Syntax-driven and ontology-driven lexical semantics.- Knowledge management for terminology-intensive applications: Needs and tools.- Logical structures in the lexicon.- Conventional metaphor and the lexicon.- Representation of semantic knowledge with term subsumption languages.- Predictable meaning shift: Some linguistic properties of Lexical Implication Rules.- Lexical operations in a unification-based framework.- Lexical structures for linguistic inference.- In so many words: Knowledge as a lexical phenomenon.- Redefining the “level” of the “word”.- Lexical and world knowledge: Theoretical and applied viewpoints.- Aspectual requirements of temporal connectives: Evidence for a two-level approach to semantics.- A model for the interaction of lexical and non-lexical knowledge in the determination of word meaning.- For the lexicon that has everything.- Acquiring and representing semantic information in a lexical knowledge base.- General lexical representation for an effect predicate.- The autonomy of shallow lexical knowledge.- A two-level knowledge representation for machine translation: Lexical semantics and tense/aspect.- Lexicon, ontology, and text meaning.- Development of the concept dictionary — Implementation of lexical knowledge.- Presuppositions and default reasoning: A study in lexical pragmatics.
Lexical Semantics and Knowledge Representation: First SIGLEX Workshop, Berkeley, CA, USA, June 17, 1991. Proceedings / Edition 1by James Pustejovsky
Pub. Date: 10/08/1992
Publisher: Springer Berlin Heidelberg
Recent work on formal methods in computational lexical semantics has had theeffect of bringing many linguistic formalisms much closer to the knowledge representation languages used in artificial intelligence. Formalisms are now emerging which may be more expressive and formally better understood than many knowledge representation languages. The interests of
Recent work on formal methods in computational lexical semantics has had theeffect of bringing many linguistic formalisms much closer to the knowledge representation languages used in artificial intelligence. Formalisms are now emerging which may be more expressive and formally better understood than many knowledge representation languages. The interests of computational linguists now extend to include such domains as commonsense knowledge,
inheritance, default reasoning, collocational relations, and even domain knowledge. With such an extension of the normal purview of "linguistic" knowledge, one may question whether there is any logical justification for distinguishing between lexical semantics and commonsense reasoning.
This volume explores the question from several methodologicaland theoretical perspectives. What emerges is a clear consensus that the notion of the lexicon and lexical knowledge assumed in earlier linguistic research is grossly inadequate and fails to address the deeper semantic issues required for natural language analysis.
- Springer Berlin Heidelberg
- Publication date:
- Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence Series , #627
- Edition description:
- Product dimensions:
- 0.82(w) x 6.14(h) x 9.21(d)
Table of Contents
Most Helpful Customer Reviews
See all customer reviews