Paper: KUL: Data-driven Approach to Temporal Parsing of Newswire Articles

ACL ID S13-2014
Title KUL: Data-driven Approach to Temporal Parsing of Newswire Articles
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes a system for temporal processing of text, which participated in the Temporal Evaluations 2013 campaign. The system employs a number of machine learning classifiers to perform the core tasks of: identi- fication of time expressions and events, recog- nition of their attributes, and estimation of temporal links between recognized events and times. The central feature of the proposed sys- tem is temporal parsing ? an approach which identifies temporal relation arguments (event- event and event-timex pairs) and the semantic label of the relation as a single decision.