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This paper describes the LIAAD system that was ranked second place in theWord-in-Context challenge (WiC) featured in SemDeep-5. Our solution is based ona novel system for Word Sense Disambiguation (WSD) using contextual embeddingsand full-inventory sense embeddings. We adapt this WSD system, in astraightforward manner, for the present task of detecting whether the samesense occurs in a pair of sentences. Additionally, we show that our solution isable to achieve competitive performance even without using the providedtraining or development sets, mitigating potential concerns related to taskoverfitting

LIAAD at SemDeep-5 Challenge: Word-in-Context (WiC)