Since the batches are ordered according to perplexity-based similarity with respect to the target domain the algorithm makes it increasingly harder for a batch to get into the final selection as (i) later batches are less similar to the targeted domain and (ii) they need to improve on a steadily improving baseline.
the algorithm implements the intuition that only those parts of generic supplementary data are selected which are good enough to generate better translation quality on the devset.