@inproceedings{dsouza-etal-2025-mining,
    title = "Mining for Species, Locations, Habitats, and Ecosystems from Scientific Papers in Invasion Biology: {A} Large-Scale Exploratory Study with Large Language Models",
    author = {D{'}Souza, Jennifer  and
      Laubach, Zachary  and
      Mustafa, Tarek Al  and
      Zarrie{\ss}, Sina  and
      Fr{\"u}hst{\"u}ckl, Robert  and
      Illari, Phyllis},
    editor = "Basile, Valerio  and
      Bosco, Cristina  and
      Grasso, Francesca  and
      Ibrohim, Muhammad Okky  and
      Skeppstedt, Maria  and
      Stede, Manfred",
    booktitle = "Proceedings of the 1st Workshop on Ecology, Environment, and Natural Language Processing (NLP4Ecology2025)",
    month = mar,
    year = "2025",
    address = "Tallinn, Estonia",
    publisher = "University of Tartu Library",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.nlp4ecology-1.6/",
    pages = "16--23",
    ISBN = "978-9908-53-114-4",
    abstract = "This study explores the use of large language models (LLMs), specifically GPT-4o, to extract key ecological entities{---}species, locations, habitats, and ecosystems{---}from invasion biology literature. This information is critical for understanding species spread, predicting future invasions, and informing conservation efforts. Without domain-specific fine-tuning, we assess the potential and limitations of GPT-4o, out-of-the-box, for this task, highlighting the role of LLMs in advancing automated knowledge extraction for ecological research and management."
}