@inproceedings{bakagianni-etal-2025-foodsafesum,
    title = "{F}ood{S}afe{S}um: Enabling Natural Language Processing Applications for Food Safety Document Summarization and Analysis",
    author = "Bakagianni, Juli  and
      Randl, Korbinian  and
      Rocchietti, Guido  and
      Rulli, Cosimo  and
      Nardini, Franco Maria  and
      Trani, Salvatore  and
      Henriksson, Aron  and
      Romanova, Anna  and
      Pavlopoulos, John",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.findings-emnlp.911/",
    doi = "10.18653/v1/2025.findings-emnlp.911",
    pages = "16786--16804",
    ISBN = "979-8-89176-335-7",
    abstract = "Food safety demands timely detection, regulation, and public communication, yet the lack of structured datasets hinders Natural Language Processing (NLP) research. We present and release a new dataset of human-written and Large Language Model (LLM)-generated summaries of food safety documents, plus food safety related metadata. We evaluate its utility on three NLP tasks directly reflecting food safety practices: multilabel classification for organizing documents into domain-specific categories; document retrieval for accessing regulatory and scientific evidence; and question answering via retrieval-augmented generation that improves factual accuracy.We show that LLM summaries perform comparably or better than human ones across tasks. We also demonstrate clustering of summaries for event tracking and compliance monitoring. This dataset enables NLP applications that support core food safety practices, including the organization of regulatory and scientific evidence, monitoring of compliance issues, and communication of risks to the public."
}