Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study

Yuchen Zhang, Nianwen Xue


Abstract
Temporal Dependency Trees are a structured temporal representation that represents temporal relations among time expressions and events in a text as a dependency tree structure. Compared to traditional pair-wise temporal relation representations, temporal dependency trees facilitate efficient annotations, higher inter-annotator agreement, and efficient computations. However, annotations on temporal dependency trees so far have only been done by expert annotators, which is costly and time-consuming. In this paper, we introduce a method to crowdsource temporal dependency tree annotations, and show that this representation is intuitive and can be collected with high accuracy and agreement through crowdsourcing. We produce a corpus of temporal dependency trees, and present a baseline temporal dependency parser, trained and evaluated on this new corpus.
Anthology ID:
S19-1019
Volume:
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Editors:
Rada Mihalcea, Ekaterina Shutova, Lun-Wei Ku, Kilian Evang, Soujanya Poria
Venue:
*SEM
SIGs:
SIGSEM | SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
178–185
Language:
URL:
https://aclanthology.org/S19-1019
DOI:
10.18653/v1/S19-1019
Bibkey:
Cite (ACL):
Yuchen Zhang and Nianwen Xue. 2019. Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 178–185, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study (Zhang & Xue, *SEM 2019)
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PDF:
https://preview.aclanthology.org/naacl-24-ws-corrections/S19-1019.pdf