Modelling metaphorical conceptualisation in Traditional Chinese Medicine terminology

Abstract

Metaphorical conceptualisation is central to the structuring of specialised knowledge in Traditional Chinese Medicine (TCM), yet poses challenges for terminology description in cross-cultural contexts. This study examines how metaphor-based conceptual structures in TCM can be modelled for terminology description and explores the methodological implications of externalising such models through the constrained use of multimodal generative artificial intelligence (GAI).

Focusing on Zang–Xiang theory, the study adopts metaphorical Idealized Cognitive Models (m-ICMs) (

) as theory-driven modelling resources and instantiates them through analysis of a Chinese–English parallel corpus. These models are then externalised through constrained multimodal generation to examine alignment and divergence between modelled conceptual structures and generated outputs. The findings show that m-ICMs provide a structured and relational framework for modelling metaphor-based terminology, while multimodal externalisation was particularly selective in cases involving high conceptual density and cultural embedding. A small bilingual prototype consolidates corpus evidence, m-ICM modelling and representational choices. Multimodal GAI thus provides a methodological setting for examining cross-cultural terminological representation.