HeidelToul: A Baseline Approach for Cross-document Event Ordering

Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pages 825–829, Denver, Colorado, June 4-5, 2015. c⃝2015 Association for Computational Linguistics HeidelToul: A Baseline Approach for Cross-document Event Ordering Bilel Moulahi1,3∗and Jannik Str¨otgen2 and Michael Gertz2 and Lynda Tamine1 1 IRIT, University of Toulouse Paul Sabatier, France 2 Institute of Computer Science, Heidelberg University, Germany 3 Faculty of Science of Tunis, University of Tunis El-Manar, Tunisia {bilel.moulahi,lynda.lechani}@irit.fr {stroetgen,gertz}@informatik.uni-heidelberg.de Abstract In this paper, we give an overview of our participation in the timeline generation task of SemEval-2015 (task 4, TimeLine: Cross- Document Event Ordering). The main goals of this new track are, given a collection of news articles and a so-called target entity, to determine events that are relevant for the en- tity, to resolve event coreferences, and to order the events chronologically. We addressed the sub-tasks, in which event mentions were pro- vided, i.e., no additional event extraction was required. For this, we developed an ad-hoc ap- proach based on a temporal tagger and a coref- erence resolution tool for entities. After de- termining relevant sentences, relevant events are extracted and anchored on a timeline. The evaluation conducted on three collections of news articles shows that our approach – de- spite its simplicity – achieves reasonable re- sults and opens several promising issues for future work. 1 Introduction Due to the tremendous amount of documents being constantly published on the Internet, there is a need for more enhanced search facilities to retrieve rel- evant information. Consider, for example, a user looking for information about the “Golden Globe Awards”. It might be possible that the user’s in- formation need is about the recent “72nd edition”. However, it is also reasonable to assume that the user ∗The work was done during an internship at Heidelberg University. would appreciate relevant information about previ- ous editions. Thus, presenting search results for time- and event-sensitive information needs in the form of a complete and updatable timeline would be a promising approach. While this issue is tack- led by some applications, early techniques required manual effort (Shahar and Musen, 1992) and recent approaches rely on heavily structured information such as Google’s entity-related search results, which are based on Google’s knowledge graph (Singhal, 2012). However, instead of listing only structured knowledge on a timeline, e.g., winners of the 71st Golden Globes in our example, search results would become much more valuable when adding tempo- rally anchored event information extracted from text documents (e.g., recent updates about the event). In the SemEval task 4,1 the goal is to detect all events in a document collection that are relevant for a target entity, and to anchor these events on a time- line. Thus, events are to be sorted chronologically, and, if possible, specific dates are to be assigned to the events. As in previous SemEval tasks addressing temporal relation extraction, namely in the Temp- Eval series (see, e.g., Verhagen et al., 2010), the TimeML event definition is used. However, a special focus is now put on the …

Content truncated to 500 words