  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.
