{"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-fofe-based-local-detection-approach-for","title":"A FOFE-based Local Detection Approach for Named Entity Recognition and Mention Detection","arxiv_id":"1611.00801","date":"2016-11-02","proceeding":null,"authors":["Mingbin Xu","Hui Jiang"],"abstract":"In this paper, we study a novel approach for named entity recognition (NER)\nand mention detection in natural language processing. Instead of treating NER\nas a sequence labelling problem, we propose a new local detection approach,\nwhich rely on the recent fixed-size ordinally forgetting encoding (FOFE) method\nto fully encode each sentence fragment and its left/right contexts into a\nfixed-size representation. Afterwards, a simple feedforward neural network is\nused to reject or predict entity label for each individual fragment. The\nproposed method has been evaluated in several popular NER and mention detection\ntasks, including the CoNLL 2003 NER task and TAC-KBP2015 and TAC-KBP2016\nTri-lingual Entity Discovery and Linking (EDL) tasks. Our methods have yielded\npretty strong performance in all of these examined tasks. This local detection\napproach has shown many advantages over the traditional sequence labelling\nmethods.","url_abs":"http://arxiv.org/abs/1611.00801v1","url_pdf":"http://arxiv.org/pdf/1611.00801v1.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-fofe-based-local-detection-approach-for","repo_url":"https://github.com/xmb-cipher/fofe-ner","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","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":"sentence","task_name":"Sentence"},{"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}