Relation Extraction from Texts with Symbolic Rules Induced by Inductive Logic Programming

Relation Extraction (RE) is the task of detecting semantic relations between entities in text. Most of the state-of-the-art RE systems rely on statistical machine learning techniques which usually employ an attribute-value representation of features. Contrarily to this trend, we focus on an alternative approach to RE based on the automatic induction of symbolic extraction rules. We present OntoILPER, an RE system based on Inductive Logic Programming which uses a domain ontology in its extraction process. Several experiments are discussed in this paper over the reACE 2004/2005 reference corpora. The results are encouraging and seem to demonstrate the effective-ness of the proposed solution.