A Deep Learning-Based System for PharmaCoNER
Ying Xiong, Yedan Shen, Yuanhang Huang, Shuai Chen, Buzhou Tang, Xiaolong Wang, Qingcai Chen, Jun Yan, Yi Zhou
Abstract
The Biological Text Mining Unit at BSC and CNIO organized the first shared task on chemical & drug mention recognition from Spanish medical texts called PharmaCoNER (Pharmacological Substances, Compounds and proteins and Named Entity Recognition track) in 2019, which includes two tracks: one for NER offset and entity classification (track 1) and the other one for concept indexing (track 2). We developed a pipeline system based on deep learning methods for this shared task, specifically, a subsystem based on BERT (Bidirectional Encoder Representations from Transformers) for NER offset and entity classification and a subsystem based on Bpool (Bi-LSTM with max/mean pooling) for concept indexing. Evaluation conducted on the shared task data showed that our system achieves a micro-average F1-score of 0.9105 on track 1 and a micro-average F1-score of 0.8391 on track 2.- Anthology ID:
- D19-5706
- Volume:
- Proceedings of the 5th Workshop on BioNLP Open Shared Tasks
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- Kim Jin-Dong, Nédellec Claire, Bossy Robert, Deléger Louise
- Venue:
- BioNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 33–37
- Language:
- URL:
- https://aclanthology.org/D19-5706
- DOI:
- 10.18653/v1/D19-5706
- Cite (ACL):
- Ying Xiong, Yedan Shen, Yuanhang Huang, Shuai Chen, Buzhou Tang, Xiaolong Wang, Qingcai Chen, Jun Yan, and Yi Zhou. 2019. A Deep Learning-Based System for PharmaCoNER. In Proceedings of the 5th Workshop on BioNLP Open Shared Tasks, pages 33–37, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- A Deep Learning-Based System for PharmaCoNER (Xiong et al., BioNLP 2019)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/D19-5706.pdf