@inproceedings{poncelas-etal-2023-sakura,
title = "Sakura at {S}em{E}val-2023 Task 2: Data Augmentation via Translation",
author = "Poncelas, Alberto and
Tkachenko, Maksim and
Htun, Ohnmar",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.239",
doi = "10.18653/v1/2023.semeval-1.239",
pages = "1718--1722",
abstract = "We demonstrate a simple yet effective approach to augmenting training data for multilingual named entity recognition using translations. The named entity spans from the original sentences are transferred to translations via word alignment and then filtered with the baseline recognizer. The proposed approach outperforms the baseline XLM-Roberta on the multilingual dataset.",
}
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<abstract>We demonstrate a simple yet effective approach to augmenting training data for multilingual named entity recognition using translations. The named entity spans from the original sentences are transferred to translations via word alignment and then filtered with the baseline recognizer. The proposed approach outperforms the baseline XLM-Roberta on the multilingual dataset.</abstract>
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%0 Conference Proceedings
%T Sakura at SemEval-2023 Task 2: Data Augmentation via Translation
%A Poncelas, Alberto
%A Tkachenko, Maksim
%A Htun, Ohnmar
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F poncelas-etal-2023-sakura
%X We demonstrate a simple yet effective approach to augmenting training data for multilingual named entity recognition using translations. The named entity spans from the original sentences are transferred to translations via word alignment and then filtered with the baseline recognizer. The proposed approach outperforms the baseline XLM-Roberta on the multilingual dataset.
%R 10.18653/v1/2023.semeval-1.239
%U https://aclanthology.org/2023.semeval-1.239
%U https://doi.org/10.18653/v1/2023.semeval-1.239
%P 1718-1722
Markdown (Informal)
[Sakura at SemEval-2023 Task 2: Data Augmentation via Translation](https://aclanthology.org/2023.semeval-1.239) (Poncelas et al., SemEval 2023)
ACL