NLP & DBpedia: an upward knowledge acquisition spiral
Sebastian Hellmann, Agata Filipowska, Caroline Barrière, Pablo N. Mendes, Dimitris Kontokostas · 2013
Recently, the DBpedia community has experienced an immense increase in activity and we believe, that the time has come to explore the connection between DBpedia & Natural Language Processing (NLP) in a yet unprecedented depth. DBpedia has a long-standing tradition to provide useful data as well as a commitment to reliable Semantic Web technologies and living best practices. As the extraction of the Wikipedia's infoboxes by DBpedia matures, we can shift our focus to new challenges such as extracting information from an unstructured article text as well as becoming a testing ground for multilingual NLP methods. DBpedia has the potential to create an upward knowledge acquisition spiral as it provides a small amount of general knowledge allowing to process text, derive more knowledge, validate this knowledge and improve text processing methods. The goal of this workshop was to present existing research, systems and resources, but also to allow discussion about different points of convergence and divergence of the NLP and DBpedia community with a special focus on challenges that lie ahead. We would like to take part in the debate on how to use DBpedia for NLP and NLP for DBpedia.