats:
json
Sub-tasks:
document-retrieval
Size:
10K - 100K
Tags:
text-retrieval
File size: 1,270 Bytes
75b4e67 1f2b754 75b4e67 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
---
task_categories:
- text-retrieval
task_ids:
- document-retrieval
config_names:
- corpus
tags:
- text-retrieval
dataset_info:
- config_name: default
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: float64
- config_name: corpus
features:
- name: id
dtype: string
- name: text
dtype: string
- config_name: queries
features:
- name: id
dtype: string
- name: text
dtype: string
configs:
- config_name: default
data_files:
- split: test
path: relevance.jsonl
- config_name: corpus
data_files:
- split: corpus
path: corpus.jsonl
- config_name: queries
data_files:
- split: queries
path: queries.jsonl
---
WikiSQL is a dataset comprising 80,654 hand-annotated examples of natural language questions and corresponding SQL queries across 24,241 tables from Wikipedia.
**Usage**
```
import datasets
# Download the dataset
queries = datasets.load_dataset("embedding-benchmark/WikiSQL", "queries")
documents = datasets.load_dataset("embedding-benchmark/WikiSQL", "corpus")
pair_labels = datasets.load_dataset("embedding-benchmark/WikiSQL", "default")
``` |