Graph Convolutions over Constituent Trees forSyntax-Aware Semantic Role Labeling
Table 3: Precision, recall and F1 on the CoNLL-2012 test set. † indicates syntactic models and ‡ indicates multi-task learning models.
['Single', 'Test  [ITALIC] P', 'Test  [ITALIC] R', 'Test  [ITALIC] F1']
SpanGCN obtains 84.4 F1, outperforming all previous models evaluated on this data. We report results with contextualized embeddings on CoNLL-2012 in Table Emb.). SpanGCN obtains state-of-the-art results. It is interesting to notice though, that results of the syntax-aware model of Wang et al.