USFD2: Annotating Temporal Expresions and TLINKs for TempEval-2

TL;DR

The USFD2 system for TempEval-2 effectively identifies and classifies temporal expressions with high accuracy, and accurately determines temporal relations within sentences, advancing automated temporal information extraction.

Contribution

This paper introduces a rule-based and maximum entropy classifier hybrid system for temporal expression and relation extraction in the TempEval-2 challenge.

Findings

90% accuracy in temporal expression classification

63% accuracy in event-time relation within sentences

Second highest score in relation classification task

Abstract

We describe the University of Sheffield system used in the TempEval-2 challenge, USFD2. The challenge requires the automatic identification of temporal entities and relations in text. USFD2 identifies and anchors temporal expressions, and also attempts two of the four temporal relation assignment tasks. A rule-based system picks out and anchors temporal expressions, and a maximum entropy classifier assigns temporal link labels, based on features that include descriptions of associated temporal signal words. USFD2 identified temporal expressions successfully, and correctly classified their type in 90% of cases. Determining the relation between an event and time expression in the same sentence was performed at 63% accuracy, the second highest score in this part of the challenge.