In this paper, we present a system, UTTime, which we submitted to TempEval-3 for Task C: Annotating temporal relations. The system uses logistic regression classifiers and exploits features extracted from a deep syntactic parser, including paths between event words in phrase structure trees and their path lengths, and paths between event words in predicateargument structures and their subgraphs. UTTime achieved an F1 score of 34.9 based on the graphed-based evaluation for Task C (ranked 2 nd ) and 56.45 for Task C-relationonly (ranked 1 st ) in the TempEval-3 evaluation.
['Natsuda Laokulrat', 'Makoto Miwa', 'Yoshimasa Tsuruoka', 'Takashi Chikayama']
UTTime: Temporal Relation Classification using Deep Syntactic Features