Swoogle: a search and metadata engine for the semantic web
Proceedings of the thirteenth ACM international conference on Information and knowledge management
In situ migration of handcrafted ontologies to reason-able forms
Data & Knowledge Engineering
Complexity assumptions in ontology verbalisation
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Grouping axioms for more coherent ontology descriptions
INLG '10 Proceedings of the 6th International Natural Language Generation Conference
Expressing OWL axioms by English sentences: dubious in theory, feasible in practice
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Enriching the gene ontology via the dissection of labels using the ontology pre-processor language
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
Levels of organisation in ontology verbalisation
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Extraction and analysis of the structure of labels in biomedical ontologies
Proceedings of the 2nd international workshop on Managing interoperability and compleXity in health systems
Generating natural language descriptions from OWL ontologies: the natural OWL system
Journal of Artificial Intelligence Research
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Despite their flat, semantics-free structure, ontology identifiers are often given names or labels corresponding to natural language words or phrases which are very dense with information as to their intended referents. We argue that by taking advantage of this information density, NLG systems applied to ontologies can guide the choice and construction of sentences to express useful ontological information, solely through the verbalisations of identifier names, and that by doing so, they can replace the extremely fussy and repetitive texts produced by ontology verbalisers with shorter and simpler texts which are clearer and easier for human readers to understand. We specify which axioms in an ontology are "defining axioms" for linguistically-complex identifiers and analyse a large corpus of OWL ontologies to identify common patterns among all defining axioms. By generating texts from ontologies, and selectively including or omitting these defining axioms, we show by surveys that human readers are typically capable of inferring information implicitly encoded in identifier phrases, and that texts which do not make such "obvious" information explicit are preferred by readers and yet communicate the same information as the longer texts in which such information is spelled out explicitly.