@inproceedings{weijers-bloem-2025-evaluation,
    title = "An evaluation of Named Entity Recognition tools for detecting person names in philosophical text",
    author = "Weijers, Ruben  and
      Bloem, Jelke",
    editor = {H{\"a}m{\"a}l{\"a}inen, Mika  and
      {\"O}hman, Emily  and
      Bizzoni, Yuri  and
      Miyagawa, So  and
      Alnajjar, Khalid},
    booktitle = "Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities",
    month = may,
    year = "2025",
    address = "Albuquerque, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.nlp4dh-1.36/",
    pages = "418--425",
    ISBN = "979-8-89176-234-3",
    abstract = "For philosophers, mentions of the names of other philosophers and scientists are an important indicator of relevance and influence. However, they don{'}t always come in neat citations, especially in older works. We evaluate various approaches to named entity recognition for person names in 20th century, English-language philosophical texts. We use part of a digitized corpus of the works of W.V. Quine, manually annotated for person names, to compare the performance of several systems: the rule-based edhiphy, spaCy{'}s CNN-based system, FLAIR{'}s BiLSTM-based system, and SpanBERT, ERNIE-v2 and ModernBERT{'}s transformer-based approaches. We also experiment with enhancing the smaller models with domain-specific embedding vectors. We find that both spaCy and FLAIR outperform transformer-based models, perhaps due to the small dataset sizes involved."
}