Multi-Sentence Argument Linking
Seth Ebner, Patrick Xia, Ryan Culkin, Kyle Rawlins, Benjamin Van Durme · 2020
We present a novel document-level model for finding argument spans that fill an event's roles, connecting related ideas in sentencelevel semantic role labeling and coreference resolution.Because existing datasets for cross-sentence linking are small, development of our neural model is supported through the creation of a new resource, Roles Across Multiple Sentences (RAMS), which contains 9,124 annotated events across 139 types.We demonstrate strong performance of our model on RAMS and other event-related datasets.1