The main weakness of CM is that a large proportion of contexts does not contain sufficient information to infer all types of the entity; e.g., based on our distant supervised training data, we label every context of "Obama" with "author", "politician" and Obama's other types in the KB.
cM is trained on a noisy training set that contains only a relatively small number of informative contexts.