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.
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Azpeitia, A., Cuadros, M., Gaines, S., Rigau, G. (2014). NERC-fr: Supervised Named Entity Recognition for French. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2014. Lecture Notes in Computer Science(), vol 8655. Springer, Cham. https://doi.org/10.1007/978-3-319-10816-2_20
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DOI: https://doi.org/10.1007/978-3-319-10816-2_20
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