Knowledge Tagger: Customizable Semantic Entity Resolution using Ontological Evidence

Knowledge Tagger performs Named Entity Resolution (NER) in texts using relevant domain ontologies and semantic data as background knowledge. Its distinguishing characteristic is its disambiguation-related customization capabilities as it allows users to define and apply custom disambiguation evidence models, based on their knowledge about the domain(s) and expected content of the texts to be analyzed. In this demo we explain the structure and content of such evidence models and we demonstrate how, given a concrete resolution scenario, one may use our system to define and apply them to texts pertaining to this scenario.