NERC-fr: Supervised Named Entity Recognition for French

Egileak: Andoni Azpeitia, Montse Cuadros, Seán Gaines, German Rigau

Data: 31.01.2014


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Abstract

Currently there are only few available language resources for French. Additionally there is a lack of available language models for for tasks such as Named Entity Recognition and Classification (NERC) which makes difficult building natural language processing systems for this language. This paper presents a new publicly available supervised Apache OpenNLP NERC model that has been trained and tested under a maximum entropy approach. This new model achieves state of the art results for French when compared with another systems. Finally we have also extended Apache OpenNLP libraries to support part-of-speech feature extraction component which has been used for our experiments.

BIB_text

@Article {
author = {Andoni Azpeitia, Montse Cuadros, Seán Gaines, German Rigau},
title = {NERC-fr: Supervised Named Entity Recognition for French},
pages = {158-165},
volume = {8655},
keywds = {

Named Entities, Language Resources, French


}
abstract = {

Currently there are only few available language resources for French. Additionally there is a lack of available language models for for tasks such as Named Entity Recognition and Classification (NERC) which makes difficult building natural language processing systems for this language. This paper presents a new publicly available supervised Apache OpenNLP NERC model that has been trained and tested under a maximum entropy approach. This new model achieves state of the art results for French when compared with another systems. Finally we have also extended Apache OpenNLP libraries to support part-of-speech feature extraction component which has been used for our experiments.


}
isbn = {978-3-319-10815-5 (Print)},
date = {2014-01-31},
year = {2014},
}
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