Poster – Paper 611

Language Agnostic Dictionary Extraction Alfredo Alba, Anni Coden, Anna Lisa Gentile, Daniel Gruhl, Petar Ristoski and Steve Welch Poster October 23, 2017, Poster and Demo Reception, 18:30-21:20 Festsaal 1 Download paper (preprint)

Abstract

Ontologies are dynamic artifacts that evolve both in struc- ture and content. Keeping them up-to-date is a very expensive and crit- ical operation for any application relying on semantic Web technologies. In this paper we focus on evolving the content of an ontology by extract- ing relevant instances of ontological concepts from text. The novelty of this work is that we propose a technique which is (i) completely language independent, (ii) combines statistical methods with human-in-the-loop and (iii) exploits Linked Data as bootstrapping source. Experiments on a publicly available parallel medical corpus show comparable performances regardless of the chosen language.