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