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Grammar-based parsers have achieved high performance in the cross-domaintext-to-SQL parsing task, but suffer from low decoding efficiency due to themuch larger number of actions for grammar selection than that of tokens in SQLqueries. Meanwhile, how to better align SQL clauses and question segments hasbeen a key challenge for parsing performance. Therefore, this paper proposesclause-level parallel decoding and alignment loss to enhance twohigh-performance grammar-based parsers, i.e., RATSQL and LGESQL. Experimentalresults of two parsers show that our method obtains consistent improvementsboth in accuracy and decoding speed.

Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level Parallel Decoding and Alignment Loss