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arXiv · 2012.10074

Mention Extraction and Linking for SQL Query Generation

Jianqiang Ma·Zeyu Yan·Shuai Pang·Yang Zhang·Jianping Shen
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Abstract

On the WikiSQL benchmark, state-of-the-art text-to-SQL systems typically take a slot-filling approach by building several dedicated models for each type of slots. Such modularized systems are not only complex butalso of limited capacity for capturing inter-dependencies among SQL clauses. To solve these problems, this paper proposes a novel extraction-linking approach, where a unified extractor recognizes all types of slot mentions appearing in the question sentence before a linker maps the recognized columns to the table schema to generate executable SQL queries. Trained with automatically generated annotations, the proposed method achieves the first place on the WikiSQL benchmark.

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Jianqiang Ma, Zeyu Yan, Shuai Pang, Yang Zhang, Jianping Shen. 2020-12-18. Mention Extraction and Linking for SQL Query Generation. https://doi.org/10.18653/v1/2020.emnlp-main.563

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