  Semantic proto-role labeling (SPRL) is an alternative to semantic role
labeling (SRL) that moves beyond a categorical definition of roles, following
Dowty's feature-based view of proto-roles. This theory determines agenthood vs.
patienthood based on a participant's instantiation of more or less typical
agent vs. patient properties, such as, for example, volition in an event. To
perform SPRL, we develop an ensemble of hierarchical models with self-attention
and concurrently learned predicate-argument-markers. Our method is competitive
with the state-of-the art, overall outperforming previous work in two
formulations of the task (multi-label and multi-variate Likert scale
prediction). In contrast to previous work, our results do not depend on gold
argument heads derived from supplementary gold tree banks.
