Planning English Sentences
Graph-based generation of referring expressions
Computational Linguistics
Intrinsic vs. extrinsic evaluation measures for referring expression generation
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
The TUNA-REG Challenge 2009: overview and evaluation results
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
A conceptual graph approach to the generation of referring expressions
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Effective query rewriting with ontologies over DBoxes
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Referring expressions as formulas of description logic
INLG '08 Proceedings of the Fifth International Natural Language Generation Conference
Computational generation of referring expressions: A survey
Computational Linguistics
Generating natural language descriptions from OWL ontologies: the natural OWL system
Journal of Artificial Intelligence Research
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The generation of referring expressions (GRE), an important subtask of Natural Language Generation (NLG) is to generate phrases that uniquely identify domain entities. Until recently, many GRE algorithms were developed using only simple formalisms, which were taylor made for the task. Following the fast development of ontology-based systems, reinterpreta-tions of GRE in terms of description logic (DL) have recently started to be studied. However, the expressive power of these DL-based algorithms is still limited, not exceeding that of older GRE approaches. In this paper, we propose a DL-based approach to GRE that exploits the full power of OWL2. Unlike existing approaches, the potential of reasoning in GRE is explored.