Ontology Verbalization using Semantic-Refinement

Tracking #: 2048-3261

This paper is currently under review
Vinu E. V
P Sreenivasa Kumar

Responsible editor: 
Philipp Cimiano

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This paper presents an inference-based verbalization approach for OWL axioms that aims at removing redundancy to provide more helpful and more concise sentences to show formal facts to users. We focus on verbalization of OWL axioms about individual and (atomic) concepts as it is relevant in the context of validating the correctness of the formalized domain knowledge by domain experts. The approaches that are currently adopted in the existing verbalization tools generally consider all axioms that are associated with the individual (or the concept) under consideration and then translate them to corresponding natural language texts. Further refinement (mainly, grouping and aggregation) of these texts would be done at the natural language level to yield a more fluent and comprehensive form. However, we observed that human-understandability of such descriptions is affected by the presence of repetitions and redundancies which can be removed easily at the semantic level. We propose a novel technique called semantic-refinement which fulfills this requirement. This technique utilizes a predefined set of rules that are repeatedly applied over the restrictions that are associated with an individual (or a concept) in a meaning-preserving manner to get a refined set of restriction that can be verbalized to get a concise description. Our experiments on two ontologies show that semantic-refinement technique could significantly improve the readability of the natural language descriptions on comparing to those descriptions that are generated without employing the semantic-refinement. We have also tested the effectiveness and usefulness of the the generated descriptions in validating the correctness of ontologies and found that the proposed technique is indeed helpful in that context.
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