Inducing Temporal Relations from Time Anchor Annotation

Fei Cheng, Yusuke Miyao


Abstract
Recognizing temporal relations among events and time expressions has been an essential but challenging task in natural language processing. Conventional annotation of judging temporal relations puts a heavy load on annotators. In reality, the existing annotated corpora include annotations on only “salient” event pairs, or on pairs in a fixed window of sentences. In this paper, we propose a new approach to obtain temporal relations from absolute time value (a.k.a. time anchors), which is suitable for texts containing rich temporal information such as news articles. We start from time anchors for events and time expressions, and temporal relation annotations are induced automatically by computing relative order of two time anchors. This proposal shows several advantages over the current methods for temporal relation annotation: it requires less annotation effort, can induce inter-sentence relations easily, and increases informativeness of temporal relations. We compare the empirical statistics and automatic recognition results with our data against a previous temporal relation corpus. We also reveal that our data contributes to a significant improvement of the downstream time anchor prediction task, demonstrating 14.1 point increase in overall accuracy.
Anthology ID:
N18-1166
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marilyn Walker, Heng Ji, Amanda Stent
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1833–1843
Language:
URL:
https://aclanthology.org/N18-1166
DOI:
10.18653/v1/N18-1166
Bibkey:
Cite (ACL):
Fei Cheng and Yusuke Miyao. 2018. Inducing Temporal Relations from Time Anchor Annotation. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 1833–1843, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Inducing Temporal Relations from Time Anchor Annotation (Cheng & Miyao, NAACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/N18-1166.pdf
Video:
 https://aclanthology.org/N18-1166.mp4
Code
 racerandom/temporalorder