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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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Abstract:
Named entity processing over historical texts is more and more being used due to the massive documents and archives being stored in digital libraries. However, due to the poor annotated resources of historical nature, information extraction performances fall behind those on contemporary texts. In this paper, we introduce the development of the NewsEye resource, a multilingual dataset for named entity recognition and linking enriched with stances towards named entities. The dataset is comprised of diachronic historical newspaper material published between 1850 and 1950 in French, German, Finnish, and Swedish. Such historical resource is essential in the context of developing and evaluating named entity processing systems. It evenly allows enhancing the forcefulness of existing approaches on historical documents which enable adequate and efficient semantic indexing of historical documents on digital cultural heritage collections ...
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URL: https://zenodo.org/record/4694465 https://dx.doi.org/10.5281/zenodo.4694465
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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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