Extracting ontology concept hierarchies from text using Markov logic
Lucas Drumond, Rosario Girardi · 2010
Ontologies have proven to be a powerful tool for many tasks such as natural language processing and information filtering and retrieval. However their development is an error prone and expensive task. One approach for this problem is to provide automatic or semi-automatic support for ontology construction. This work presents the Probabilistic Relational Hierarchy Extraction (PREHE) technique, an approach for extracting concept hierarchies from text that uses statistical relational learning and natural language processing for combining cues from many state-of-the-art techniques. A Markov Logic Network has been developed for this task and is described here. A preliminary evaluation of the proposed approach is also outlined.