This paper describes an automatic method for creating a domain-independent senseannotated corpus harvested from the web. As a proof of concept, this method has been applied to German, a language for which sense-annotated corpora are still in short supply. The sense inventory is taken from the German wordnet GermaNet. The web-harvesting relies on an existing mapping of GermaNet to the German version of the web-based dictionary Wiktionary. The data obtained by this method constitute WebCAGe (short for: Web-Harvested Corpus Annotated with GermaNet Senses), a resource which currently represents the largest sense-annotated corpus available for German. .
