Multilingual Named Entity Recognition Using Pretrained Embeddings, Attention Mechanism and NCRF
Abstract
In this paper we tackle multilingual named entity recognition task. We use the BERT Language Model as embeddings with bidirectional recurrent network, attention, and NCRF on the top. We apply multilingual BERT only as embedder without any fine-tuning. We test out model on the dataset of the BSNLP shared task, which consists of texts in Bulgarian, Czech, Polish and Russian languages.- Anthology ID:
- W19-3713
- Volume:
- Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Tomaž Erjavec, Michał Marcińczuk, Preslav Nakov, Jakub Piskorski, Lidia Pivovarova, Jan Šnajder, Josef Steinberger, Roman Yangarber
- Venue:
- BSNLP
- SIG:
- SIGSLAV
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 94–99
- Language:
- URL:
- https://aclanthology.org/W19-3713
- DOI:
- 10.18653/v1/W19-3713
- Cite (ACL):
- Anton Emelyanov and Ekaterina Artemova. 2019. Multilingual Named Entity Recognition Using Pretrained Embeddings, Attention Mechanism and NCRF. In Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing, pages 94–99, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Multilingual Named Entity Recognition Using Pretrained Embeddings, Attention Mechanism and NCRF (Emelyanov & Artemova, BSNLP 2019)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/W19-3713.pdf
- Code
- additional community code