Joint models of syntactic and semantic parsing have the potential to improve performance on both tasks-but to date, the best results have been achieved with pipelines. We introduce a joint model using CCG, which is motivated by the close link between CCG syntax and semantics. Semantic roles are recovered by labelling the deep dependency structures produced by the grammar. Furthermore, because CCG is lexicalized, we show it is possible to factor the parsing model over words and introduce a new A * parsing algorithmwhich we demonstrate is faster and more accurate than adaptive supertagging. Our joint model is the first to substantially improve both syntactic and semantic accuracy over a comparable pipeline, and also achieves state-of-the-art results for a nonensemble semantic role labelling model.
REF present a joint model of CCG parsing and semantic role labeling (SRL), which is closely related to our approach.
Joint A* CCG Parsing and Semantic Role Labelling
EMNLP
Computer Science