Learning a lexicalized grammar for German

In syntax, the trend nowadays is towards lexicalized grammar formalisms. It is now widely accepted that dividing words into wordclasses may serve as a laborsaving mechanism - but at the same time, it discards all detaile
In syntax, the trend nowadays is towards lexicalized grammar formalisms. It is now widely accepted that dividing words into wordclasses may serve as a laborsaving mechanism - but at the same time, it discards all detailed information on the idiosyncratic behavior of words. And that is exactly the type of information that may be necessary in order to parse a sentence. For learning approaches, however, lexicalized grammars represent a challenge for the very reason that they include so much detailed and specific information, which is difficult to learn. This paper will present an algorithm for learning a link grammar of German. The problem of data sparseness is tackled by using all the available information from partial parses as well as from an existing grammar fragment and a tagger. This is a report about work in progress so there are no representative results available yet.
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Metadaten
Author:Sandra Kübler
URN:urn:nbn:de:hebis:30-1110623
Document Type:Article
Language:German
Date of Publication (online):2008/10/21
Year of first Publication:1998
Publishing Institution:Univ.-Bibliothek Frankfurt am Main
Release Date:2008/10/21
Source:http://jones.ling.indiana.edu/~skuebler/papers/aussi.ps ; (in:) Proceedings of NeMLaP 3/CoNLL98. New Methods in Language Processing and Computational Natural Language Learning - Australia, 1998, S. 11-18
HeBIS PPN:206770529
Dewey Decimal Classification:400 Sprache
Sammlungen:Linguistik
Linguistic-Classification:Linguistik-Klassifikation: Computerlinguistik / Computational linguistics
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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