Fenglin Yin
2023
Conversing with databases: Practical Natural Language Querying
Denis Kochedykov
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Fenglin Yin
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Sreevidya Khatravath
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track
In this work, we designed, developed and released in production DataQue – a hybrid NLQ (Natural Language Querying) system for conversational DB querying. We address multiple practical problems that are not accounted for in public Text-to-SQL solutions – numerous complex implied conditions in user questions, jargon and abbreviations, custom calculations, non-SQL operations, a need to inject all those into pipeline fast and to have guaranteed parsing results for demanding users, cold-start problem. The DataQue processing pipeline for Text-to-SQL translation consists of 10-15 model-based and rule-based components that allows to tightly control the processing.
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