Many tasks in which a system needs to mediate between natural language expressions and elements of a vocabulary in an ontology or dataset require knowledge about how the elements of the vocabulary (i.e. classes, properties, and individuals) are expressed in natural language. In a multilingual setting, such knowledge is needed for each of the supported languages. In this paper we present M-ATOLL, a framework for automatically inducing ontology lexica in multiple languages on the basis of a multilingual corpus. The framework exploits a set of language-specific dependency patterns which are formalized as SPARQL queries and run over a parsed corpus. We have instantiated the system for two languages: German and English. We evaluate it in terms of precision, recall and F-measure for English and German by comparing an automatically induced lexicon to manually constructed ontology lexica for DBpedia. In particular, we investigate the contribution of each single dependency pattern and perform an analysis of the impact of different parameters.