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Named Entity Recognition for German Using Conditional Random Fields and Linguistic Resources

  • This paper presents a Named Entity Recognition system for German based on Conditional Random Fields. The model also includes language-independant features and features computed form large coverage lexical resources. Along side the results themselves, we show that by adding linguistic resources to a probabilistic model, the results improve significantly.

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Metadaten
Author:Patrick Watrin, Louis de Viron, Denis Lebailly, Matthieu Constant, Stéphanie Weiser
URN:https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-3107
ISBN:978-3-934105-47-8
Document Type:Conference Proceeding
Language:English
Date of Publication (online):2014/11/25
Release Date:2014/11/25
Tag:NER; Named entity recognition
GND Keyword:Computerlinguistik
Source:Workshop Proceedings of the 12th KONVENS 2014
PPN:Link zum Katalog
Institutes:Fachbereich III / Informationswissenschaft und Sprachtechnologie
DDC classes:400 Sprache / 400 Sprache, Linguistik
Collections:KONVENS 2014 / Workshop Proceedings of the 12th KONVENS 2014
Licence (German):License LogoCreative Commons - Namensnennung 3.0