This collection describes techniques of lexical representation within a unification-based framework.
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'A very valuable description ... should be available in all centres of artificial intelligence.' Artificial Intelligence Review
The lexicon is now a major focus of research in computational linguistics and natural language processing (NLP), as more linguistic theories concentrate on the lexicon and as the acquisition of an adequate vocabulary has become the chief bottleneck in developing practical NLP systems. This collection describes techniques of lexical representation within a unification-based framework and their linguistic application, concentrating on the issue of structuring the lexicon using inheritance and defaults. Topics covered include typed feature structures, default unification, lexical rules, multiple inheritance and non-monotonic reasoning. The contributions describe both theoretical results and implemented languages and systems, including DATR, the Stuttgart TFS and ISSCO's ELU. This book arose out of a workshop on default inheritance in the lexicon organized as a part of the Esprit ACQUILEX project on computational lexicography. Besides the contributed papers mentioned above, it contains a detailed description of the ACQUILEX lexical knowledge base (LKB) system and its use in the representation of lexicons extracted semi-automatically from machine-readable dictionaries.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Inheritance has been used in AI knowledge representation for many years. Until recently, however, it had not been much exploited in linguistic representation. This collection describes how the lexicon may be structured using inheritance. The papers are mostly formal in orientation, mainly concentrating on unification-based systems (which nowadays form the basis for most theoretically motivated work on NLP, and for current linguistic theories such as HPSG) and discuss syntax and morphology as well as lexical semantics. The formalization of default inheritance, in particular, is discussed in detail, and linked with the AI literature. Artikel-Nr. 9780521028059
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