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We describe a statistical approach to s role labelling that employs only shallo mation. We use a Maximum Entropy learne augmented by EM-based clustering to mod the fit between a verb and its argument didate. The instances to be classified quences of chunks that occur frequently guments in the training corpus. Our bes obtains an F score of 51.70 on the test set.