Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Formats:
json
Sub-tasks:
document-retrieval
Size:
10K - 100K
Tags:
text-retrieval
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") | |
``` |