Methodology for bootstrapping relation extraction for the semantic web

Abstract

The paper describes a methodology for bootstrapping relation extraction from unstructured text in the context of GATE, but also applied to the KIM semantic annotation platform. The focus is on identifying a set of relations between entities previously found by named entity recognizer. The methodology is developed and applied to three kinds of relations and evaluated both with the ANNIE system and the default information extraction module of KIM. The methodology covers the problem of identifying the task, the target domain, the development of training and testing corpora, and useful lexical resources, the choice of a particular relation extraction approach. The application of information extraction for the Semantic Web also brings a new interesting dimension of not merely recognizing the entity type, but going into instantiation of entity references and linking them to an entity instance in a semantic repository. © Springer-Verlag Berlin Heidelberg 2006.