SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning

ICLR 2018 Xiaojun XuChang LiuDawn Song

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... (read more)

PDF Abstract

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK LEADERBOARD
Text-To-Sql WikiSQL SQLNet (Seq2set+CA+WE) Accuracy (agg) 90.3% # 2
Accuracy (sel) 90.9% # 2
Accuracy (anywhere) 71.9% # 2