arXiv 1609.094052017-01-31cs.CLcs.AI

Evaluating Induced CCG Parsers on Grounded Semantic Parsing

University of Southern California（南加州大学）；University of Edinburgh（爱丁堡大学）；Google（谷歌）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）

Yonatan Bisk, Siva Reddy, John Blitzer, Julia Hockenmaier, Mark Steedman

备注：: EMNLP 2016, Table 2 erratum, Code and Freebase Semantic Parsing data URL

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英文摘要：

We compare the effectiveness of four different syntactic CCG parsers for a semantic slot-filling task to explore how much syntactic supervision is required for downstream semantic analysis. This extrinsic, task-based evaluation provides a unique window to explore the strengths and weaknesses of semantics captured by unsupervised grammar induction systems. We release a new Freebase semantic parsing dataset called SPADES (Semantic PArsing of DEclarative Sentences) containing 93K cloze-style questions paired with answers. We evaluate all our models on this dataset. Our code and data are available at https://github.com/sivareddyg/graph-parser.

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。