Abstract
Current approaches to computational lexicology in language technology are knowledge-based (competence-oriented) and try to abstract away from specific formalisms, domains, and applications. This results in severe complexity, acquisition and reusability bottlenecks. As an alternative, we propose a particular performance-oriented approach to Natural Language Processing based on automatic memory-based learning of linguistic (lexical) tasks. The consequences of the approach for computational lexicology are discussed, and the application of the approach on a number of lexical acquisition and disambiguation tasks in phonology, morphology and syntax is described.
I would like to thank my colleagues in the Atila project (Steven Gillis, Gert Durieux, and Antal van den Bosch) for their contributions to the approach described in this paper. The Atila (Antwerp-Tilburg Inductive Language Acquisition) project is a research corporation between the University of Antwerp and Tilburg University focusing on the application of Machine Learning techniques in linguistic engineering and in developmental psycholinguistics. Thanks also to the participants of the Heidelberg workshop on Machine Translation and the Lexicon for useful comments and suggestions.
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Daelemans, W. (1995). Memory-based lexical acquisition and processing. In: Steffens, P. (eds) Machine Translation and the Lexicon. WMTL 1993. Lecture Notes in Computer Science, vol 898. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59040-4_22
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DOI: https://doi.org/10.1007/3-540-59040-4_22
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