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arxiv:2012.10074

Mention Extraction and Linking for SQL Query Generation

Published on Dec 18, 2020
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Abstract

A unified extraction-linking approach for text-to-SQL systems improves performance on the WikiSQL benchmark by recognizing slot mentions and mapping them to table schemas.

AI-generated summary

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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