Acquisition of OWL DL Axioms from Lexical Resources

Abstract

Abstract. State-of-the-art research on automated learning of ontologies from text currently focuses on inexpressive ontologies. The acquisition of complex axioms involving logical connectives, role restrictions, and other expressive features of the Web Ontology Language OWL remains largely unexplored. In this paper, we present a method and implementation for enriching inexpressive OWL ontologies with expressive axioms which is based on a deep syntactic analysis of natural language definitions. We argue that it can serve as a core for a semi-automatic ontology engineering process supported by a methodology that integrates methods for both ontology learning and evaluation. The feasibility of our approach is demonstrated by generating complex class descriptions from Wikipedia definitions and from a fishery glossary provided by the Food and Agriculture Organization of the United Nations.

PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation Using Probabilistic Methods

“…theory NELL [3] 24 × 7 learning fixed dynamic ML techniques DART [7] world knowledge × × semi-automated RTE [2], and [13] entailment × × ATP NLU [20] commonsense rules × × semi-supervised Text2Onto [6] ontology learning √ √ semi-supervised LexO [24] complex classes √ × semi-supervised FCA [5] taxonomy √ × FCA OP [4], and [23] ontology population available available semi-/supervised a corpus many be large, it might not contain all the necessary evidence of an event of interest. A corpus contains ambiguous statements about an event that leads to a non-determinism of the state of the event.…”

Class expression learning for ontology engineering

“…Naturally, there is also a large amount of research work on ontology learning from text. The most closely related approach in this area is [31], in which OWL DL axioms are obtained by analysing sentences, which have definitional character.…”

ORE - A Tool for Repairing and Enriching Knowledge Bases

“…Naturally, there is also a lot of research work on ontology learning from text. The most closely related approach in this area is [31], in which OWL DL axioms are obtained by analysing sentences which have definitorial character.…”