RESTFul POS tagging WEB service for Sinhala language

Abstract

In the present context of human computer interaction, world has achieved tremendous progress in the field of Natural Language Processing (NLP) applications. The availability of lexical resources is vital to many natural language processing in the field of computation linguistics. But only few languages in the world have the advantage of having enough lexical resources. Though Sinhala language has a long history, Natural Language Processing and computational linguistic aided development of the language is far behind compared with other languages. Researches on NLP for Sinhala language can be pushed by creation of required lexical resources and tools. In this paper we present our research work that was carried out for contributing to NLP based development of the language by developing a part of speech tagger for Sinhala language. The tagger we developed shows over 91% of an accuracy, and the tagger is available as RESTFul web service on the Internet that is freely accessible to the public.