State of the art Word Sense Disambiguation (WSD) systems require large sense-tagged corpora along with lexical databases toreach satisfactory results. The number of English language resources for developed WSD increased in the past years, while mostother languages are still under-resourced. The situation is no different for Dutch. In order to overcome this data bottleneck, the DutchSemCor project will deliver a Dutch corpus that is sense-tagged with senses from the Cornetto lexical database. Part of this corpus (circa 300K examples) is manually tagged. The remainder is automatically tagged using different WSD systems and validated by human annotators. The project uses existing corpora compiled in other projects; these are extended with Internetexamples f or word senses that are less frequent and do not (sufficiently) appear in the corpora. We report on the status of theproject and the evaluations of the WSD systems with the current training data.