Interactive Learning: an Approach for Building DL Ontologies from Natural Language and Reasoning

In this paper, we present an approach based on Reasoning and Natural Language Processing for Ontology Learning, specifically over Description Logic (DL) knowledge bases constituted by a TBox with ALC expressivity, from interactions with users in controled natural language text. The viability of our approach is demonstrated through the generation of descriptions of complex axioms from concepts defined by users. We evaluated our approach in an experiment with entry interactions enriched with hierarchy axioms, disjunction, conjunction, negation, as well as existential and universal quantification to impose restriction of properties. The obtained results prove that our model is an effective solution for reasoning, knowledge representation and automatic construction of expressive Ontologies. Thereby, it assists professionals involved in processes for obtain, construct and model knowledge domain.