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arXiv 1810.07942cs.CL

Semantic Parsing for Task Oriented Dialog using Hierarchical Representations

Facebook Conversational AI(Facebook 对话人工智能);Facebook AI Research(Facebook 人工智能研究院)

Sonal Gupta, Rushin Shah, Mrinal Mohit, Anuj Kumar, Mike Lewis

英文摘要:

Task oriented dialog systems typically first parse user utterances to semantic frames comprised of intents and slots. Previous work on task oriented intent and slot-filling work has been restricted to one intent per query and one slot label per token, and thus cannot model complex compositional requests. Alternative semantic parsing systems have represented queries as logical forms, but these are challenging to annotate and parse. We propose a hierarchical annotation scheme for semantic parsing that allows the representation of compositional queries, and can be efficiently and accurately parsed by standard constituency parsing models. We release a dataset of 44k annotated queries (fb.me/semanticparsingdialog), and show that parsing models outperform sequence-to-sequence approaches on this dataset.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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