Count-based metrics can deduce from the similar translations of two phrases that they have similar meanings, despite dissimilarity between the two word sequencese.g., they can deduce that "red" and "burgundy" belong in the same cluster.
these metrics are unreliable when total counts are low, since phrase co-occurrences are determined by a noisy alignment process.