Part-whole relations in object-centered systems: an overview
Data & Knowledge Engineering - Special issue on modeling parts and wholes
Handbook of Logic and Language
Handbook of Logic and Language
Sweetening Ontologies with DOLCE
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Knowledge Representation and the Semantics of Natural Language (Cognitive Technologies)
Knowledge Representation and the Semantics of Natural Language (Cognitive Technologies)
Learning to recognize features of valid textual entailments
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A discourse commitment-based framework for recognizing textual entailment
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
Logical validation, answer merging and witness selection a study in multi-stream question answering
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Question answering using sentence parsing and semantic network matching
CLEF'04 Proceedings of the 5th conference on Cross-Language Evaluation Forum: multilingual Information Access for Text, Speech and Images
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Knowledge representation systems aiming at full natural language understanding need to cover a wide range of semantic phenomena including lexical ambiguities, coreference, modalities, counterfactuals, and generic sentences. In order to achieve this goal, we argue for a multidimensional view on the representation of natural language semantics. The proposed approach, which has been successfully applied to various NLP tasks including text retrieval and question answering, tries to keep the balance between expressiveness and manageability by introducing separate semantic layers for capturing dimensions such as facticity, degree of generalization, and determination of reference. Layer specifications are also used to express the distinction between categorical and situational knowledge and the encapsulation of knowledge needed e.g. for a proper modeling of propositional attitudes. The paper describes the role of these classificational means for natural language understanding, knowledge representation, and reasoning, and exemplifies their use in NLP applications.