Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface

Understand

A natural language database interface (NLDB) can democratize data-driven insights for non-technical users.

• However, existing Text-to-SQL semantic parsers cannot achieve high enough accuracy in the cross-database setting to allow good usability in practice.
• This work presents Turing, a NLDB system toward bridging this gap.
• The cross-domain semantic parser of Turing with our novel value prediction method achieves $75.1\%$ execution accuracy, and $78.3\%$ top-5 beam execution accuracy on the Spider validation set.