Sanskrit is one of the most ancient and richest languages in the world. Its literature boasts of text spanning every facet of life and contains works on mathematics, arts, sciences, religion, philosophy, etc. Unfortunately, the large volume of such works and the relative lack of proficiency in the language have kept treasures in those text hidden from the common man. Unraveling information from these texts in a targeted and systematic manner can not only help in enhancing the knowledge systems but can also revive an interest in the language.
Sanskrit enjoys one of the largest and most varied literature in the whole world. Extracting the knowledge from it, however, is a challenging task due to multiple reasons including complexity of the language and paucity of standard natural language processing tools. Therefore, we explore the construction of knowledge graphs through the process of manual annotation of a Sanskrit text, Vālmīki Rāmāyaṇa. We have developed a comprehensive NLP annotation tool, Antarlekhaka, which is being used for this large scale annotation task.
Hrishikesh Terdalkar
Postdoctoral Researcher
My research lies in the intersection of Computational Linguistics, Natural Language Processing, and Graph Databases with a particular emphasis on low-resource languages such as Sanskrit and other Indian languages. I am committed to pioneering NLP innovations that have a real-world impact. I enjoy building user-friendly GUIs and CLIs for various applications. My interests also include Artificial Intelligence, Databases, Human-Computer Interaction, Information Retrieval, and Data Mining.