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We describe the University of Alberta systems for the SemEval-2022 Task 2 onmultilingual idiomaticity detection. Working under the assumption thatidiomatic expressions are noncompositional, our first method integratesinformation on the meanings of the individual words of an expression into abinary classifier. Further hypothesizing that literal and idiomatic expressionstranslate differently, our second method translates an expression in context,and uses a lexical knowledge base to determine if the translation is literal.Our approaches are grounded in linguistic phenomena, and leverage existingsources of lexical knowledge. Our results offer support for both approaches,particularly the former.

UAlberta at SemEval 2022 Task 2: Leveraging Glosses and Translations for Multilingual Idiomaticity Detection