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Communication Dans Un Congrès Année : 2019

TLR at BSNLP2019: A Multilingual Named Entity Recognition System

Résumé

This paper presents our participation at the shared task on multilingual named entity recognition at BSNLP2019. Our strategy is based on a standard neural architecture for sequence labeling. In particular, we use a mixed model which combines multilingualcontextual and language-specific embeddings. Our only submitted run is based on a voting schema using multiple models, one for each of the four languages of the task (Bulgarian, Czech, Polish, and Russian) and another for English. Results for named entity recognition are encouraging for all languages, varying from 60% to 83% in terms of Strict and Relaxed metrics, respectively.

Dates et versions

hal-02364839 , version 1 (15-11-2019)

Identifiants

Citer

Jose G. Moreno, Elvys Linhares Pontes, Mickaël Coustaty, Antoine Doucet. TLR at BSNLP2019: A Multilingual Named Entity Recognition System. 7th Workshop on Balto-Slavic Natural Language Processing, Aug 2019, Florence, Italy. pp.83-88, ⟨10.18653/v1/W19-3711⟩. ⟨hal-02364839⟩
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