Finally we average to get chrP and chrR, and compute the F-score: chrP = (17/17 + 13/16)/2 = .906 chrR = (17/18 + 13/17)/2 = .855 chrF2,2 = 5 chrP * chrR 4chrP + chrR = .86 chrF is simple, robust, and correlates very well with human judgments in many languages (Kocmi et al., 2021) . There are various alternative overlap metrics. For example, before the development of chrF, it was common to use a word-based overlap metric called BLEU (for BiLingual Evaluation Understudy), that is purely precision-based rather than combining precision and recall (Papineni et al., 2002) . The BLEU score for a corpus of candidate translation sentences is a function of the n-gram word precision over all the sentences combined with a brevity penalty computed over the corpus as a whole. Because BLEU is a word-based metric, it is very sensitive to word tokenization, making it difficult to compare across situations, and doesn't work as well in languages with complex morphology.