Nessy: A Hybrid Approach to Named Entity Recognition for German
- 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.
| Author: | Martin Hermann, Michael Hochleitner, Sarah Kellner, Simon Preissner, Desislava Zhekova |
|---|---|
| URN: | https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-3071 |
| Parent Title (English): | Workshop proceedings of the 12th edition of the KONVENS conference |
| 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 |
| First Page: | 139 |
| Last Page: | 143 |
| 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): |  Creative Commons - Namensnennung 3.0 |
