ECCE: Entity-centric Corpus Exploration Using Contextual Implicit Networks

In the Digital Age, the analysis and exploration of unstructured document collections is of central importance to members of investigative professions, whether they might be scholars, journalists, paralegals, or analysts. In many of their domains, entities play a key role in the discovery of implicit relations between the contents of documents and thus serve as natural entry points to a detailed manual analysis, such as the prototypical 5Ws in journalism or stock symbols in finance. To assist in these analyses, entity-centric networks have been proposed as a language model that represents document collections as a cooccurrence graph of entities and terms, and thereby enables the visual exploration of corpora. Here, we present ECCE, a web-based application that implements entitycentric networks, augments them with contextual language models, and provides users with the ability to upload, manage, and explore document collections. Our application is available as a web-based service at http://dimtools.uni.kn/ecce.