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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.<\/jats:p>\n               <jats:p>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<\/jats:p>","DOI":"10.1093\/database\/baae069","type":"journal-article","created":{"date-parts":[[2024,8,8]],"date-time":"2024-08-08T18:57:12Z","timestamp":1723143432000},"source":"Crossref","is-referenced-by-count":5,"title":["The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII"],"prefix":"10.1093","volume":"2024","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5651-1860","authenticated-orcid":false,"given":"Rezarta","family":"Islamaj","sequence":"first","affiliation":[{"name":"National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH) , 8600 Rockville Pike, Bethesda, MD 20894,","place":["United States"]}]},{"given":"Po-Ting","family":"Lai","sequence":"additional","affiliation":[{"name":"National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH) , 8600 Rockville Pike, Bethesda, MD 20894,","place":["United States"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5094-7321","authenticated-orcid":false,"given":"Chih-Hsuan","family":"Wei","sequence":"additional","affiliation":[{"name":"National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH) , 8600 Rockville Pike, Bethesda, MD 20894,","place":["United States"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5141-0259","authenticated-orcid":false,"given":"Ling","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Dalian University of Technology , No. 2 Linggong Road, Ganjingzi District, Dalian 116024,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4258-3350","authenticated-orcid":false,"given":"Tiago","family":"Almeida","sequence":"additional","affiliation":[{"name":"Department of Electronics, Telecommunications and Informatics (DETI), Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro , Campus Universit\u00e1rio de Santiago, Aveiro 3810-193,","place":["Portugal"]}]},{"given":"Richard A. 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