{"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/bio-yodie-a-named-entity-linking-system-for","title":"Bio-YODIE: A Named Entity Linking System for Biomedical Text","arxiv_id":"1811.04860","date":"2018-11-12","proceeding":null,"authors":["Genevieve Gorrell","Xingyi Song","Angus Roberts"],"abstract":"Ever-expanding volumes of biomedical text require automated semantic\nannotation techniques to curate and put to best use. An established field of\nresearch seeks to link mentions in text to knowledge bases such as those\nincluded in the UMLS (Unified Medical Language System), in order to enable a\nmore sophisticated understanding. This work has yielded good results for tasks\nsuch as curating literature, but increasingly, annotation systems are more\nbroadly applied. Medical vocabularies are expanding in size, and with them the\nextent of term ambiguity. Document collections are increasing in size and\ncomplexity, creating a greater need for speed and robustness. Furthermore, as\nthe technologies are turned to new tasks, requirements change; for example\ngreater coverage of expressions may be required in order to annotate patient\nrecords, and greater accuracy may be needed for applications that affect\npatients. This places new demands on the approaches currently in use. In this\nwork, we present a new system, Bio-YODIE, and compare it to two other popular\nsystems in order to give guidance about suitable approaches in different\nscenarios and how systems might be designed to accommodate future needs.","url_abs":"http://arxiv.org/abs/1811.04860v1","url_pdf":"http://arxiv.org/pdf/1811.04860v1.pdf","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":"bio-yodie-a-named-entity-linking-system-for","repo_url":"https://github.com/GateNLP/Bio-YODIE","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"entity-linking","task_name":"Entity Linking"}],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}