Treebank based deep grammar acquisition and Part-Of-Speech Tagging for Sanskrit sentences

Sanskrit since many thousands of years has been the oriental language of India. It is the base for most of the Indian Languages. Ambiguity is inherent in the Natural Language sentences. Here, one word can be used in multiple senses. Morphology process takes word in isolation and fails to disambiguate correct sense of a word. Part-Of-Speech Tagging (POST) takes word sequences in to consideration to resolve the correct sense of a word present in the given sentence. Efficient POST have been developed for processing of English, Japanese, and Chinese languages but it is lacking for Indian languages. In this paper our work present simple rule-based POST for Sanskrit language. It uses rule based approach to tag each word of the sentence. These rules are stored in the database. It parses the given Sanskrit sentence and assigns suitable tag to each word automatically. We have tested this approach for 15 tags and 100 words of the language this rule based tagger gives correct tags for all the inflected words in the given sentence.