Can Subcategorisation Probabilities Help a Statistical Parser?

dc.creatorCarroll, John
dc.creatorMinnen, Guido
dc.creatorBriscoe, Ted
dc.date1998-06-21
dc.date.accessioned2026-07-07T02:36:16Z
dc.date.available2026-07-07T02:36:16Z
dc.descriptionResearch into the automatic acquisition of lexical information from corpora is starting to produce large-scale computational lexicons containing data on the relative frequencies of subcategorisation alternatives for individual verbal predicates. However, the empirical question of whether this type of frequency information can in practice improve the accuracy of a statistical parser has not yet been answered. In this paper we describe an experiment with a wide-coverage statistical grammar and parser for English and subcategorisation frequencies acquired from ten million words of text which shows that this information can significantly improve parse accuracy.
dc.description9 pages, uses colacl.sty
dc.identifierhttps://arxiv.org/abs/cmp-lg/9806013
dc.identifierhttp://arxiv.org/abs/cmp-lg/9806013
dc.identifier6th Workshop on Very Large Corpora, Montreal, Canada, 1998
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/15857
dc.subjectComputation and Language
dc.titleCan Subcategorisation Probabilities Help a Statistical Parser?
dc.typetext

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