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Nessy: A Hybrid Approach to Named Entity Recognition for German
Abstract
In this paper we present Nessy (Named Entity Searching System) and its application to German in the context of the GermEval 2014 Named Entity Recognition Shared Task (Benikova et al., 2014a). We tackle the challenge by using a combination of machine learning (Naive Bayes classification) and rule-based methods. Altogether, Nessy achieves an F-score of 58.78% on the final test set.
Publikationstyp
ConferencePaper
Autor*in • • • •
Hermann, Martin
Hochleitner, Michael
Kellner, Sarah
Preissner, Simon
Zhekova, Desislava
Erscheinungsdatum
2014
Fachbereich
Institut / Einrichtung
Erschienen in
Workshop proceedings of the 12th edition of the KONVENS conference
Erste Seite
139
Letzte Seite
143
URN
urn:nbn:de:gbv:hil2-opus-3071
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