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Atténuer les erreurs de numérisation dans la reconnaissance d'entités nommées pour les documents historiques
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In: Conférence en Recherche d'Informations et Applications (CORIA 2021) ; https://hal.archives-ouvertes.fr/hal-03320332 ; Conférence en Recherche d'Informations et Applications (CORIA 2021), ARIA : Association Francophone de Recherche d’Information (RI) et Applications, Apr 2021, Grenoble (virtuel), France. pp.1 - 7 ; http://coria.asso-aria.org/2021/articles/mini_24/main.pdf (2021)
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A Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers
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In: SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval ; https://hal.archives-ouvertes.fr/hal-03418387 ; SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2021, Virtual Event, Canada. pp.2328-2334, ⟨10.1145/3404835.3463255⟩ (2021)
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MELHISSA: a multilingual entity linking architecture for historical press articles ...
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MELHISSA: a multilingual entity linking architecture for historical press articles ...
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Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers ...
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A Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers ...
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Annotation Guidelines for Named Entity Recognition, Entity Linking and Stance Detection ...
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Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers ...
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Annotation Guidelines for Named Entity Recognition, Entity Linking and Stance Detection ...
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A Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers ...
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Entity Linking for Historical Documents: Challenges and Solutions
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In: 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020 ; https://hal.archives-ouvertes.fr/hal-03034492 ; 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, 12504, Springer, pp.215-231, 2020, Lecture Notes in Computer Science, 978-3-030-64452-9. ⟨10.1007/978-3-030-64452-9_19⟩ (2020)
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Robust Named Entity Recognition and Linking on Historical Multilingual Documents
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In: Conference and Labs of the Evaluation Forum (CLEF 2020) ; https://hal.archives-ouvertes.fr/hal-03026969 ; Conference and Labs of the Evaluation Forum (CLEF 2020), Sep 2020, Thessaloniki, Greece. pp.1-17, ⟨10.5281/zenodo.4068074⟩ ; http://ceur-ws.org/Vol-2696/paper_171.pdf (2020)
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Robust Named Entity Recognition and Linking on Historical Multilingual Documents ...
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Robust Named Entity Recognition and Linking on Historical Multilingual Documents ...
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Benchmark for the evaluation of named entity recognition over ancient documents ...
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Robust Named Entity Recognition and Linking on Historical Multilingual Documents ...
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Benchmark for the evaluation of named entity recognition over ancient documents ...
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Robust Named Entity Recognition and Linking on Historical Multilingual Documents ...
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Alleviating Digitization Errors in Named Entity Recognition for Historical Documents ...
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Alleviating Digitization Errors in Named Entity Recognition for Historical Documents ...
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Abstract:
This paper tackles the task of named entity recognition (NER) applied to digitized historical texts obtained from processing digital images of newspapers using optical character recognition (OCR) techniques. We argue that the main challenge for this task is that the OCR process leads to misspellings and linguistic errors in the output text. Moreover, historical variations can be present in aged documents, which can impact the performance of the NER process. We conduct a comparative evaluation on two historical datasets in German and French against previous state-of-the-art models, and we propose a model based on a hierarchical stack of Transformers to approach the NER task for historical data. Our findings show that the proposed model clearly improves the results on both historical datasets, and does not degrade the results for modern datasets. ...
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URL: https://dx.doi.org/10.5281/zenodo.4475988 https://zenodo.org/record/4475988
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