Mention Extraction and Linking for SQL Query Generation
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 but also 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.
EMNLP