Title: "Information Extraction for Ontology Population and Relation Learning"
Authors: (probably) Diana Maynard, Yaoyong Li, Ting Wang, Kalina Bontcheva

Abstract:

This chapter investigates NLP techniques for ontology population and relation learning, using a combination of rule-based approaches and machine learning. We describe some previous work on term and relation extraction using linguistic and statistical techniques, making use of contextual information to bootstrap learning. This work is  extended to incorporate machine learning approaches which take the rule-based approach a stage further and deal with more general kinds of language than the more restricted term-based approach. We evaluate our ontology-based information extraction results using a novel technique we have developed which makes use of similarity-based metrics first developed for term extraction.