Frame-Semantic Role Labeling with Heterogeneous Annotations

We consider the task of identifying and labeling the semantic arguments of a predicate that evokes a FrameNet frame. This task is challenging because there are only a few thousand fully annotated sentences for supervised training. Our approach augments an existing model with features derived from FrameNet and PropBank and with partially annotated exemplars from FrameNet. We observe a 4% absolute increase in F1 versus the original model.

• Type: Journal
• Year: 2015
• Where: ACL
• Authors: Meghana Kshirsagar, Sam Thomson, Nathan Schneider, Jaime G. Carbonell, Noah A. Smith, Chris Dyer
• Keywords: ACL 2015, Computational Linguistics