Leveraging Adjective-noun Phrasing Knowledge for Comparison Relation Prediction in Text-to-SQL

Published:

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Introduction

One key component in text-to-SQL is to predict the comparison relations between columns and their values. To the best of our knowledge, no existing models explicitly introduce external common knowledge to address this problem, thus their capabilities of predicting comparison relations are limited beyond training data. In this paper, we propose to leverage adjective-noun phrasing knowledge mined from the web to predict the comparison relations in text-to-SQL. Experimental results on both the original and the re-split Spider dataset show that our approach achieves significant improvement over state-of-the-art methods on comparison relation prediction.

Cite

@inproceedings{liu2019leveraging,
  title={Leveraging Adjective-Noun Phrasing Knowledge for Comparison Relation Prediction in Text-to-SQL},
  author={Liu, Haoyan and Fang, Lei and Liu, Qian and Chen, Bei and Jian-Guang, LOU and Li, Zhoujun},
  booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
  year={2019}
}