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DATR: a language for lexical knowledge representation

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Gerald GazdarAuthors Info & Claims

Computational Linguistics, Volume 22, Issue 2

Pages 167 - 216

Published: 01 June 1996 Publication History

Abstract

Much recent research on the design of natural language lexicons has made use of nonmonotonic inheritance networks as originally developed for general knowledge representation purposes in Artificial Intelligence. DATR is a simple, spartan language for defining nonmonotonic inheritance networks with path/value equations, one that has been designed specifically for lexical knowledge representation. In keeping with its intendedly minimalist character, it lacks many of the constructs embodied either in general-purpose knowledge representation languages or in contemporary grammar formalisms. The present paper shows that the language is nonetheless sufficiently expressive to represent concisely the structure of lexical information at a variety of levels of linguistic analysis. The paper provides an informal example-based introduction to DATR and to techniques for its use, including finite-state transduction, the encoding of DAGs and lexical rules, and the representation of ambiguity and alternation. Sample analysis of phenomena such as inflectional syncretism and verbal subcategorization are given that show how the language can be used to squeeze out redundancy from lexical descriptions.

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cover image Computational Linguistics

Computational Linguistics Volume 22, Issue 2

June 1996

131 pages

ISSN:0891-2017

EISSN:1530-9312

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MIT Press

Cambridge, MA, United States

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Published: 01 June 1996

Published in COLI Volume 22, Issue 2

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https://dl.acm.org/doi/10.1007/978-3-662-53826-5_16
Cahill L(2012)A rule-based approach to unknown word recognition in ArabicProceedings of the Twelfth Meeting of the Special Interest Group on Computational Morphology and Phonology10.5555/2390930.2390935(35-41)Online publication date: 7-Jun-2012
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