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Efficient Deployment of Conversational Natural Language Interfaces over Databases
[article]
2020
arXiv
pre-print
Many users communicate with chatbots and AI assistants in order to help them with various tasks. A key component of the assistant is the ability to understand and answer a user's natural language questions for question-answering (QA). Because data can be usually stored in a structured manner, an essential step involves turning a natural language question into its corresponding query language. However, in order to train most natural language-to-query-language state-of-the-art models, a large
arXiv:2006.00591v2
fatcat:u3xdhyfhsrgrpebwudw2qnz7pu