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Compositional Semantic Parsing Across Graphbanks

2019-09-18 | |  101 |   45 |   0 0 0
Abstract Most semantic parsers that map sentences to graph-based meaning representations are handdesigned 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.

上一篇：Automatic Generation of High Quality CCGbanksfor Parser Domain Adaptation

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