A huge amount of datasets on the Semantic Web are linked to a few datahubs, the most prominent of which is DBpedia. What makes the exploitation of DBpedia challenging for natural language-based ap- plications, however, is that such NLP applications require knowledge about how the ontology elements are verbalized in natural language. In order to provide such knowledge at the required scale and thereby lever- age the use of DBpedia in different applications, we construct a lexicon for the DBpedia 2014 ontology by means of existing automatic methods for lexicon induction. It contains 11,998 lexical entries for 574 different properties in three languages: English, German, and Spanish. Just like DBpedia provides a hub for Semantic Web datasets, this lexicon can pro- vide a hub for the lexical Semantic Web, an ecosystem in which ontology lexica are published, linked, and re-used across applications.