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The translation of ambiguous text presents a challenge for translationsystems, as it requires using the surrounding context to disambiguate theintended meaning as much as possible. While prior work has studied ambiguitiesthat result from different grammatical features of the source and targetlanguage, we study semantic ambiguities that exist in the source (English inthis work) itself. In particular, we focus on idioms that are open to bothliteral and figurative interpretations (e.g., goose egg), and collect TIDE, adataset of 512 pairs of English sentences containing idioms with disambiguatingcontext such that one is literal (it laid a goose egg) and another isfigurative (they scored a goose egg, as in a score of zero). In experiments, wecompare MT-specific models and language models for (i) their preference whengiven an ambiguous subsentence, (ii) their sensitivity to disambiguatingcontext, and (iii) the performance disparity between figurative and literalsource sentences. We find that current MT models consistently translate Englishidioms literally, even when the context suggests a figurative interpretation.On the other hand, LMs are far more context-aware, although there remaindisparities across target languages. Our findings underline the potential ofLMs as a strong backbone for context-aware translation.

That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?