Automatic Inference of DATR Theories

dc.creatorBarg, Petra
dc.date1996-01-04
dc.date.accessioned2026-07-07T09:10:05Z
dc.date.available2026-07-07T09:10:05Z
dc.descriptionThis 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.
dc.descriptionLatex 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
dc.identifierhttps://arxiv.org/abs/cmp-lg/9601001
dc.identifierhttp://arxiv.org/abs/cmp-lg/9601001
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/151255
dc.subjectComputation and Language
dc.titleAutomatic Inference of DATR Theories
dc.typetext

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