Medical-FLAVORS-AECC: Spanish Oncological Metaphors Dataset

Lucia Pitarch, Jordi Bernad, Sergio LUIS Ojeda Trueba, Alec Sánchez-Montero, Maxim Ionov, Emma Anglés-Herrero, Ángel Óscar Corona Beomont, Gemma Bel-Enguix


Abstract
Metaphors play a central role in cancer narratives, helping patients and practitioners articulate complex experiences and technical concepts. While cancer metaphors in English have been extensively studied, Spanish remains underexplored in this regard, despite its global importance and rich cultural variation. This paper presents a new dataset of Spanish cancer metaphors designed to address these gaps. The resource comprises over 80K annotated words drawn from diverse forum posts, with detailed documentation of lexical units, contextual versus basic meanings, and inter-annotator agreements. To construct the dataset, we adapted the Metaphor Identification Procedure (MIP) for Spanish medical discourse, proposing methodological refinements to challenges such as defining lexical units or domain-specific Basic Meaning labels.
Anthology ID:
2026.cl4health-1.15
Volume:
Proceedings of the Third Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC 2026
Month:
May
Year:
2026
Address:
Palma, Mallorca (Spain)
Editors:
Deepak Gupta, Paul Thompson, Sophia Ananiadou, Dina Demner-Fushman
Venues:
CL4Health | WS
SIG:
Publisher:
ELRA Language Resources Association (ELRA)
Note:
Pages:
159–170
Language:
External URL:
https://lrec.elra.info/lrec2026-ws-cl4health-15
DOI:
10.63317/5dfcbwok85xr
Bibkey:
Cite (ACL):
Lucia Pitarch, Jordi Bernad, Sergio LUIS Ojeda Trueba, Alec Sánchez-Montero, Maxim Ionov, Emma Anglés-Herrero, Ángel Óscar Corona Beomont, and Gemma Bel-Enguix. 2026. Medical-FLAVORS-AECC: Spanish Oncological Metaphors Dataset. In Proceedings of the Third Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC 2026, pages 159–170, Palma, Mallorca (Spain). ELRA Language Resources Association (ELRA).
Cite (Informal):
Medical-FLAVORS-AECC: Spanish Oncological Metaphors Dataset (Pitarch et al., CL4Health 2026)
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