TLR at BSNLP2019: A Multilingual Named Entity Recognition System

Jose G. Moreno, Elvys Linhares Pontes, Mickael Coustaty, Antoine Doucet


Abstract
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.
Anthology ID:
W19-3711
Volume:
Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | BSNLP | WS
SIG:
SIGSLAV
Publisher:
Association for Computational Linguistics
Note:
Pages:
83–88
Language:
URL:
https://aclanthology.org/W19-3711
DOI:
10.18653/v1/W19-3711
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/W19-3711.pdf
Data
CoNLL-2003