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. © 2014 Springer International Publishing.
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
Cite
CITATION STYLE
Azpeitia, A., Cuadros, M., Gaines, S., & Rigau, G. (2014). NERC-fr: Supervised named entity recognition for French. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8655 LNAI, pp. 158–165). Springer Verlag. https://doi.org/10.1007/978-3-319-10816-2_20
Readers over time
Readers' Seniority
Readers' Discipline
