WVALI: Temporal Relation Identification by Syntactico-Semantic Analysis

Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval-2007), pages 484–487, Prague, June 2007. c⃝2007 Association for Computational Linguistics WVALI: Temporal Relation Identification by Syntactico-Semantic Analysis Georgiana Pus¸cas¸u†§ †Research Group in Computational Linguistics §Department of Software and Computing Systems University of Wolverhampton, UK University of Alicante, Spain georgie@wlv.ac.uk Abstract This paper reports on the participation of University of Wolverhampton and University of Alicante at the SemEval-2007 TempEval evaluation exercise. TempEval consisted of three tasks involving the identification of event-time and event-event temporal relations. We participated in all three tasks with TICTAC (Syntactico- Semantic Temporal Annotation Cluster), a system comprising both knowledge based and statistical techniques. Our system achieved the highest strict and relaxed scores for tasks A and B, and the highest relaxed score for task C. 1 Introduction TempEval comprises novel tasks concerned with the identification of temporal relations between events and temporal expressions (TEs). The evaluation exercise includes three tasks testing the capability of participating systems to relate an event and a TE located in the same sentence (task A), an event and the TE representing the Document Creation Time (DCT) (task B), and two events located in neighbouring sentences (task C). We tackle all tasks with a mix of knowledge based and statistical techniques incorporated in our system TICTAC. Our approach for discovering intrasentential temporal relations relies on sentence-level syntactic trees and on a bottom-up propagation of the temporal relations between syntactic constituents, by employing syntactical and lexical properties of the constituents and the relations between them. A temporal reasoning mechanism is afterwards employed to relate the two targeted temporal entities to their closest ancestor and then to each other. Conflict resolution heuristics are also applied. In establishing a temporal relation between an event and the Document Creation Time (DCT), the temporal expressions directly or indirectly linked to that event are first analysed and, if no relation is detected, the temporal relation with the DCT is propagated top-down in the syntactic tree. Inter-sentence temporal relations are discovered by first applying several heuristics that involve the temporal expressions and the tensed verbs of the two clauses containing the main events to be temporally related, and then by using statistical data extracted from the training corpus that revealed the most frequent temporal relation between two tensed verbs characterised by the tense information. This paper presents the techniques employed for the three TempEval tasks (Sections 2, 3 and 4 correspond to the tasks A, B and C). The evaluation results are presented and discussed in Section 5. Conclusions are drawn in the last section. 2 Task A Task A at TempEval involved the automatic identification of the temporal relations holding between events and all temporal expressions appearing in the same sentence. The events and TEs were annotated in the source in accordance with the TimeML standard (Pustejovsky et al., 2003a). For all tasks, the set of temporal relations to be predicted includes: OVERLAP, BEFORE, AFTER, 484 BEFORE-OR-OVERLAP, OVERLAP-OR-AFTER and VAGUE. Figure 1 depicts the processing stages involved in the …

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