DErivBase: Inducing and Evaluating a Derivational Morphology Resource for German

Britta Zeller, Jan Snajder and Sebastian Pado

The 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013)
Sofia, Bulgaria, August 4-9, 2013

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Abstract

Derivational models are still an under-researched area in computational morphology. Even for German, a rather resource-rich language, there is a lack of large-coverage derivational knowledge. This paper describes a rule-based framework for inducing derivational families (i.e., clusters of lemmas in derivational relationships) and its application to create a high-coverage German resource, DErivBase, mapping over 280k lemmas into more than 17k non-singleton clusters. We focus on the rule component and a qualitative and quantitative evaluation. Our approach achieves up to 93% precision and 71% recall. We attribute the high precision to the fact that our rules are based on information from grammar books.

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