Parsing with the Shortest Derivation

dc.creatorBod, Rens
dc.date2000-09-27
dc.date.accessioned2026-07-07T03:16:35Z
dc.date.available2026-07-07T03:16:35Z
dc.descriptionCommon wisdom has it that the bias of stochastic grammars in favor of shorter derivations of a sentence is harmful and should be redressed. We show that the common wisdom is wrong for stochastic grammars that use elementary trees instead of context-free rules, such as Stochastic Tree-Substitution Grammars used by Data-Oriented Parsing models. For such grammars a non-probabilistic metric based on the shortest derivation outperforms a probabilistic metric on the ATIS and OVIS corpora, while it obtains very competitive results on the Wall Street Journal corpus. This paper also contains the first published experiments with DOP on the Wall Street Journal.
dc.description7 pages
dc.identifierhttps://arxiv.org/abs/cs/0009025
dc.identifierhttp://arxiv.org/abs/cs/0009025
dc.identifierProceedings COLING'2000, with a minor correction
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30404
dc.subjectComputation and Language
dc.subjectI.2.7
dc.titleParsing with the Shortest Derivation
dc.typetext

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