Paulin Melatagia Yonta ; Michael Franklin Mbouopda - Named Entity Recognition in Low-resource Languages using Cross-lingual distributional word representation

arima:6439 - Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, September 29, 2020, Volume 33 - 2020 - Special issue CRI 2019 - https://doi.org/10.46298/arima.6439
Named Entity Recognition in Low-resource Languages using Cross-lingual distributional word representation

Authors: Paulin Melatagia Yonta ; Michael Franklin Mbouopda

Named Entity Recognition (NER) is a fundamental task in many NLP applications that seek to identify and classify expressions such as people, location, and organization names. Many NER systems have been developed, but the annotated data needed for good performances are not available for low-resource languages, such as Cameroonian languages. In this paper we exploit the low frequency of named entities in text to define a new suitable cross-lingual distributional representation for named entity recognition. We build the first Ewondo (a Bantu low-resource language of Cameroon) named entities recognizer by projecting named entity tags from English using our word representation. In terms of Recall, Precision and F-score, the obtained results show the effectiveness of the proposed distributional representation of words


Volume: Volume 33 - 2020 - Special issue CRI 2019
Published on: September 29, 2020
Accepted on: July 27, 2020
Submitted on: April 29, 2020
Keywords: Low resource language,Annotation Projection,Neural Network,Named Entity Recognition,Natural Language Processing,Projection d'annotations,Réseau de neurones,Reconnaissance des Entités Nommées,Langue peu dotée,Inter-linguistique,Traitement Automatique du Langage Naturel,Natural Language Processing,Named Entity Recognition,Neural Network,Annotation Projection,Low resource language,Cross-lingual MOTS-CLES : Traitement Automatique du Langage Naturel,[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing,[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG],[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]


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