BENNERD: A Neural Named Entity Linking System for COVID-19

Mohammad Golam Sohrab, Khoa Duong, Makoto Miwa, Goran Topić, Ikeda Masami, Takamura Hiroya

Abstract
We present a biomedical entity linking (EL) system BENNERD that detects named enti- ties in text and links them to the unified medical language system (UMLS) knowledge base (KB) entries to facilitate the corona virus disease 2019 (COVID-19) research. BEN- NERD mainly covers biomedical domain, es- pecially new entity types (e.g., coronavirus, vi- ral proteins, immune responses) by address- ing CORD-NER dataset. It includes several NLP tools to process biomedical texts includ- ing tokenization, flat and nested entity recog- nition, and candidate generation and rank- ing for EL that have been pre-trained using the CORD-NER corpus. To the best of our knowledge, this is the first attempt that ad- dresses NER and EL on COVID-19-related entities, such as COVID-19 virus, potential vaccines, and spreading mechanism, that may benefit research on COVID-19. We release an online system to enable real-time entity annotation with linking for end users. We also release the manually annotated test set and CORD-NERD dataset for leveraging EL task. The BENNERD system is available at https://aistairc.github.io/BENNERD/.
Anthology ID:
2020.emnlp-demos.24
Volume:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
October
Year:
2020
Address:
Online
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
182–188
Language:
URL:
https://aclanthology.org/2020.emnlp-demos.24
DOI:
10.18653/v1/2020.emnlp-demos.24
Bibkey:
Cite (ACL):
Mohammad Golam Sohrab, Khoa Duong, Makoto Miwa, Goran Topić, Ikeda Masami, and Takamura Hiroya. 2020. BENNERD: A Neural Named Entity Linking System for COVID-19. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 182–188, Online. Association for Computational Linguistics.
Cite (Informal):
BENNERD: A Neural Named Entity Linking System for COVID-19 (Sohrab et al., EMNLP 2020)
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