{"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/sequence-labeling-a-practical-approach","title":"Sequence Labeling: A Practical Approach","arxiv_id":"1808.03926","date":"2018-08-12","proceeding":null,"authors":["Adnan Akhundov","Dietrich Trautmann","Georg Groh"],"abstract":"We take a practical approach to solving sequence labeling problem assuming\nunavailability of domain expertise and scarcity of informational and\ncomputational resources. To this end, we utilize a universal end-to-end\nBi-LSTM-based neural sequence labeling model applicable to a wide range of NLP\ntasks and languages. The model combines morphological, semantic, and structural\ncues extracted from data to arrive at informed predictions. The model's\nperformance is evaluated on eight benchmark datasets (covering three tasks:\nPOS-tagging, NER, and Chunking, and four languages: English, German, Dutch, and\nSpanish). We observe state-of-the-art results on four of them: CoNLL-2012\n(English NER), CoNLL-2002 (Dutch NER), GermEval 2014 (German NER), Tiger Corpus\n(German POS-tagging), and competitive performance on the rest.","url_abs":"http://arxiv.org/abs/1808.03926v1","url_pdf":"http://arxiv.org/pdf/1808.03926v1.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":"sequence-labeling-a-practical-approach","repo_url":"https://github.com/aakhundov/sequence-labeling","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"chunking","task_name":"Chunking"},{"task_slug":"cg","task_name":"NER"},{"task_slug":"pos","task_name":"POS"},{"task_slug":"pos-tagging","task_name":"POS Tagging"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1808.03926","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}