{"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-byte-sized-approach-to-named-entity","title":"A Byte-sized Approach to Named Entity Recognition","arxiv_id":"1809.08386","date":"2018-09-22","proceeding":null,"authors":["Emily Sheng","Prem Natarajan"],"abstract":"In biomedical literature, it is common for entity boundaries to not align\nwith word boundaries. Therefore, effective identification of entity spans\nrequires approaches capable of considering tokens that are smaller than words.\nWe introduce a novel, subword approach for named entity recognition (NER) that\nuses byte-pair encodings (BPE) in combination with convolutional and recurrent\nneural networks to produce byte-level tags of entities. We present experimental\nresults on several standard biomedical datasets, namely the BioCreative VI\nBio-ID, JNLPBA, and GENETAG datasets. We demonstrate competitive performance\nwhile bypassing the specialized domain expertise needed to create biomedical\ntext tokenization rules.","url_abs":"http://arxiv.org/abs/1809.08386v1","url_pdf":"http://arxiv.org/pdf/1809.08386v1.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":"a-byte-sized-approach-to-named-entity","repo_url":"https://github.com/ewsheng/byteNER","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"cg","task_name":"NER"},{"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":"named-entity-recognition","task_name":"named-entity-recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}