@inproceedings{emelyanov-artemova-2019-multilingual,
title = "Multilingual Named Entity Recognition Using Pretrained Embeddings, Attention Mechanism and {NCRF}",
author = "Emelyanov, Anton and
Artemova, Ekaterina",
editor = "Erjavec, Toma{\v{z}} and
Marci{\'n}czuk, Micha{\l} and
Nakov, Preslav and
Piskorski, Jakub and
Pivovarova, Lidia and
{\v{S}}najder, Jan and
Steinberger, Josef and
Yangarber, Roman",
booktitle = "Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-3713",
doi = "10.18653/v1/W19-3713",
pages = "94--99",
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.",
}
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<namePart type="given">Michał</namePart>
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<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.</abstract>
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%0 Conference Proceedings
%T Multilingual Named Entity Recognition Using Pretrained Embeddings, Attention Mechanism and NCRF
%A Emelyanov, Anton
%A Artemova, Ekaterina
%Y Erjavec, Tomaž
%Y Marcińczuk, Michał
%Y Nakov, Preslav
%Y Piskorski, Jakub
%Y Pivovarova, Lidia
%Y Šnajder, Jan
%Y Steinberger, Josef
%Y Yangarber, Roman
%S Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F emelyanov-artemova-2019-multilingual
%X 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.
%R 10.18653/v1/W19-3713
%U https://aclanthology.org/W19-3713
%U https://doi.org/10.18653/v1/W19-3713
%P 94-99
Markdown (Informal)
[Multilingual Named Entity Recognition Using Pretrained Embeddings, Attention Mechanism and NCRF](https://aclanthology.org/W19-3713) (Emelyanov & Artemova, BSNLP 2019)
ACL