CONNER: A Cascade Count and Measurement Extraction Tool for Scientific Discourse

Jiarun Cao, Yuejia Xiang, Yunyan Zhang, Zhiyuan Qi, Xi Chen, Yefeng Zheng


Abstract
This paper presents our wining contribution to SemEval 2021 Task 8: MeasEval. The purpose of this task is identifying the counts and measurements from clinical scientific discourse, including quantities, entities, properties, qualifiers, units, modifiers, and their mutual relations. This task can be induced to a joint entity and relation extraction problem. Accordingly, we propose CONNER, a cascade count and measurement extraction tool that can identify entities and the corresponding relations in a two-step pipeline model. We provide a detailed description of the proposed model hereinafter. Furthermore, the impact of the essential modules and our in-process technical schemes are also investigated.
Anthology ID:
2021.semeval-1.176
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1239–1244
Language:
URL:
https://aclanthology.org/2021.semeval-1.176
DOI:
10.18653/v1/2021.semeval-1.176
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.176.pdf