An Evidence-based Veri cation Approach to Extract Entities and Relations for Knowledge Base Population

This paper presents an approach to automatically extract entities and relationships from textual documents. The main goal is to populate a knowledge base that hosts this structured information about domain entities. The extracted entities and their expected relationships are veri ed using two evidence based techniques: classi cation and linking. This last process also enables the linking of our knowledge base to other sources which are part of the Linked Open Data cloud. We demonstrate the bene t of our approach through series of experiments with real-world datasets.