Temporal Histories of Epidemic Events (THEE): A Case Study in Temporal Annotation for Public Health

Jingcheng Niu, Victoria Ng, Gerald Penn, Erin E. Rees


Abstract
We present a new temporal annotation standard, THEE-TimeML, and a corpus TheeBank enabling precise temporal information extraction (TIE) for event-based surveillance (EBS) systems in the public health domain. Current EBS must estimate the occurrence time of each event based on coarse document metadata such as document publication time. Because of the complicated language and narration style of news articles, estimated case outbreak times are often inaccurate or even erroneous. Thus, it is necessary to create annotation standards and corpora to facilitate the development of TIE systems in the public health domain to address this problem. We will discuss the adaptations that have proved necessary for this domain as we present THEE-TimeML and TheeBank. Finally, we document the corpus annotation process, and demonstrate the immediate benefit to public health applications brought by the annotations.
Anthology ID:
2020.lrec-1.271
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2223–2230
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.271
DOI:
Bibkey:
Cite (ACL):
Jingcheng Niu, Victoria Ng, Gerald Penn, and Erin E. Rees. 2020. Temporal Histories of Epidemic Events (THEE): A Case Study in Temporal Annotation for Public Health. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2223–2230, Marseille, France. European Language Resources Association.
Cite (Informal):
Temporal Histories of Epidemic Events (THEE): A Case Study in Temporal Annotation for Public Health (Niu et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.271.pdf