The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII-Reference-Cited by-同舟云学术

The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII

Published:2024 Issue: Volume:2024 Page:
ISSN:1758-0463
Container-title:Database
language:en
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Author:

Islamaj Rezarta¹^ORCID,Lai Po-Ting¹,Wei Chih-Hsuan¹^ORCID,Luo Ling²^ORCID,Almeida Tiago³^ORCID,Jonker Richard A A³,Conceição Sofia I R⁴,Sousa Diana F⁴,Phan Cong-Phuoc⁵,Chiang Jung-Hsien⁵,Li Jiru²^ORCID,Pan Dinghao²,Meesawad Wilailack⁶,Tsai Richard Tzong-Han⁶⁷,Sarol M Janina⁸^ORCID,Hong Gibong⁸,Valiev Airat⁹,Tutubalina Elena⁹¹⁰^ORCID,Lee Shao-Man¹¹,Hsu Yi-Yu¹¹^ORCID,Li Mingjie¹²,Verspoor Karin¹²^ORCID,Lu Zhiyong¹^ORCID

Affiliation:

1. National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH) , 8600 Rockville Pike, Bethesda, MD 20894, United States

2. School of Computer Science and Technology, Dalian University of Technology , No. 2 Linggong Road, Ganjingzi District, Dalian 116024, China

3. Department of Electronics, Telecommunications and Informatics (DETI), Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro , Campus Universitário de Santiago, Aveiro 3810-193, Portugal

4. Departamento de Informática, Faculdade de Ciências da Universidade de Lisboa , Edifício C6 Campo Grande, Lisbon 1749-016, Portugal

5. Department of Computer Science and Information Engineering, National Cheng Kung University , No.1, University Road, Tainan City 701, Taiwan, Republic of China

6. Department of Computer Science and Information Engineering, National Central University , No. 300, Zhongda Rd., Zhongli District, Taoyuan City 32001, Taiwan, Republic of China

7. Research Center for Humanities and Social Sciences, Academia Sinica , No. 128, Section 2, Academia Rd., Nangang District, Taoyuan City 115201, Taiwan, Republic of China

8. School of Information Sciences, University of Illinois at Urbana-Champaign , 614 E. Daniel St, Champaign, IL 61820, United States

9. Higher School of Economics University , 20 Myasnitskaya st, Moscow 101000, Russia

10. Kazan Federal University , 18 Kremlevskaya st, Kazan, Russia 420008, Russia

11. Miin Wu School of Computing, National Cheng Kung University , No. 1, University Road, Tainan 701, Taiwan, Republic of China

12. School of Computing Technologies, RMIT University , 124 La Trobe Street, Melbourne, Victoria 3000, Australia

Abstract

Abstract The BioRED track at BioCreative VIII calls for a community effort to identify, semantically categorize, and highlight the novelty factor of the relationships between biomedical entities in unstructured text. Relation extraction is crucial for many biomedical natural language processing (NLP) applications, from drug discovery to custom medical solutions. The BioRED track simulates a real-world application of biomedical relationship extraction, and as such, considers multiple biomedical entity types, normalized to their specific corresponding database identifiers, as well as defines relationships between them in the documents. The challenge consisted of two subtasks: (i) in Subtask 1, participants were given the article text and human expert annotated entities, and were asked to extract the relation pairs, identify their semantic type and the novelty factor, and (ii) in Subtask 2, participants were given only the article text, and were asked to build an end-to-end system that could identify and categorize the relationships and their novelty. We received a total of 94 submissions from 14 teams worldwide. The highest F-score performances achieved for the Subtask 1 were: 77.17% for relation pair identification, 58.95% for relation type identification, 59.22% for novelty identification, and 44.55% when evaluating all of the above aspects of the comprehensive relation extraction. The highest F-score performances achieved for the Subtask 2 were: 55.84% for relation pair, 43.03% for relation type, 42.74% for novelty, and 32.75% for comprehensive relation extraction. The entire BioRED track dataset and other challenge materials are available at https://ftp.ncbi.nlm.nih.gov/pub/lu/BC8-BioRED-track/ and https://codalab.lisn.upsaclay.fr/competitions/13377 and https://codalab.lisn.upsaclay.fr/competitions/13378. Database URL: https://ftp.ncbi.nlm.nih.gov/pub/lu/BC8-BioRED-track/https://codalab.lisn.upsaclay.fr/competitions/13377https://codalab.lisn.upsaclay.fr/competitions/13378

Funder

Research Unit

Russian Science Foundation

Kazan Federal University

LASIGE Computer Science and Engineering Research Centre

Fundamental Research Funds for the Central Universities

Fct

Fundação para a Ciência e a Tecnologia

the NIH Intramural Research Program, National Library of Medicine

FCT

Publisher

Oxford University Press (OUP)