Translating Questions to SQL Queries with Generative Parsers Discriminatively Reranked

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Provided by: Association for Computational Linguistics
Topic: Data Management
Format: PDF
In this paper, the authors define models for automatically translating a factoid question in natural language to an SQL query that retrieves the correct answer from a target relational DataBase (DB). They exploit the DB structure to generate a set of candidate SQL queries, which they rerank with an SVM-ranker based on tree kernels. In particular, in the generation phase, they use lexical dependencies in the question and the DB metadata, to build a set of plausible SELECT, WHERE and FROM clauses enriched with meaningful joins.
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