@inproceedings{adkins-etal-2025-named,
    title = "Named Entity Recognition for the {I}rish Language",
    author = "Adkins, Jane  and
      Collins, Hugo  and
      Wagner, Joachim  and
      Walsh, Abigail  and
      Davis, Brian",
    editor = {Ojha, Atul Kr.  and
      Giouli, Voula  and
      Mititelu, Verginica Barbu  and
      Constant, Mathieu  and
      Korvel, Gra{\v{z}}ina  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Rademaker, Alexandre},
    booktitle = "Proceedings of the 21st Workshop on Multiword Expressions (MWE 2025)",
    month = may,
    year = "2025",
    address = "Albuquerque, New Mexico, U.S.A.",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.mwe-1.9/",
    pages = "82--96",
    ISBN = "979-8-89176-243-5",
    abstract = "The Irish language has been deemed `definitely endangered' (Moseley, 2012) and has been clas- sified as having `weak or no support' (Lynn, 2023) regarding digital resources in spite of its status as the first official and national language of the Republic of Ireland. This research de- velops the first named entity recognition (NER) tool for the Irish language, one of the essen- tial tasks identified by the Digital Plan for Irish (N{\'i} Chasaide et al., 2022). In this study, we produce a small gold-standard NER-annotated corpus and compare both monolingual and mul- tilingual BERT models fine-tuned on this task. We experiment with different model architec- tures and low-resource language approaches to enrich our dataset. We test our models on a mix of single- and multi-word named entities as well as a specific multi-word named entity test set. Our proposed gaBERT model with the implementation of random data augmentation and a conditional random fields layer demon- strates significant performance improvements over baseline models, alternative architectures, and multilingual models, achieving an F1 score of 76.52. This study contributes to advanc- ing Irish language technologies and supporting Irish language digital resources, providing a basis for Irish NER and identification of other MWE types."
}