README.md

---
license: mit
task_categories:
- table-question-answering
language:
- en
pretty_name: SQUALL
size_categories:
- 10K<n<100K
---


## SQUALL Dataset
To explore the utility of fine-grained, lexical-level supervision, authors introduce SQUALL, a dataset that enriches 11,276 WikiTableQuestions English-language questions with manually created SQL equivalents plus alignments between SQL and question fragments.

## Code
Please refer to our [github repo](https://github.com/tzshi/squall/) for code implementation.

## Contact
For any issues or questions, kindly email us at: Siyue Zhang (siyue001@e.ntu.edu.sg).

## Citation
```
@inproceedings{Shi:Zhao:Boyd-Graber:Daume-III:Lee-2020,
	Title = {On the Potential of Lexico-logical Alignments for Semantic Parsing to {SQL} Queries},
	Author = {Tianze Shi and Chen Zhao and Jordan Boyd-Graber and Hal {Daum\'{e} III} and Lillian Lee},
	Booktitle = {Findings of EMNLP},
	Year = {2020},
}
```