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Building unified timelines from a collection of written news articlesrequires cross-document event coreference resolution and temporal relationextraction. In this paper we present an approach event coreference resolutionaccording to: a) similar temporal information, and b) similar semanticarguments. Temporal information is detected using an automatic temporalinformation system (TIPSem), while semantic information is represented by meansof LDA Topic Modeling. The evaluation of our approach shows that it obtains thehighest Micro-average F-score results in the SemEval2015 Task 4: TimeLine:Cross-Document Event Ordering (25.36\% for TrackB, 23.15\% for SubtrackB), withan improvement of up to 6\% in comparison to the other systems. However, ourexperiment also showed some draw-backs in the Topic Modeling approach thatdegrades performance of the system.

Combining Temporal Information and Topic Modeling for Cross-Document Event Ordering