ALLiS: a symbolic learning system for Natural Language Learning

Authors:
Hervé Déjean
Affiliations:
Universität Tübingen
Venue:
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Year:
2000

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Abstract

We present ALLiS, a learning system for identifying syntactic structures which uses theory refinement. When other learning techniques (symbolic or statistical) are widely used in Natural Language Learning, few applications use theory refinement (Abecker and Schmid, 1996), (Mooney, 1993). We would like to show that even a basic implementation of notions used in TR is enough to build an efficient machine learning system concerning the task of learning linguistic structures.