%0 Conference Proceedings %T Compositional Semantic Parsing across Graphbanks %A Lindemann, Matthias %A Groschwitz, Jonas %A Koller, Alexander %Y Korhonen, Anna %Y Traum, David %Y Màrquez, Lluís %S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics %D 2019 %8 July %I Association for Computational Linguistics %C Florence, Italy %F lindemann-etal-2019-compositional %X Most semantic parsers that map sentences to graph-based meaning representations are hand-designed for specific graphbanks. We present a compositional neural semantic parser which achieves, for the first time, competitive accuracies across a diverse range of graphbanks. Incorporating BERT embeddings and multi-task learning improves the accuracy further, setting new states of the art on DM, PAS, PSD, AMR 2015 and EDS. %R 10.18653/v1/P19-1450 %U https://aclanthology.org/P19-1450 %U https://doi.org/10.18653/v1/P19-1450 %P 4576-4585