Probabilistic Parsing Using Left Corner Language Models

dc.creatorManning, Christopher D.
dc.creatorCarpenter, Bob
dc.date1997-11-17
dc.date.accessioned2026-07-07T02:36:07Z
dc.date.available2026-07-07T02:36:07Z
dc.descriptionWe introduce a novel parser based on a probabilistic version of a left-corner parser. The left-corner strategy is attractive because rule probabilities can be conditioned on both top-down goals and bottom-up derivations. We develop the underlying theory and explain how a grammar can be induced from analyzed data. We show that the left-corner approach provides an advantage over simple top-down probabilistic context-free grammars in parsing the Wall Street Journal using a grammar induced from the Penn Treebank. We also conclude that the Penn Treebank provides a fairly weak testbed due to the flatness of its bracketings and to the obvious overgeneration and undergeneration of its induced grammar.
dc.description12 pages, uses iwpt97.sty
dc.identifierhttps://arxiv.org/abs/cmp-lg/9711003
dc.identifierhttp://arxiv.org/abs/cmp-lg/9711003
dc.identifierProceedings of the Fifth International Workshop on Parsing Technologies, MIT, Boston MA, 1997
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/15801
dc.subjectComputation and Language
dc.titleProbabilistic Parsing Using Left Corner Language Models
dc.typetext

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