Polysemy is the type of lexical ambiguity where a word has multiple distinct but related
interpretations. In the past decade, it has been the subject of a great many studies across …

Large Language Models (LLMs) have demonstrated exceptional natural language
understanding abilities and have excelled in a variety of natural language processing (NLP) …

Transformer-based language models have taken many fields in NLP by storm. BERT and its
derivatives dominate most of the existing evaluation benchmarks, including those for Word …

Abstract Machine translation produces marginal accuracy rates for low-resource languages,
but its deep learning model expects to yield improved accuracy with time. This longitudinal …

Colexification occurs when two distinct concepts are lexified by the same word. The term
covers both polysemy and homonymy. We posit and investigate the hypothesis that no pair …

We describe the University of Alberta systems for the SemEval-2022 Task 2 on multilingual
idiomaticity detection. Working under the assumption that idiomatic expressions are …

Deciding whether a semantically ambiguous word is homonymous or polysemous is
equivalent to establishing whether it has any pair of senses that are semantically unrelated …

We describe the University of Alberta systems for the SemEval-2021 Word-in-Context (WiC)
disambiguation task. We explore the use of translation information for deciding whether two …

Word senses are the fundamental unit of description in lexicography, yet it is rarely the case
that different dictionaries reach any agreement on the number and definition of senses in a …

This work aims to address the lack of clear theoretical foundations in computational lexical
semantics, the sub-field of natural language processing pertaining to computing with the …