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On the WikiSQL benchmark, state-of-the-art text-to-SQL systems typically takea slot-filling approach by building several dedicated models for each type ofslots. Such modularized systems are not only complex butalso of limitedcapacity for capturing inter-dependencies among SQL clauses. To solve theseproblems, this paper proposes a novel extraction-linking approach, where aunified extractor recognizes all types of slot mentions appearing in thequestion sentence before a linker maps the recognized columns to the tableschema to generate executable SQL queries. Trained with automatically generatedannotations, the proposed method achieves the first place on the WikiSQLbenchmark.

Mention Extraction and Linking for SQL Query Generation