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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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Gado2: multilingual newspapers from the Netherlands Indies ...
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Gado2: multilingual newspapers from the Netherlands Indies ...
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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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Gado2: multilingual newspapers from the Netherlands Indies ...
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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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Gado2: multilingual newspapers from the Netherlands Indies ...
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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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Linking Named Entities across Languages using Multilingual Word Embeddings ...
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Abstract:
Digital libraries are online collections of digital objects that can include text, images, audio, or videos in several languages. It has long been observed that named entities (NEs) are key to the access to digital library portals as they are contained in most user queries. However, NEs can have different spellings for each language which reduces the performance of user queries to retrieve documents across languages. Cross-lingual named entity linking (XEL) connects NEs from documents in a source language to external knowledge bases in another (target) language. The XEL task is especially challenging due to the diversity of NEs across languages and contexts. This paper describes a XEL system applied and evaluated with several languages pairs including English and various low-resourced languages of different linguistic families such as Croatian, Finnish, Estonian and Slovenian. We tested this approach to analyze documents and NEs in low-resourced languages and link them to the English version of Wikipedia. We ...
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Keyword:
Cross-Lingual Named Entity Linking; Digital Library; Indexing; Multilingual Word Embeddings
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URL: https://dx.doi.org/10.5281/zenodo.3759436 https://zenodo.org/record/3759436
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