{"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/integrated-sequence-tagging-for-medieval","title":"Integrated Sequence Tagging for Medieval Latin Using Deep Representation Learning","arxiv_id":"1603.01597","date":"2016-03-04","proceeding":null,"authors":["Mike Kestemont","Jeroen De Gussem"],"abstract":"In this paper we consider two sequence tagging tasks for medieval Latin:\npart-of-speech tagging and lemmatization. These are both basic, yet\nfoundational preprocessing steps in applications such as text re-use detection.\nNevertheless, they are generally complicated by the considerable orthographic\nvariation which is typical of medieval Latin. In Digital Classics, these tasks\nare traditionally solved in a (i) cascaded and (ii) lexicon-dependent fashion.\nFor example, a lexicon is used to generate all the potential lemma-tag pairs\nfor a token, and next, a context-aware PoS-tagger is used to select the most\nappropriate tag-lemma pair. Apart from the problems with out-of-lexicon items,\nerror percolation is a major downside of such approaches. In this paper we\nexplore the possibility to elegantly solve these tasks using a single,\nintegrated approach. For this, we make use of a layered neural network\narchitecture from the field of deep representation learning.","url_abs":"http://arxiv.org/abs/1603.01597v2","url_pdf":"http://arxiv.org/pdf/1603.01597v2.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":"integrated-sequence-tagging-for-medieval","repo_url":"https://github.com/jedgusse/collaborative-authorship","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"lemma","task_name":"LEMMA"},{"task_slug":"lemmatization","task_name":"Lemmatization"},{"task_slug":"pos","task_name":"POS"},{"task_slug":"part-of-speech-tagging","task_name":"Part-Of-Speech Tagging"},{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"tag","task_name":"TAG"}],"methods":[],"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}