Enhanced Word Sense Disambiguation Algorithm for Afaan Oromoo

Abstract

In various circumstances, the same word can mean differently based on the usage of the word in a particular sentence. The aim of word sense disambiguation (WSD) is to precisely understand the meaning of a word in particular usage. WSD utilized in several applications of natural language to interpret an ambiguous word contextually. This paper enhances a statistical algorithm proposed by Abdo [36] that performs a task of WSD for Afaan Oromoo (one of under-resourced language spoken in East Africa by nearly 50% of Ethiopians). The paper evaluates appropriate methods that used to increase the performance of disambiguation for the language with and without morphology consideration. The algorithm evaluated by 249 sentences with four evaluation metrics: recall, precision, F1 and accuracy. The evaluation result has achieved state of the art for Afaan Oromoo. Finally, future direction is highlighted for further research of the task on the language.