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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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pretty_name: Spider Context Validation Schema Ranked |
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tags: |
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- text-to-sql |
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- SQL |
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- spider |
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- validation |
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- eval |
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- spider-eval |
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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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|
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# Dataset Card for Spider Context Validation |
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### Ranked Schema by ChatGPT |
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The database context used here is generated from ChatGPT after telling it to reorder the schema with the most relevant columns in the beginning of the db_info. |
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### Dataset Summary |
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Spider 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 spider-fine-tuned LLMs with database context. |
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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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``` |
