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--- |
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license: mit |
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task_categories: |
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- table-question-answering |
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language: |
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- en |
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pretty_name: SQUALL |
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size_categories: |
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- 10K<n<100K |
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--- |
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## SQUALL Dataset |
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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. 5-fold splits are applied to the full dataset (1 fold as dev set at each time). The subset defines which fold is selected as the validation dataset. |
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WARN: alignment data (i.e., `nl_ralign` and `align`) is not implemented. |
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## Source |
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Please refer to [github repo](https://github.com/tzshi/squall/) for source data. |
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## Contact |
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For any issues or questions, kindly email us at: Siyue Zhang ([email protected]). |
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## Citation |
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``` |
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@inproceedings{Shi:Zhao:Boyd-Graber:Daume-III:Lee-2020, |
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Title = {On the Potential of Lexico-logical Alignments for Semantic Parsing to {SQL} Queries}, |
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Author = {Tianze Shi and Chen Zhao and Jordan Boyd-Graber and Hal {Daum\'{e} III} and Lillian Lee}, |
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Booktitle = {Findings of EMNLP}, |
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Year = {2020}, |
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} |
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``` |
