Semantic Analysis Using Dependency Tree Construction for Sanskrit Language

Processing of natural language for extraction of the meaning is a challenge in the field of artificial intelligence. Research work in this area is being carried out in most of the Indian and foreign languages by analyzing the grammatical aspect of these languages. Sanskrit, a language that possesses a definite rule-based structure given by Panini, has a great potential in the field of semantic extraction. Hence, Sanskrit and computational linguistic are strongly associated. As given in the grammar of Sanskrit language, its case endings are strong identifiers of the respective word in the sentence. To extract the semantic from the language, dependencies amongst the words of a sentence are developed, and the semantic role of words is identified (e.g., agent, object, etc.). In this work, an algorithm has been developed for creating a dependency-based structure for the sentence in Sanskrit by analyzing the features given by the Part of Speech (POS) tags. Dependency Tags (DTs) are used to relate the verb with other words in a sentence. POS tags give the syntactic information and DT gives the semantic information. Mapping between the two is established in the proposed algorithm and its analysis is done. Sanskrit, being an order-free language, imposes a great challenge for the development of dependency-based structure for the sentence. This paper is an effort in the same direction. Such representations are useful for applications such as knowledge representation, query-based system and machine learning.