Translating Natural Language to SQL using Pointer-Generator Networks and How Decoding Order Matters

2018-11-13 · Denis Lukovnikov, Nilesh Chakraborty, Jens Lehmann, Asja Fischer

Translating natural language to SQL queries for table-based question answering is a challenging problem and has received significant attention from the research community. In this work, we extend a pointer-generator and investigate the order-matters problem in semantic parsing for SQL. Even though our model is a straightforward extension of a general-purpose pointer-generator, it outperforms early works for WikiSQL and remains competitive to concurrently introduced, more complex models. Moreover, we provide a deeper investigation of the potential order-matters problem that could arise due to having multiple correct decoding paths, and investigate the use of REINFORCE as well as a dynamic oracle in this context.

📄 PDF Abstract BibTeX arXiv:1811.05303

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Tasks

Question Answering Semantic ParsingTable-based Question Answering

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