An efficient part-of-speech tagger rule-based approach of Sanskrit language analysis

Abstract

The versatility and depth of Sanskrit have led to its designation as a universal syntax. The significance of grammar in language translation cannot be exaggerated. Grammar pertains to the structural arrangement of a sentence. It consists of regulations and guidelines. POS tagging is the process of assigning the appropriate part of speech to each word in a phrase. Additionally, it associates with adjacent and comparable words inside a phrase or sentence. The process of morphology involves the separation of phrases and does not determine the correct meaning. Parts of Speech Tagging (POST) consider word sequences to ascertain the accurate interpretation of a word inside a given sentence. Russian, English, and Japanese, in contrast to Indian languages, have developed efficient POST for processing. POS tagging is primarily performed using rule-based, stochastic, and transformation-based methods. The paper will concentrate on the examination of the structure and meaning of Sanskrit sentences. This paper utilizes Lex and Yacc to create a part-of-speech rule-based tagger for Sanskrit. The tagger employs a concise collection of elementary principles to produce sequences of tokens, along with a limited lexicon or vocabulary to identify potential tags for each word. The database maintains a record of these regulations. The system automatically analyzes the provided sentence and assigns the appropriate tags to each word.