For example, Fares (2016) reports that the temporal and locative relations in NomBank (ARGM-TMP and ARGM-LOC, respectively) and their counterparts in PCEDT (TWHEN and LOC) exhibit a relatively consistent behavior across frameworks as they annotate many of the same compounds.
in MTL, we train one model simultaneously to learn both PCEDT and NomBank relations, and therefore all the MTL models have two objective functions and two output layers.