Semantic parsing with Bayesian tree transducers

Bevan Keeley Jones, Mark Johnson, Sharon Goldwater

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

34 Citations (Scopus)

Abstract

Many semantic parsing models use tree transformations to map between natural language and meaning representation. However, while tree transformations are central to several state-of-the-art approaches, little use has been made of the rich literature on tree automata. This paper makes the connection concrete with a tree transducer based semantic parsing model and suggests that other models can be interpreted in a similar framework, increasing the generality of their contributions. In particular, this paper further introduces a variational Bayesian inference algorithm that is applicable to a wide class of tree transducers, producing state-of-the-art semantic parsing results while remaining applicable to any domain employing probabilistic tree transducers.

Original languageEnglish
Title of host publicationProceedings of the 50th Annual Meeting of the Association for Computational Linguistics, ACL 2012
Place of PublicationStroudsburg, PA
PublisherAssociation for Computational Linguistics (ACL)
Pages488-496
Number of pages9
Volume1
ISBN (Print)9781937284244
Publication statusPublished - 2012
Event50th Annual Meeting of the Association for Computational Linguistics, ACL - 2012 - Jeju Island, Korea, Republic of
Duration: 8 Jul 201214 Jul 2012

Other

Other50th Annual Meeting of the Association for Computational Linguistics, ACL - 2012
CountryKorea, Republic of
CityJeju Island
Period8/07/1214/07/12

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