Target word sense disambiguation system for Kannada language
The process of identifying the correct sense of a word in a specific context is called as Word Sense Disambiguation (WSD). It is essential for communication in a natural language. It is motivated by its use in many crucial applications such as Information retrieval, Information extraction, Machine Translation, Part-of-Speech tagging etc. The aim of our research is to develop a WSD system for target words in Kannada language. This paper presents our preliminary work towards building target word sense disambiguation system for Kannada language. To the best of our knowledge, this is the first attempt towards building WSD system for Kannada. Our work is a mile stone for Kannada language processing activities. In the present work, we exploited the compound words clue and syntactic features in a local context for target word sense disambiguation. It is noticed that, the use of syntax will improve the performance of the WSD system. The Kannada Shallow parser has been used for syntactic analysis. The ambiguous target word is disambiguated using supervised learning techniques. The experiments are conducted using Naive Bayes classifier. We created Kannada Corpora for evaluating the experiments and the results are encouraging.