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Lexicon Acquisition with and for Symbolic NLP-Systems – a Bootstrapping Approach.

Kuhn, Jonas ; Eckle-Kohler, Judith ; Rohrer, Christian (1998)
Lexicon Acquisition with and for Symbolic NLP-Systems – a Bootstrapping Approach.
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

We present a method of applying a broad-coverage LFG grammar of German in the process of semi-automatic lexicon acquisition from corpora. The identification of corpus instances that illustrate a certain subcategorization frame uniquely is done by a comparison of the numbers of analyses the grammar assigns to the corpus instances, under the assumption of different hypothetical lexicon entries for the candidate verb. Filtering conditions expressed on the feature representation output by the grammar further restrict the sentences that the automatic extraction step is based on. Experiments show that the grammar-based method produces better results than a method based on patterns in a corpus query language.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 1998
Autor(en): Kuhn, Jonas ; Eckle-Kohler, Judith ; Rohrer, Christian
Art des Eintrags: Bibliographie
Titel: Lexicon Acquisition with and for Symbolic NLP-Systems – a Bootstrapping Approach.
Sprache: Englisch
Publikationsjahr: 1998
Buchtitel: Proceedings of the First International Conference on Language Resources and Evaluation (LREC98)
URL / URN: https://eckle-kohler.de/kuhn_ecklekohler_rohrer_98.pdf
Kurzbeschreibung (Abstract):

We present a method of applying a broad-coverage LFG grammar of German in the process of semi-automatic lexicon acquisition from corpora. The identification of corpus instances that illustrate a certain subcategorization frame uniquely is done by a comparison of the numbers of analyses the grammar assigns to the corpus instances, under the assumption of different hypothetical lexicon entries for the candidate verb. Filtering conditions expressed on the feature representation output by the grammar further restrict the sentences that the automatic extraction step is based on. Experiments show that the grammar-based method produces better results than a method based on patterns in a corpus query language.

ID-Nummer: TUD-CS-1998-0003
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung
Hinterlegungsdatum: 31 Dez 2016 14:29
Letzte Änderung: 10 Sep 2018 18:58
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