1. A method for building a relationship hierarchy comprises: obtaining a plurality of relationships from training samples drawn from big data through open information extraction models; grouping the obtained relationships under generic relationships based on similarity; creating sub-groups of the grouped relationships; tagging the training sample with relationship tags to the occurrences of relationships in training samples; building relationship extraction models from the tagged training samples using one or more machine learning approaches; and providing new training samples from the big data; extracting new relationships using natural language processing based open information extraction models; reconciling the new relationships under at least one of the existing generic relationships or a new generic relationship; annotating training samples with the relationships extracted through the open information extraction models; create one or more new relationship extraction models; populating the relationship extraction models with new relationship extraction models that can successfully identify new relationships; and passing the text data through new relationship recognition models to identify new relationships from data using one or more machine Learning models; extract relationships from the big data using the relationship extraction models; building relationship recognition models adapted to identify different forms of generic relationships; resolving the relationships by grouping the similar relationships together and separating the relationships which are syntactically and semantically dissimilar; and reconciling the resolved relationships to build the relationship hierarchy, wherein the relationship hierarchy comprises groups and subgroups of relationships created based on generic relationship similarity based on a contextual aspect and a specialization aspect using a Language and Domain model.