{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-neural-named-entity-recognition-and-multi","title":"A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text Mining","arxiv_id":null,"date":"2019-06-04","proceeding":"IEEE Access 2019 6","authors":["Donghyeon Kim","Jinhyuk Lee","Chan Ho So","Hwisang Jeon","Minbyul Jeong","Yonghwa Choi","Wonjin Yoon","Mujeen Sung","Jaewoo Kang"],"abstract":"The amount of biomedical literature is vast and growing quickly, and accurate text mining techniques could help researchers to efficiently extract useful information from the literature. However, existing named entity recognition models used by text mining tools such as tmTool and ezTag are not effective enough, and cannot accurately discover new entities. Also, the traditional text mining tools do not consider overlapping entities, which are frequently observed in multi-type named entity recognition results. We propose a neural biomedical named entity recognition and multi-type normalization tool called BERN. The BERN uses high-performance BioBERT named entity recognition models which recognize known entities and discover new entities. Also, probability-based decision rules are developed to identify the types of overlapping entities. Furthermore, various named entity normalization models are integrated into BERN for assigning a distinct identifier to each recognized entity. The BERN provides a Web service for tagging entities in PubMed articles or raw text. Researchers can use the BERN Web service for their text mining tasks, such as new named entity discovery, information retrieval, question answering, and relation extraction. The application programming interfaces and demonstrations of BERN are publicly available at https://bern.korea.ac.kr","url_abs":"https://ieeexplore.ieee.org/document/8730332","url_pdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8730332","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-neural-named-entity-recognition-and-multi","repo_url":"https://github.com/dmis-lab/bern","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"BSD-2-Clause"}}],"tasks":[{"task_slug":"articles","task_name":"Articles"},{"task_slug":"information-retrieval","task_name":"Information Retrieval"},{"task_slug":"named-entity-recognition-1","task_name":"Named Entity Recognition"},{"task_slug":"named-entity-recognition-ner","task_name":"Named Entity Recognition (NER)"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"relation-extraction","task_name":"Relation Extraction"},{"task_slug":"named-entity-recognition","task_name":"named-entity-recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/named-entity-recognition-on-bc2gm","task":"Named Entity Recognition (NER)","dataset":"BC2GM","model":"BERN","rank_in_archive_order":12,"of":13,"metrics":{"F1":"83.4"},"uses_additional_data":false},{"leaderboard":"/sota/named-entity-recognition-on-bc4chemd","task":"Named Entity Recognition (NER)","dataset":"BC4CHEMD","model":"BERN","rank_in_archive_order":5,"of":7,"metrics":{"F1":"91.2"},"uses_additional_data":false},{"leaderboard":"/sota/named-entity-recognition-on-linnaeus","task":"Named Entity Recognition (NER)","dataset":"LINNAEUS","model":"BERN","rank_in_archive_order":4,"of":6,"metrics":{"F1":"88.0"},"uses_additional_data":false},{"leaderboard":"/sota/named-entity-recognition-ner-on-ncbi-disease","task":"Named Entity Recognition (NER)","dataset":"NCBI-disease","model":"BERN","rank_in_archive_order":13,"of":26,"metrics":{"F1":"88.3"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}