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Extracting Subevents via an Effective Two-phase Approach
2016
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
We present our pilot research on automatically extracting subevents from a domain-specific corpus, focusing on the type of subevents that describe physical actions composing an event. We decompose the challenging problem and propose a two-phase approach that effectively captures sentential and local cues that describe subevents. We extracted a rich set of over 600 novel subevent phrases. Evaluation shows the automatically learned subevents help to discover 10% additional main events (of which
doi:10.18653/v1/d16-1088
dblp:conf/emnlp/BadgettH16
fatcat:oi6fnbeeprei5fcy7pxp76n74q