As for POS-mismatches, we do note that the work of <cite>Noraset et al. (2017)</cite> had a much lower rate of 4.29%: we suggest that this may be due to the fact that they employ a learned character-level convolutional network, which arguably would be able to capture orthography and rudiments of morphology.