Idiomatic expressions carry figurative meaning that's difficult to capture with standard word embeddings, especially across languages. This paper builds an interpretable graph-based framework annotating 160 idioms from eight languages with cognitive-linguistic features (like containment or concealment), connecting them via similarity graphs. The resulting network clusters idioms by conceptual schema rather than language, aids automatic idiom detection, and enables cross-lingual identification of equivalent expressions better than embedding-based methods. Applications include machine translation systems handling figurative language, cross-lingual NLP tools, and computational tools for linguistics and cognitive science research into shared human conceptual structures.
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