@inproceedings{fonseca-vieira-2026-larger,
    title = "A Larger Annotated Corpus of {P}ortuguese Coreference",
    author = "Fonseca, Evandro  and
      Vieira, Renata",
    editor = "Souza, Marlo  and
      de-Dios-Flores, Iria  and
      Santos, Diana  and
      Freitas, Larissa  and
      Souza, Jackson Wilke da Cruz  and
      Ribeiro, Eug{\'e}nio",
    booktitle = "Proceedings of the 17th International Conference on Computational Processing of {P}ortuguese ({PROPOR} 2026) - Vol. 2",
    month = apr,
    year = "2026",
    address = "Salvador, Brazil",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-dnd/2026.propor-2.33/",
    pages = "247--254",
    ISBN = "979-8-89176-387-6",
    abstract = "Coreference resolution is a crucial task in natural language processing (NLP) that aims to identify and link expressions in a text that refer to the same entity. However, the lack of annotated data for coreference resolution in Portuguese has hindered the development of robust and accurate systems for this language. In this paper, we present an assessment of coreference annotation utilizing large language models (LLMs) for Portuguese: LLM-PREF is proposed to annotate coreference in Portuguese texts. It was evaluated and compared to a system previously proposed in the literature. The results show that although the model{'}s world knowledge and inference capacity are quite rich - allowing it to recognize complex coreference patterns, including the pronominal anaphora phenomenon - it does not excel the previously developed rule based system."
}