Papers with TypeSQL
TypeSQL: Knowledge-Based Type-Aware Neural Text-to-SQL Generation (N18-2)
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| Challenge: | Existing systems that can understand natural language questions and generate corresponding SQL queries are not able to do this. |
| Approach: | They propose a novel approach which formats the problem as a slot filling task in a more reasonable way and utilizes type information to better understand rare entities and numbers in the questions. |
| Outcome: | The proposed approach outperforms the prior art on the WikiSQL dataset and can reach 82.6% accuracy, a 17.5% improvement compared to the previous content-sensitive model. |