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In this paper we present a novel approach to semi-automatically learn concept hierarchies from natural language requirements of the automotive industry. The approach is based on the distributional hypothesis and the special characteristics of domain-specific German compounds. We extract taxonomies by using clustering techniques in combination with general thesauri. Such a taxonomy can be used to support requirements engineering in early stages by providing a common system understanding and an agreedupon terminology. This work is part of an ontology-driven requirements engineering process, which builds on top of the taxonomy. Evaluation shows that this taxonomy extraction approach outperforms common hierarchical clustering techniques.