@inproceedings{menini-2024-semantic,
    title = "Semantic Frame Extraction in Multilingual Olfactory Events",
    author = "Menini, Stefano",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.1273",
    pages = "14622--14627",
    abstract = "In this work we present a system for multilingual olfactory information extraction covering six European languages, introducing new models to extract olfactory information from large amounts of text in a structured and scalable way. For the task we rely on a supervised multi-task approach to detect olfactory related text adopting a FrameNet-like structure, identifying the lexical units triggering the smell event and a related set of frame elements.",
}

In this work we present a system for multilingual olfactory information extraction covering six European languages, introducing new models to extract olfactory information from large amounts of text in a structured and scalable way. For the task we rely on a supervised multi-task approach to detect olfactory related text adopting a FrameNet-like structure, identifying the lexical units triggering the smell event and a related set of frame elements.
Menini, Stefano
Semantic Frame Extraction in Multilingual Olfactory Events