In order to reach comparable analyses cross-linguistically, UD often ends up in annotation that is similar to the common practice in semantic treebanks, such as linking content words to content words wherever possible.
preliminary experiments using our approach produced promising results on each of the tasks' respective English development sets, when treated as a single task: 67.1% labeled Smatch F 1 on AMR (adding a transition for implicit nodes and classifier for node labels), 79.1% labeled F 1 on DM, and 80.1% LAS F 1 on UD.