Roger Evans, Gerald Gazdar & Bill Keller
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 document shows that the language is nonetheless sufficiently expressive to represent concisely the structure of lexical information at a variety of levels of linguistic analysis. This document provides an informal example-based introduction to DATR; formal treatments of the semantics and theory of inference for the language; and an introduction to techniques for the use of the language, including finite state transduction, the encoding of DAGs and lexical rules, and the representation of ambiguity and alternation. Sample analyses of phenomena such as inflectional syncretism and verbal subcategorisation are given which show how the language can be used to squeeze out redundancy from lexical descriptions.