Datasets:
Tasks:
Text2Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
1K - 10K
ArXiv:
Tags:
text-to-sql
License:
File size: 4,203 Bytes
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---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
- machine-generated
languages:
- en
licenses:
- cc-by-4-0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- conditional-text-generation
task_ids:
- conditional-text-generation-other-stuctured-to-text
paperswithcode_id: spider-1
---
# Dataset Card for [spider]
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://yale-lily.github.io/spider
- **Repository:** https://github.com/taoyds/spider
- **Paper:** https://www.aclweb.org/anthology/D18-1425/
- **Point of Contact:** [Yale LILY](https://yale-lily.github.io/)
### Dataset Summary
Spider is a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 Yale students
The goal of the Spider challenge is to develop natural language interfaces to cross-domain databases
### Supported Tasks and Leaderboards
The leaderboard can be seen at https://yale-lily.github.io/spider
### Languages
The text in the dataset is in English.
## Dataset Structure
### Data Instances
**What do the instances that comprise the dataset represent?**
Each instance is natural language question and the equivalent SQL query
**How many instances are there in total?**
**What data does each instance consist of?**
[More Information Needed]
### Data Fields
* **db_id**: Database name
* **question**: Natural language to interpret into SQL
* **query**: Target SQL query
* **query_toks**: List of tokens for the query
* **query_toks_no_value**: List of tokens for the query
* **question_toks**: List of tokens for the question
### Data Splits
**train**: 7000 questions and SQL query pairs
**dev**: 1034 question and SQL query pairs
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
[More Information Needed]
### Annotations
The dataset was annotated by 11 college students at Yale University
#### Annotation process
#### Who are the annotators?
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
## Additional Information
The listed authors in the homepage are maintaining/supporting the dataset.
### Dataset Curators
[More Information Needed]
The spider dataset is licensed under
the [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/legalcode)
[More Information Needed]
### Citation Information
```
@article{yu2018spider,
title={Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task},
author={Yu, Tao and Zhang, Rui and Yang, Kai and Yasunaga, Michihiro and Wang, Dongxu and Li, Zifan and Ma, James and Li, Irene and Yao, Qingning and Roman, Shanelle and others},
journal={arXiv preprint arXiv:1809.08887},
year={2018}
}
```
### Contributions
Thanks to [@olinguyen](https://github.com/olinguyen) for adding this dataset. |