Temporal Annotation in the Clinical Domain

William F. Styler IV, Steven Bethard, Sean Finan, Martha Palmer, Sameer Pradhan, Piet C de Groen, Brad Erickson, Timothy Miller, Chen Lin, Guergana Savova, James Pustejovsky


Abstract
This article discusses the requirements of a formal specification for the annotation of temporal information in clinical narratives. We discuss the implementation and extension of ISO-TimeML for annotating a corpus of clinical notes, known as the THYME corpus. To reflect the information task and the heavily inference-based reasoning demands in the domain, a new annotation guideline has been developed, “the THYME Guidelines to ISO-TimeML (THYME-TimeML)”. To clarify what relations merit annotation, we distinguish between linguistically-derived and inferentially-derived temporal orderings in the text. We also apply a top performing TempEval 2013 system against this new resource to measure the difficulty of adapting systems to the clinical domain. The corpus is available to the community and has been proposed for use in a SemEval 2015 task.
Anthology ID:
Q14-1012
Volume:
Transactions of the Association for Computational Linguistics, Volume 2
Month:
Year:
2014
Address:
Cambridge, MA
Editors:
Dekang Lin, Michael Collins, Lillian Lee
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
143–154
Language:
URL:
https://aclanthology.org/Q14-1012
DOI:
10.1162/tacl_a_00172
Bibkey:
Cite (ACL):
William F. Styler IV, Steven Bethard, Sean Finan, Martha Palmer, Sameer Pradhan, Piet C de Groen, Brad Erickson, Timothy Miller, Chen Lin, Guergana Savova, and James Pustejovsky. 2014. Temporal Annotation in the Clinical Domain. Transactions of the Association for Computational Linguistics, 2:143–154.
Cite (Informal):
Temporal Annotation in the Clinical Domain (Styler IV et al., TACL 2014)
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PDF:
https://aclanthology.org/Q14-1012.pdf
Video:
 https://aclanthology.org/Q14-1012.mp4