Instance-Based Ontology Population Exploiting Named-Entity Substitution

We present an approach to ontology population based on a lexical substitution technique. It consists in estimating the plausibility of sentences where the named entity to be classified is substituted with the ones contained in the training data, in our case, a partially populated ontology. Plausibility is estimated by using Web data, while the classification algorithm is instance-based. We evaluated our method on two different ontology population tasks. Experiments show that our solution is effective, outperforming existing methods, and it can be applied to practical ontology population problems.