In this paper we express the external syntactic information as vectors of discrete features, because this enables us to explore different ways of injecting the syntactic information into the neural SRL model.
we propose three different syntax encoding methods: a) a full constituency tree representation (Full-C); b) an SRLspecific span representation (SRL-C); and c) a dependency tree representation (Dep).