Decomposing and Recomposing Event Structure

Author:

Gantt William1,Glass Lelia2,White Aaron Steven3

Affiliation:

1. University of Rochester, USA. wgantt@cs.rochester.edu

2. Georgia Institute of Technology, USA. lelia.glass@modlangs.gatech.edu

3. University of Rochester, USA. aaron.white@rochester.edu

Abstract

AbstractWe present an event structure classification empirically derived from inferential properties annotated on sentence- and document-level Universal Decompositional Semantics (UDS) graphs. We induce this classification jointly with semantic role, entity, and event-event relation classifications using a document-level generative model structured by these graphs. To support this induction, we augment existing annotations found in the UDS1.0 dataset, which covers the entirety of the English Web Treebank, with an array of inferential properties capturing fine-grained aspects of the temporal and aspectual structure of events. The resulting dataset (available at decomp.io) is the largest annotation of event structure and (partial) event coreference to date.

Publisher

MIT Press

Subject

Artificial Intelligence,Computer Science Applications,Linguistics and Language,Human-Computer Interaction,Communication

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