@inproceedings{67492c569b584cf1b85291729dcf782a,
title = "A Deep Learning-Based System for PharmaCoNER",
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. The shared task 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 microaverage F1-score of 0.8391 on track 2. c 2019 Association for Computational Linguistics.",
author = "Ying Xiong and Yedan Shen and Yuanhang Huang and Shuai Chen and Buzhou Tang and Xiaolong Wang and Qingcai Chen and Jun Yan and Yi Zhou",
note = "Publisher Copyright: {\textcopyright} 2019 BioNLP-OST@EMNLP-IJNCLP 2019 - Proceedings of the 5th Workshop on BioNLP Open Shared Tasks. All rights reserved.; 5th Workshop on BioNLP Open Shared Tasks, BioNLP-OST@EMNLP-IJNCLP 2019 ; Conference date: 04-11-2019",
year = "2019",
doi = "10.18653/v1/d19-5706",
language = "英语",
series = "BioNLP-OST@EMNLP-IJNCLP 2019 - Proceedings of the 5th Workshop on BioNLP Open Shared Tasks",
publisher = "Association for Computational Linguistics (ACL)",
pages = "33--37",
booktitle = "BioNLP-OST@EMNLP-IJNCLP 2019 - Proceedings of the 5th Workshop on BioNLP Open Shared Tasks",
address = "澳大利亚",
}