Implementation of Kadazan Tagger Based on Brill's Method

Abstract

We present and evaluate the implementation of Part of Speech (POS) Tagging for the Kadazan language by using the Transformation-based approach. The main purpose of this study is to develop an automatic POS tagging for the Kadazan language, which had never, been developed before. POS tagging can tag the Kadazan corpus automatically and can help reduce the disambiguation problem of this language. The implementation of this approach in this study is to achieve a better and higher accuracy or at least similar to that of the other tagging approaches such as the statistical and the original rule-based approach. This approach can transform the tags based on the prescribed set of rules. A number of objectives were set in order to achieve the main purpose of this study. Firstly, to apply the lexical and contextual rules for this language. Secondly, to implement the Brill's algorithm based on the set of rules and finally to determine the effectiveness of the Kadazan Part of Speech by using this approach. The tagging system had been trained using four Kadazan corpuses containing 5663 words in all. Based on the evaluation results, the tagging system had achieved around 93% accuracy.