An improved parser for data-oriented lexical-functional analysis

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dc.creatorBod, Rens
dc.date2000-09-27
dc.date.accessioned2026-07-07T03:16:35Z
dc.date.available2026-07-07T03:16:35Z
dc.descriptionWe present an LFG-DOP parser which uses fragments from LFG-annotated sentences to parse new sentences. Experiments with the Verbmobil and Homecentre corpora show that (1) Viterbi n best search performs about 100 times faster than Monte Carlo search while both achieve the same accuracy; (2) the DOP hypothesis which states that parse accuracy increases with increasing fragment size is confirmed for LFG-DOP; (3) LFG-DOP's relative frequency estimator performs worse than a discounted frequency estimator; and (4) LFG-DOP significantly outperforms Tree-DOP is evaluated on tree structures only.
dc.description8 pages
dc.identifierhttps://arxiv.org/abs/cs/0009026
dc.identifierhttp://arxiv.org/abs/cs/0009026
dc.identifierProceedings ACL'2000, Hong Kong
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30405
dc.subjectComputation and Language
dc.subjectI.2.7
dc.titleAn improved parser for data-oriented lexical-functional analysis
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