JaMIE: A Pipeline Japanese Medical Information Extraction System with Novel Relation Annotation

Fei Cheng, Shuntaro Yada, Ribeka Tanaka, Eiji Aramaki, Sadao Kurohashi


Abstract
In the field of Japanese medical information extraction, few analyzing tools are available and relation extraction is still an under-explored topic. In this paper, we first propose a novel relation annotation schema for investigating the medical and temporal relations between medical entities in Japanese medical reports. We experiment with the practical annotation scenarios by separately annotating two different types of reports. We design a pipeline system with three components for recognizing medical entities, classifying entity modalities, and extracting relations. The empirical results show accurate analyzing performance and suggest the satisfactory annotation quality, the superiority of the latest contextual embedding models. and the feasible annotation strategy for high-accuracy demand.
Anthology ID:
2022.lrec-1.397
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
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, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
3724–3731
Language:
URL:
https://aclanthology.org/2022.lrec-1.397
DOI:
Bibkey:
Cite (ACL):
Fei Cheng, Shuntaro Yada, Ribeka Tanaka, Eiji Aramaki, and Sadao Kurohashi. 2022. JaMIE: A Pipeline Japanese Medical Information Extraction System with Novel Relation Annotation. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 3724–3731, Marseille, France. European Language Resources Association.
Cite (Informal):
JaMIE: A Pipeline Japanese Medical Information Extraction System with Novel Relation Annotation (Cheng et al., LREC 2022)
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PDF:
https://aclanthology.org/2022.lrec-1.397.pdf