Note that both imp-greedy and logistic use the same amount of labeled data, though in different ways: logistic performs standard supervised classification; imp-greedy uses the labeled data to perform constraint selection for label regularization.
to summarize our answer to RQ2, we find that imp-greedy provides a robust method to select constraints in the presence of noise.