SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning

Understand

Synthesizing SQL queries from natural language is a long-standing open problem and has been attracting considerable interest recently.

• Toward solving the problem, the de facto approach is to employ a sequence-to-sequence-style model.
• Such an approach will necessarily require the SQL queries to be serialized.
• Since the same SQL query may have multiple equivalent serializations, training a sequence-to-sequence-style model is sensitive to the choice from one of them.