We describe the development of a Dutch memory-based shallow parser. The availability of large treebanks for Dutch, such as the one provided by the Spoken Dutch Corpus, allows memory-based learners to be trained on examples of shallow parsing taken from the treebank, and act as a shallow parser after training. An overview is given of a modular memory-based learning approach to shallow parsing, composed of a part-of-speech tagger– chunker and two grammatical relation finders, which has originally been developed for English. This approach is applied to the syntactically annotated part of the Spoken Dutch Corpus to construct a Dutch shallow parser. From the generalisation scores of the parser we conclude that existing memory-based parsing approaches can be applied to spoken Dutch successfully, but that there is room for improvement in the tagger–chunker.