The authors present an interpretable network-based framework for representing idiomatic and figurative meaning across eight typologically diverse languages, totaling 160 conventional expressions. Each expression is annotated with binary conceptual features derived from cognitive-linguistic theory, and pairwise Jaccard similarities define a weighted graph.
- Community detection reveals that idioms cluster by conceptual schema rather than by language, producing a structure consistent with cognitive-linguistic predictions.
- The conceptual network captures unique semantic information not present in distributional embeddings and can be scaled via automatic annotation with LLMs.
- Cross-lingual transfer experiments show that conceptual proximity alone can identify acceptable translation equivalents across five language families, with substantial gains over embedding-based baselines.
- Ablation studies demonstrate that schemas, roles, and valence contribute non-redundantly to the network's organizational properties and performance on idiom detection.
The framework offers an interpretable, cross-linguistically stable representation of idiomatic meaning, combining theoretical grounding with practical utility.