Motivated by nonparametric posterior inference in a Bayesian problem where two independent unlabelled samples are available, we study the problem of sampling exactly in the set of coagulated partitions. These are obtained by matching a random number of cluster pairs chosen across the samples, and listing the remaining clusters unmatched. We propose an exact method for sampling from the correct target distribution, and present empirical evidence in comparison with the exact distribution.