Derivational models are still an under- researched area in computational morphol- ogy. Even for German, a rather resource- rich language, there is a lack of large- coverage derivational knowledge. This pa- per describes a rule-based framework for inducing derivational families (i.e., clus- ters of lemmas in derivational relation- ships) 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 quan- titative 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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