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Named Entity Recognition and Classification on Historical Documents: A Survey

, , , , and . (2021)cite arxiv:2109.11406Comment: 39 pages.

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Named Entity Recognition and Classification on Historical Documents: A Survey., , , , and . CoRR, (2021)In-depth analysis of the impact of OCR errors on named entity recognition and linking., , , , and . Nat. Lang. Eng., 29 (2): 425-448 (March 2023)The Effects of Factorizing Root and Pattern Mapping in Bidirectional Tunisian - Standard Arabic Machine Translation., , , and . MTSummit, (2013)Knowledge-based Contexts for Historical Named Entity Recognition & Linking., , , , , and . CLEF (Working Notes), volume 3180 of CEUR Workshop Proceedings, page 1064-1078. CEUR-WS.org, (2022)A Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers., , , , , , and . SIGIR, page 2328-2334. ACM, (2021)Traitement automatique du dialecte tunisien à l'aide d'outils et de ressources de l'arabe standard : application à l'étiquetage morphosyntaxique. Aix-Marseille University, France, (2015)Automatically building a Tunisian Lexicon for Deverbal Nouns., , and . VarDial@COLING, page 95-102. Association for Computational Linguistics and Dublin City University, (2014)Yes but.. Can ChatGPT Identify Entities in Historical Documents?, , , , , and . JCDL, page 184-189. IEEE, (2023)DocILE 2023 Teaser: Document Information Localization and Extraction., , , , and . ECIR (3), volume 13982 of Lecture Notes in Computer Science, page 600-608. Springer, (2023)Alleviating Digitization Errors in Named Entity Recognition for Historical Documents., , , , , , and . CoNLL, page 431-441. Association for Computational Linguistics, (2020)