Paper: Employing Event Inference to Improve Semi-Supervised Chinese Event Extraction

ACL ID C14-1204
Title Employing Event Inference to Improve Semi-Supervised Chinese Event Extraction
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

Although semi-supervised model can extract the event mentions matching frequent event patterns, it suf- fers much from those event mentions, which match infrequent patterns or have no matching pattern. To solve this issue, this paper introduces various kinds of linguistic knowledge-driven event inference mechanisms to semi-supervised Chinese event extraction. These event inference mechanisms can capture linguistic knowledge from four aspects, i.e. semantics of argument role, compositional semantics of trig- ger, consistency on coreference events and relevant events, to further recover missing event mentions from unlabeled texts. Evaluation on the ACE 2005 Chinese corpus shows that our event inference mech- anisms significantly outperform the refined state-of-the-art semi-supervised Chi...