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dc.contributor.authorNederhof, Mark Jan
dc.date.accessioned2016-08-12T23:34:21Z
dc.date.available2016-08-12T23:34:21Z
dc.date.issued2016-08-12
dc.identifier.citationNederhof , M J 2016 , Transition-based dependency parsing as latent-variable constituent parsing . in Proceedings of the SIGFSM Workshop on Statistical NLP and Weighted Automata . Association for Computational Linguistics , Berlin , pp. 21-31 , 54th Annual meeting of the Association for Computational Linguistics , Berlin , Germany , 7/08/16 .en
dc.identifier.citationconferenceen
dc.identifier.isbn9781945626135
dc.identifier.otherPURE: 243585471
dc.identifier.otherPURE UUID: ac34e2d7-eac6-4eca-b42a-2a680c54f30f
dc.identifier.otherORCID: /0000-0002-1845-6829/work/46002698
dc.identifier.urihttps://hdl.handle.net/10023/9298
dc.description.abstractWe provide a theoretical argument that a common form of projective transition-based dependency parsing is less powerful than constituent parsing using latent variables. The argument is a proof that, under reasonable assumptions, a transition-based dependency parser can be converted to a latent-variable context-free grammar producing equivalent structures.
dc.format.extent11
dc.language.isoeng
dc.publisherAssociation for Computational Linguistics
dc.relation.ispartofProceedings of the SIGFSM Workshop on Statistical NLP and Weighted Automataen
dc.rights© 2016, Association for Computational Linguistics. This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at http://www.aclweb.org/anthology/W16-2403en
dc.subjectAutomata theoryen
dc.subjectParsing algorithmsen
dc.subjectP Language and Literatureen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectNDASen
dc.subject.lccPen
dc.subject.lccQA75en
dc.titleTransition-based dependency parsing as latent-variable constituent parsingen
dc.typeConference itemen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.date.embargoedUntil2016-08-12


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