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--- |
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language: |
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- en |
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license: |
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- cc-by-4.0 |
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source_datasets: |
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- spider |
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tags: |
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- sql |
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- spider |
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- natsql |
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- text-to-sql |
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- sql finetune |
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dataset_info: |
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features: |
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- name: db_id |
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dtype: string |
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- name: prompt |
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dtype: string |
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- name: ground_truth |
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dtype: string |
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--- |
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# Dataset Card for Spider NatSQL Context Validation |
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### Dataset Summary |
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[Spider](https://arxiv.org/abs/1809.08887) is a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 Yale students |
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The goal of the Spider challenge is to develop natural language interfaces to cross-domain databases. |
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This dataset was created to validate LLMs on the Spider dev dataset with database context using NatSQL. |
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### NatSQL |
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[NatSQL](https://arxiv.org/abs/2109.05153) is an intermediate representation for SQL that simplifies the queries and reduces the mismatch between |
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natural language and SQL. NatSQL preserves the core functionalities of SQL, but removes some clauses and keywords |
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that are hard to infer from natural language descriptions. NatSQL also makes schema linking easier by reducing the |
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number of schema items to predict. NatSQL can be easily converted to executable SQL queries and can improve the |
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performance of text-to-SQL models. |
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### Yale Lily Spider Leaderboards |
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The leaderboard can be seen at https://yale-lily.github.io/spider |
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### Languages |
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The text in the dataset is in English. |
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### Licensing Information |
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The spider dataset is licensed under |
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the [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/legalcode) |
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### Citation |
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``` |
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@article{yu2018spider, |
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title={Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task}, |
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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}, |
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journal={arXiv preprint arXiv:1809.08887}, |
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year={2018} |
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} |
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``` |
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``` |
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@inproceedings{gan-etal-2021-natural-sql, |
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title = "Natural {SQL}: Making {SQL} Easier to Infer from Natural Language Specifications", |
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author = "Gan, Yujian and |
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Chen, Xinyun and |
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Xie, Jinxia and |
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Purver, Matthew and |
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Woodward, John R. and |
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Drake, John and |
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Zhang, Qiaofu", |
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021", |
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month = nov, |
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year = "2021", |
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address = "Punta Cana, Dominican Republic", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2021.findings-emnlp.174", |
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doi = "10.18653/v1/2021.findings-emnlp.174", |
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pages = "2030--2042", |
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} |
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``` |
