Automatic Inference of DATR Theories
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.
Cite
@article{arxiv.cmp-lg/9601001,
title = {Automatic Inference of DATR Theories},
author = {Petra Barg},
journal= {arXiv preprint arXiv:cmp-lg/9601001},
year = {2008}
}
Comments
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