Paper: TimeML Events Recognition and Classification: Learning CRF Models with Semantic Roles

ACL ID C10-1082
Title TimeML Events Recognition and Classification: Learning CRF Models with Semantic Roles
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

This paper analyzes the contribution of se- mantic roles to TimeML event recognition and classification. For that purpose, an approach using conditional random fields with a variety of morphosyntactic features plus semantic roles features is developed and evaluated. Our system achieves an F1 of 81.4% in recognition and a 64.2% in classification. We demonstrate that the application of semantic roles improves the performance of the presented system, es- pecially for nominal events.