Property type distribution in Wordnet, corpora and Wikipedia

The ontology learning from text lacks an initial evaluation of the property types present in the resource used in the learning task. We need a way to explore the distribution of property types before the actual ontology learning process. In this paper we propose three algorithms that help ontologists in the preliminary resource exploration. The algorithms are devised for Wordnet, generic corpora and Wikipedia. Minimal assumptions about the property types that can be extracted are made. The algorithms are tested with concepts belonging to five taxonomies. The distribution of property types for the extracted concepts is computed and reported.