Semantic Frame Extraction in Multilingual Olfactory Events

Stefano Menini


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.
Anthology ID:
2024.lrec-main.1273
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
14622–14627
Language:
URL:
https://aclanthology.org/2024.lrec-main.1273
DOI:
Bibkey:
Cite (ACL):
Stefano Menini. 2024. Semantic Frame Extraction in Multilingual Olfactory Events. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 14622–14627, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Semantic Frame Extraction in Multilingual Olfactory Events (Menini, LREC-COLING 2024)
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PDF:
https://aclanthology.org/2024.lrec-main.1273.pdf