Automatic Inference of DATR Theories

1996/01/04 by Petra Barg, Barg, Petra
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #cmp-lg #cs.CL

paper · pdf · doi:10.48550/arxiv.cmp-lg/9601001

Latex 10 pages, 1 Postscript figure. To appear in H.-H. Bock, W. Polasek (eds.) Data Analysis and Information Systems: Statistical and conceptual approaches (Proceedings of the 19th Annual Conference of the Gesellschaft fuer Klassifikation e.V., University of Basel), Springer Verlag, pp. 506-515

Abstract

This paper presents an approach for the automatic acquisition of linguistic knowledge from unstructured data. The acquired knowledge is represented in the lexical knowledge representation language DATR. A set of transformation rules that establish inheritance relationships and a default-inference algorithm make up the basis components of the system. Since the overall approach is not restricted to a special domain, the heuristic inference strategy uses criteria to evaluate the quality of a DATR theory, where different domains may require different criteria. The system is applied to the linguistic learning task of German noun inflection.

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