While being an important pillar of human society, legal domain consists of large corpora of complex documents about different aspects such as laws or court judgements. In recent years, knowledge graphs have become a prominent solution to represent such complex information in semantically rich machine readable manner allowing access to other AI powered downstream applications. In this work, we aim to construct a reliable knowledge graph from Legal domain corpus that may be utilized by researchers and the application developers working in legal domain.The source dataset chosen is the Indian Legal Court Judgements and NyOn1 (Nyaya Ontology) has been utilized for conceptualization. A framework that consists of entity extraction, relation extraction, triple construction is used to convert the legal text into RDF triples. The knowledge graph thus built has been quantitatively evaluated over a small random sample with reasonable results.