Create README.md

README.md

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