@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.",
}

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.
Poncelas, Alberto Tkachenko, Maksim Htun, Ohnmar
Sakura at SemEval-2023 Task 2: Data Augmentation via Translation