Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Generating referring expressions: boolean extensions of the incremental algorithm
Computational Linguistics
Sentence Generation from Conceptual Graphs
ICCS '95 Proceedings of the Third International Conference on Conceptual Structures: Applications, Implementation and Theory
Graph-based generation of referring expressions
Computational Linguistics
Generating referring expressions involving relations
EACL '91 Proceedings of the fifth conference on European chapter of the Association for Computational Linguistics
Extensions of simple conceptual graphs: the complexity of rules and constraints
Journal of Artificial Intelligence Research
An Inferential Approach to the Generation of Referring Expressions
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications
Distinguishable entities: definition and properties
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
A situated context model for resolution and generation of referring expressions
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
Distinguishing Answers in Conceptual Graph Knowledge Bases
ICCS '09 Proceedings of the 17th International Conference on Conceptual Structures: Conceptual Structures: Leveraging Semantic Technologies
Situated resolution and generation of spatial referring expressions for robotic assistants
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Charting the potential of description logic for the generation of referring expressions
INLG '10 Proceedings of the 6th International Natural Language Generation Conference
Computational generation of referring expressions: A survey
Computational Linguistics
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This paper presents a Conceptual Graph (CG) framework to the Generation of Referring Expressions (GRE). Employing Conceptual Graphs as the underlying formalism allows a rigorous, semantically rich, approach to GRE. A number of advantages over existing work are discussed. The new framework is also used to revisit existing complexity results in a fully rigorous way, showing that the expressive power of CGs does not increase the theoretical complexity of GRE.