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A general framework for information extraction using dynamic span graphs
2019
Proceedings of the 2019 Conference of the North
We introduce a general framework for several information extraction tasks that share span representations using dynamically constructed span graphs. The graphs are constructed by selecting the most confident entity spans and linking these nodes with confidenceweighted relation types and coreferences. The dynamic span graph allows coreference and relation type confidences to propagate through the graph to iteratively refine the span representations. This is unlike previous multitask frameworks
doi:10.18653/v1/n19-1308
dblp:conf/naacl/LuanWHSOH19
fatcat:fwvmu7ifz5d6fb36xcy5ho6igu