For example, our model corrects [S-PER Charles] [S-PER Picqué] to [B-PER Charles] [E-PER Picqué] because the CRFs layer fully trained on other languages assigns a low score to the rare transition S-PER→S-PER and promotes B-PER→E-PER.
with a large number of parameters, it cannot be fully trained only using the low-resource task data.