AI Magazine
Handbook of formal languages, vol. 3
Towards a standard upper ontology
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Talking about Trees and Truth-Conditions
Journal of Logic, Language and Information
Handbook on Ontologies (International Handbooks on Information Systems)
Handbook on Ontologies (International Handbooks on Information Systems)
An ontology of time for the semantic web
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on Temporal Information Processing
The Description Logic Handbook
The Description Logic Handbook
Proceedings of the 12th international conference on Intelligent user interfaces
Towards portable natural language interfaces to knowledge bases - The case of the ORAKEL system
Data & Knowledge Engineering
A linguistic ontology of space for natural language processing
Artificial Intelligence
Natural language interfaces: what is the problem? – a data-driven quantitative analysis
NLDB'09 Proceedings of the 14th international conference on Applications of Natural Language to Information Systems
Applied Ontology - Is there Beauty in Ontologies?
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In line with Nirenburg and Raskin's paradigm of ontological semantics, we adhere to the basic tenet that natural language semantics needs to be captured with respect to an explicitly formalized ontology. Many researchers in computational semantics, however, have neglected the ontological aspects of meaning representation, and even more have neglected aspects of meaning representation related to domain-independent ontologies, i.e. foundational or upper-level ontologies. In this paper we argue for a stronger integration of foundational ontologies in computational semantics. We show that relying on foundational ontologies can, on the one hand, lead to a clean separation between domain-specific and domain-independent components of natural language processing systems. On the other hand, we show how the interplay between foundational, domain ontologies and lexical semantics resources can elegantly account for disambiguation as well as allow to draw non-trivial inferences. Further, a temporal theory compliant with the foundational ontology is absolutely necessary for supporting temporal reasoning in natural language understanding.