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ACL
2015

Seed-Based Event Trigger Labeling: How far can event descriptions get us?

8 years 1 months ago
Seed-Based Event Trigger Labeling: How far can event descriptions get us?
The task of event trigger labeling is typically addressed in the standard supervised setting: triggers for each target event type are annotated as training data, based on annotation guidelines. We propose an alternative approach, which takes the example trigger terms mentioned in the guidelines as seeds, and then applies an eventindependent similarity-based classifier for trigger labeling. This way we can skip manual annotation for new event types, while requiring only minimal annotated training data for few example events at system setup. Our method is evaluated on the ACE-2005 dataset, achieving 5.7% F1 improvement over a state-of-the-art supervised system which uses the full training data.
Ofer Bronstein, Ido Dagan, Qi Li, Heng Ji, Anette
Added 13 Apr 2016
Updated 13 Apr 2016
Type Journal
Year 2015
Where ACL
Authors Ofer Bronstein, Ido Dagan, Qi Li, Heng Ji, Anette Frank
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