Mention Extraction and Linking for SQL Query Generation

December 18, 2020 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Jianqiang Ma, Zeyu Yan, Shuai Pang, Yang Zhang, Jianping Shen arXiv ID 2012.10074 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 32 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 4 months ago
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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