  Word Sense Disambiguation (WSD), the process of automatically identifying the
meaning of a polysemous word in a sentence, is a fundamental task in Natural
Language Processing (NLP). Progress in this approach to WSD opens up many
promising developments in the field of NLP and its applications. Indeed,
improvement over current performance levels could allow us to take a first step
towards natural language understanding. Due to the lack of lexical resources it
is sometimes difficult to perform WSD for under-resourced languages. This paper
is an investigation on how to initiate research in WSD for under-resourced
languages by applying Word Sense Induction (WSI) and suggests some interesting
topics to focus on.
