Training and Scaling Preference Functions for Disambiguation

dc.creatorAlshawi, Hiyan
dc.creatorCarter, David
dc.date1994-08-24
dc.date.accessioned2026-07-07T09:09:28Z
dc.date.available2026-07-07T09:09:28Z
dc.descriptionWe present an automatic method for weighting the contributions of preference functions used in disambiguation. Initial scaling factors are derived as the solution to a least-squares minimization problem, and improvements are then made by hill-climbing. The method is applied to disambiguating sentences in the ATIS (Air Travel Information System) corpus, and the performance of the resulting scaling factors is compared with hand-tuned factors. We then focus on one class of preference function, those based on semantic lexical collocations. Experimental results are presented showing that such functions vary considerably in selecting correct analyses. In particular we define a function that performs significantly better than ones based on mutual information and likelihood ratios of lexical associations.
dc.descriptionTo appear in Computational Linguistics (probably volume 20, December 94). LaTeX, 21 pages
dc.identifierhttps://arxiv.org/abs/cmp-lg/9408013
dc.identifierhttp://arxiv.org/abs/cmp-lg/9408013
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/151052
dc.subjectComputation and Language
dc.titleTraining and Scaling Preference Functions for Disambiguation
dc.typetext

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