Comparing MERGED with MTL-all we see that the performance difference is mainly due to MTL-all introducing fewer new classification errors over the STL baseline.
: both metaphor tasks, where training (and evaluation) data for a particular token or construction is sparse, profit heavily from inclusion of the idiom datasets.