Evaluating induced CCG parsers on grounded semantic parsing

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 also provides a unique window into the semantics captured (or missed) by unsupervised grammar induction systems.

Original languageEnglish (US)
Title of host publicationEMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages2022-2027
Number of pages6
ISBN (Electronic)9781945626258
DOIs
StatePublished - 2016
Event2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016 - Austin, United States
Duration: Nov 1 2016Nov 5 2016

Publication series

NameEMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings

Conference

Conference2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016
CountryUnited States
CityAustin
Period11/1/1611/5/16

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Computational Theory and Mathematics

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  • Cite this

    Bisk, Y., Reddy, S., Blitzer, J., Hockenmaier, J., & Steedman, M. (2016). Evaluating induced CCG parsers on grounded semantic parsing. In EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 2022-2027). (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d16-1214