  We introduce a transductive model for parsing into Universal Decompositional
Semantics (UDS) representations, which jointly learns to map natural language
utterances into UDS graph structures and annotate the graph with
decompositional semantic attribute scores. We also introduce a strong pipeline
model for parsing into the UDS graph structure, and show that our transductive
parser performs comparably while additionally performing attribute prediction.
By analyzing the attribute prediction errors, we find the model captures
natural relationships between attribute groups.
