We find the dis-  tributions over the frequencies of particular errors follow a Zipfian skew across both S&B datasets, with the Arabic being more pronounced (the most frequent error being made 27 times, with 627 errors being made just once) in comparison with the Hebrew (with the most frequent error being made 19 times, and with 856 isolated errors).
in both the Arabic and Hebrew S&B tasks we find that a tendency to over-segment certain characters off of their correct morphemes and on to other frequently occurring, yet incorrect, particles is actually the cause of many of these isolated errors.