@inproceedings{ferreira-etal-2021-priberam,
title = "Priberam Labs at the 3rd Shared Task on {S}lav{NER}",
author = "Ferreira, Pedro and
Cardoso, Ruben and
Mendes, Afonso",
editor = "Babych, Bogdan and
Kanishcheva, Olga and
Nakov, Preslav and
Piskorski, Jakub and
Pivovarova, Lidia and
Starko, Vasyl and
Steinberger, Josef and
Yangarber, Roman and
Marci{\'n}czuk, Micha{\l} and
Pollak, Senja and
P{\v{r}}ib{\'a}{\v{n}}, Pavel and
Robnik-{\v{S}}ikonja, Marko",
booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
month = apr,
year = "2021",
address = "Kiyv, Ukraine",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.bsnlp-1.10",
pages = "86--92",
abstract = "This document describes our participation at the 3rd Shared Task on SlavNER, part of the 8th Balto-Slavic Natural Language Processing Workshop, where we focused exclusively in the Named Entity Recognition (NER) task. We addressed this task by combining multi-lingual contextual embedding models, such as XLM-R (Conneau et al., 2020), with character- level embeddings and a biaffine classifier (Yu et al., 2020). This allowed us to train downstream models for NER using all the available training data. We are able to show that this approach results in good performance when replicating the scenario of the 2nd Shared Task.",
}
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<abstract>This document describes our participation at the 3rd Shared Task on SlavNER, part of the 8th Balto-Slavic Natural Language Processing Workshop, where we focused exclusively in the Named Entity Recognition (NER) task. We addressed this task by combining multi-lingual contextual embedding models, such as XLM-R (Conneau et al., 2020), with character- level embeddings and a biaffine classifier (Yu et al., 2020). This allowed us to train downstream models for NER using all the available training data. We are able to show that this approach results in good performance when replicating the scenario of the 2nd Shared Task.</abstract>
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%0 Conference Proceedings
%T Priberam Labs at the 3rd Shared Task on SlavNER
%A Ferreira, Pedro
%A Cardoso, Ruben
%A Mendes, Afonso
%Y Babych, Bogdan
%Y Kanishcheva, Olga
%Y Nakov, Preslav
%Y Piskorski, Jakub
%Y Pivovarova, Lidia
%Y Starko, Vasyl
%Y Steinberger, Josef
%Y Yangarber, Roman
%Y Marcińczuk, Michał
%Y Pollak, Senja
%Y Přibáň, Pavel
%Y Robnik-Šikonja, Marko
%S Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kiyv, Ukraine
%F ferreira-etal-2021-priberam
%X This document describes our participation at the 3rd Shared Task on SlavNER, part of the 8th Balto-Slavic Natural Language Processing Workshop, where we focused exclusively in the Named Entity Recognition (NER) task. We addressed this task by combining multi-lingual contextual embedding models, such as XLM-R (Conneau et al., 2020), with character- level embeddings and a biaffine classifier (Yu et al., 2020). This allowed us to train downstream models for NER using all the available training data. We are able to show that this approach results in good performance when replicating the scenario of the 2nd Shared Task.
%U https://aclanthology.org/2021.bsnlp-1.10
%P 86-92
Markdown (Informal)
[Priberam Labs at the 3rd Shared Task on SlavNER](https://aclanthology.org/2021.bsnlp-1.10) (Ferreira et al., BSNLP 2021)
ACL
- Pedro Ferreira, Ruben Cardoso, and Afonso Mendes. 2021. Priberam Labs at the 3rd Shared Task on SlavNER. In Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing, pages 86–92, Kiyv, Ukraine. Association for Computational Linguistics.