Papers › Semantic Parsing with Syntax- and Table-Aware SQL Generation

Semantic Parsing with Syntax- and Table-Aware SQL Generation

23 Apr 2018ACL 2018 7arXiv:1804.08338archive 2025-07-28

Yibo Sun, Duyu Tang, Nan Duan, Jianshu ji, Guihong Cao, Xiaocheng Feng, Bing Qin, Ting Liu, Ming Zhou

We present a generative model to map natural language questions into SQL queries. Existing neural network based approaches typically generate a SQL query word-by-word, however, a large portion of the generated results are incorrect or not executable due to the mismatch between question words and table contents. Our approach addresses this problem by considering the structure of table and the syntax of SQL language. The quality of the generated SQL query is significantly improved through (1) learning to replicate content from column names, cells or SQL keywords; and (2) improving the generation of WHERE clause by leveraging the column-cell relation. Experiments are conducted on WikiSQL, a recently released dataset with the largest question-SQL pairs. Our approach significantly improves the state-of-the-art execution accuracy from 69.0% to 74.4%.

PaperPDFConference PDF

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

Code

No code repository is listed for this paper in the archive or in Syntology's graph.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Semantic Parsing

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Code Generation WikiSQL STAMP+RL (Sun et al., 2018)+ Exact Match Accuracy 61.0 #4 of 10 Archive leaderboard report
Code Generation WikiSQL STAMP+RL (Sun et al., 2018)+ Execution Accuracy 74.6 #4 of 10 Archive leaderboard report
Code Generation WikiSQL STAMP (Sun et al., 2018)+ Exact Match Accuracy 60.7 #5 of 10 Archive leaderboard report
Code Generation WikiSQL STAMP (Sun et al., 2018)+ Execution Accuracy 74.4 #5 of 10 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections