The SUMTIME system builders believe deviating from corpus frequency in such cases makes SUMTIME texts better from the reader's perspective, and it does appear to increase human ratings of the system; but deviating from the corpus in such a way decreases the system's score under corpus-similarity metrics.
judging the output of an NLG system by comparing it to corpus texts by a method that rewards corpus similarity will penalise systems which do not base choice on highest frequency of occurrence in the corpus, even if this is motivated by careful studies of what is best for text readers.