stanford-oval/schema2qa
Schema2QA Question Answering Dataset
This dataset helps researchers and developers create robust question-answering systems for virtual assistants. It takes natural language questions about restaurants, hotels, people, movies, books, and music, and outputs structured commands in ThingTalk, a programming language for intelligent agents. The primary users are natural language processing researchers and developers building conversational AI applications.
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Use this if you are developing or evaluating a natural language understanding model that translates user questions into executable commands for virtual assistants or knowledge graph queries.
Not ideal if you are looking for a pre-trained, ready-to-deploy question-answering system or a dataset for general conversational dialogue without specific structured data goals.
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Aug 22, 2022
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