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.
Over the last decade, several CNLs such as Attempto Controlled English (ACE) @cite_1 @cite_13 , Ordnance Survey's Rabbit (Rabbit) @cite_5 , and Sydney OWL Syntax (SOS) @cite_10 , have been specifically designed for ontology language OWL. All these languages are meant to make the interactions with formal ontological statements easier and faster for users who are unfamiliar with formal notations. Unlike the other languages @cite_0 @cite_12 @cite_8 that have been suggested to represent OWL in controlled English, these CNLs are designed to have formal language semantics and bidirectional mapping between NL fragments and OWL constructs. Even though these formal language semantics and bidirectional mapping are helpful in enabling a formal check that the resulting NL expressions are unambiguous, they generate a collection of unordered sentences that are difficult to comprehend.
@cite_8 @cite_10 @cite_1 @cite_0 @cite_5 @cite_13 @cite_12
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We present Naturalowl, a natural language generation system that produces texts describing individuals or classes of owl ontologies. Unlike simpler owl verbalizers, which typically express a single axiom at a time in controlled, often not entirely fluent natural language primarily for the benefit of domain experts, we aim to generate fluent and coherent multi-sentence texts for end-users. With a system like Naturalowl, one can publish information in owl on the Web, along with automatically produced corresponding texts in multiple languages, making the information accessible not only to computer programs and domain experts, but also end-users. We discuss the processing stages of Naturalowl, the optional domain-dependent linguistic resources that the system can use at each stage, and why they are useful. We also present trials showing that when the domain-dependent linguistic resources are available, Naturalowl produces significantly better texts compared to a simpler verbalizer, and that the resources can be created with relatively light effort. This paper describes a proposed new syntax that can be used to write and read OWL ontologies in Controlled Natural Language (CNL): a well-defined subset of the English language. Following the lead of Manchester OWL Syntax in making OWL more accessible for non-logicians, and building on the previous success of Schwitter’s PENG (Processable English), the proposed Sydney OWL Syntax enables two-way translation and generation of grammatically correct full English sentences to and from OWL 1.1 functional syntax. Used in conjunction with OWL tools, it is designed to facilitate ontology construction and editing by enabling authors to write an OWL ontology in a defined subset of English. It also improves readability and understanding of OWL statements or whole ontologies, by enabling them to be read as English sentences. It is hoped that by providing the option of an intuitive, easy to use English syntax which requires no specialized knowledge, the broader community will be far more likely to develop and benefit from Semantic Web applications. This paper is a discussion paper covering the scope, design, and examples of Sydney OWL Syntax in use, and the authors invite feedback on all aspects of the proposal via email to krr.sydneysyntax@cse.unsw.edu.au. Working drafts of the full specification are available at http: www.ics.mq.edu.au rolfs sos. We describe a verbalization of the logical content of OWL ontologies — using OWL 1.1 without data-valued properties — in Attempto Controlled English (ACE). Because ACE is a subset of English, the verbalization makes OWL ontologies accessible to people with no training in formal methods. We conclude that OWL can be verbalized in concise and understandable English provided that a certain naming style is adopted for OWL individuals, classes, and properties. A demand defrost system in which a high resistive epoxy resin hermetically seals a capacitive sensor plate and a noise immune phase detector detects a phase shift caused by the build up of frost. Verbalization is the process of writing the semantics captured in axioms into natural language sentences, which enables domain experts (who are not trained to understand technical formal languages) to be able to participate in the modeling and validation processes of their domain knowledge. We present a novel approach to support multilingual verbalization of logical theories, axiomatizations, and other specifications such as business rules. This engineering solution is demonstrated with the Object Role Modeling language and the ontology engineering tool DogmaModeler, although its underlying principles can be reused with other conceptual models and formal languages, such as Description Logics, to improve its understandability and usability by the domain expert. Our engineering solution for multilingual verbalization is characterized by its flexibility, extensibility and maintainability of the verbalization templates, which allow for easy augmentation with other languages than the 10 currently supported.