Paper: Extracting Narrative Timelines as Temporal Dependency Structures

ACL ID P12-1010
Title Extracting Narrative Timelines as Temporal Dependency Structures
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2012

We propose a new approach to characterizing the timeline of a text: temporal dependency structures, where all the events of a narrative are linked via partial ordering relations like BE- FORE, AFTER, OVERLAP and IDENTITY. We annotate a corpus of children?s stories with tem- poral dependency trees, achieving agreement (Krippendorff?s Alpha) of 0.856 on the event words, 0.822 on the links between events, and of 0.700 on the ordering relation labels. We compare two parsing models for temporal de- pendency structures, and show that a determin- istic non-projective dependency parser outper- forms a graph-based maximum spanning tree parser, achieving labeled attachment accuracy of 0.647 and labeled tree edit distance of 0.596. Our analysis of the dependency parser errors gives some insights into...