We investigate the problem of verbalizing Web Ontology Language (OWL) axioms of domain ontologies in this paper. The existing approaches address the problem of fidelity of verbalized OWL texts to OWL semantics by exploring different ways of expressing the same OWL axiom in various linguistic forms. They also perform grouping and aggregating of the natural language (NL) sentences that are generated corresponding to each OWL statement into a comprehensible structure. However, no efforts have been taken to try out a semantic reduction at logical level to remove redundancies and repetitions, so that the reduced set of axioms can be used for generating a more meaningful and human-understandable (what we call redundancy-free) text. Our experiments show that, formal semantic reduction at logical level is very helpful to generate redundancy-free descriptions of ontology entities. In this paper, we particularly focus on generating descriptions of individuals of SHIQ based ontologies. The details of a case study are provided to support the usefulness of the redundancy-free NL descriptions of individuals, in knowledge validation application.
To use these CNLs as a means for ontology authoring and for knowledge validation purposes, appropriate organization of the verbalized text is necessary. A detailed comparison of the systems that comprehend the NL texts is given in @cite_11 . Among such systems, SWAT tools @cite_9 are one of the recent and prominent tools which use standard techniques from computational linguistics to make the verbalized text more readable. They tried to give more clarity to the generated text by grouping, aggregation and elision. The Semantic Web Authoring (SWAT) tools have given much focus for comprehending the linguistic form of the sentences, rather than handling their logical forms, hence have deficiencies in their NL representations.
@cite_9 @cite_11
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It has frequently been observed that domain experts are not necessarily ontology experts, and that the production of ontologies would be aided if they could read and edit axioms in natural language. The SWAT Tools Verbaliser is available, via a web interface, for verbalising OWL ontologies as texts in a controlled fragment of English. Taking as input any OWL ontology, the verbaliser creates a lexicon containing entries for all the entities in the input, and uses it to generate an English sentence corresponding to each logical axiom. These sentences are then organised into a document structure similar to that of an encyclopaedia, with an entry providing a definition, typology and examples for each entity. The output is either organised, easily-navigable English text encoded in XML, or a copy of the input OWL in which each entity is annotated with its description entry. The generated texts have been evaluated in a number of ways which are briefly presented here. Background Text definitions for entities within bio-ontologies are a cornerstone of the effort to gain a consensus in understanding and usage of those ontologies. Writing these definitions is, however, a considerable effort and there is often a lag between specification of the main part of an ontology (logical descriptions and definitions of entities) and the development of the text-based definitions. The goal of natural language generation (NLG) from ontologies is to take the logical description of entities and generate fluent natural language. The application described here uses NLG to automatically provide text-based definitions from an ontology that has logical descriptions of its entities, so avoiding the bottleneck of authoring these definitions by hand.