Abstract
The growing impact of climate change on coastal areas, particularly active but fragile regions, necessitates collaboration among diverse stakeholders and disciplines to formulate effective environmental protection policies. We introduce a novel specialized corpus comprising 2,491 sentences from 410 scientific abstracts concerning coastal areas, for the Automatic Term Extraction (ATE) and Classification (ATC) tasks. Inspired by the ARDI framework, focused on the identification of Actors, Resources, Dynamics and Interactions, we automatically extract domain terms and their distinct roles in the functioning of coastal systems by leveraging monolingual and multilingual transformer models. The evaluation demonstrates consistent results, achieving an F1 score of approximately 80% for automated term extraction and F1 of 70% for extracting terms and their labels. These findings are promising and signify an initial step towards the development of a specialized Knowledge Base dedicated to coastal areas.
J. Delaunay and T. H. Tran—These authors contributed equally to this work.
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Notes
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Corpus and code are available at https://github.com/jdelaunay/coastal_area_term_extraction.
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Acknowledgments
The work was supported by the TERMITRAD (2020-2019-8510010) project funded by the Nouvelle-Aquitaine Region, France, by the Slovenian Research and Innovation Agency core research program Knowledge Technologies (P2-0103) and the project Cross-lingual and Cross-domain Methods for Terminology Extraction and Alignment, a bilateral project funded by the program PROTEUS under the grant number BI-FR/23-24-PROTEUS006. We express our gratitude to Kenza HERMAN and Geraldine DUBOS for their invaluable assistance in the annotation process.
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Delaunay, J. et al. (2024). CoastTerm: A Corpus for Multidisciplinary Term Extraction in Coastal Scientific Literature. In: Nöth, E., Horák, A., Sojka, P. (eds) Text, Speech, and Dialogue. TSD 2024. Lecture Notes in Computer Science(), vol 15048. Springer, Cham. https://doi.org/10.1007/978-3-031-70563-2_8
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