The goal of the open-domain table QA task is to answer a question based on retrieving and extracting information from a large corpus of structured tables. Currently, the accuracy of the most popular framework in open-...
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ISBN:
(纸本)9781450398336
The goal of the open-domain table QA task is to answer a question based on retrieving and extracting information from a large corpus of structured tables. Currently, the accuracy of the most popular framework in open-domain QA: the two-stage retrieval, is limited by the table retriever. Inspired by the research on text-to-sql, this paper proposes to use execution guidance to enhance the effect of table retrieval. Our contributions are mainly threefold: 1. Proposed using execution-guided method to enhance table retrieval to fully leveraging schema information of tables. 2. Proposed the pure text-to-sql task for open domains. We design a two-stage Table QA framework based on semantic parsing to generate logical forms and answers simultaneously. 3. Proposed an open-domain text-to-sql dataset: Open-domain Wikisql. We change the original Wikisql to become suitable for the Open-domain setting, by removing the approximate tables, decontextualizing the questions, etc. We conducted experiments on the new dataset using BM25 and DPR as the retriever, and HydraNet as the generator of sql. The results show that the execute-guided significantly improves the table retrieval by 19% (DPR in [email protected]) and achieves good performance (accuracy of logical form and execution improves by 12.7% and 13.1%) on end-to-end open-domain text-to-sql tasks as well.
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