The aim of this thesis is enhance the behaviour of an intelligent agent analysing and suggesting improvements in its self-evaluation of exploration, interpretation and improvisation of general knowledge stored in a knowledge graph. We propose an evaluation of these aspects through metrics that highlight five key components: adherence, cohesion, diversity, serendipity and magnitude. Our work is built on two basic units, namely a triple and a document: in the first step, we extract data from Wikidata, an open structured knowledge graph, pre-processing each page as a document. Each one is composed by statements that we shape in simplified triples that we store and adapt into a graph knowledge base.