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1
Ungoliant: An Optimized Pipeline for the Generation of a Very Large-Scale Multilingual Web Corpus
In: CMLC 2021 - 9th Workshop on Challenges in the Management of Large Corpora ; https://hal.inria.fr/hal-03301590 ; CMLC 2021 - 9th Workshop on Challenges in the Management of Large Corpora, Jul 2021, Limerick / Virtual, Ireland. ⟨10.14618/ids-pub-10468⟩ ; https://www.cl2021.org/ (2021)
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2
Expanding the content model of annotationBlock
In: Next Gen TEI, 2021 - TEI Conference and Members’ Meeting ; https://hal.archives-ouvertes.fr/hal-03380805 ; Next Gen TEI, 2021 - TEI Conference and Members’ Meeting, Oct 2021, Virtual, United States (2021)
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3
Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus ...
Abadji, Julien; Ortiz Suárez, Pedro Javier; Romary, Laurent. - : Leibniz-Institut für Deutsche Sprache, 2021
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Establishing a New State-of-the-Art for French Named Entity Recognition
In: LREC 2020 - 12th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-02617950 ; LREC 2020 - 12th Language Resources and Evaluation Conference, May 2020, Marseille, France ; http://www.lrec-conf.org (2020)
Abstract: Due to COVID19 pandemic, the 12th edition is cancelled. The LREC 2020 Proceedings are available at http://www.lrec-conf.org/proceedings/lrec2020/index.html ; International audience ; The French TreeBank developed at the University Paris 7 is the main source of morphosyntactic and syntactic annotations for French. However, it does not include explicit information related to named entities, which are among the most useful information for several natural language processing tasks and applications. Moreover, no large-scale French corpus with named entity annotations contain referential information, which complement the type and the span of each mention with an indication of the entity it refers to. We have manually annotated the French TreeBank with such information, after an automatic pre-annotation step. We sketch the underlying annotation guidelines and we provide a few figures about the resulting annotations.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; French; Language Modeling; Named Entity Recognition
URL: https://hal.inria.fr/hal-02617950v2/file/lrec19ner.pdf
https://hal.inria.fr/hal-02617950v2/document
https://hal.inria.fr/hal-02617950
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5
CamemBERT: a Tasty French Language Model
In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-02889805 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States. ⟨10.18653/v1/2020.acl-main.645⟩ (2020)
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6
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-02863875 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States. ⟨10.18653/v1/2020.acl-main.156⟩ ; https://acl2020.org (2020)
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7
Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures
In: 7th Workshop on the Challenges in the Management of Large Corpora (CMLC-7) ; https://hal.inria.fr/hal-02148693 ; 7th Workshop on the Challenges in the Management of Large Corpora (CMLC-7), Jul 2019, Cardiff, United Kingdom. ⟨10.14618/IDS-PUB-9021⟩ (2019)
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8
CamemBERT: a Tasty French Language Model
In: https://hal.inria.fr/hal-02445946 ; 2019 (2019)
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9
Preparing the Dictionnaire Universel for Automatic Enrichment
In: 10th International Conference on Historical Lexicography and Lexicology (ICHLL) ; https://hal.inria.fr/hal-02131598 ; 10th International Conference on Historical Lexicography and Lexicology (ICHLL), Jun 2019, Leeuwarden, Netherlands ; https://easychair.org/smart-program/ICHLL-10/ (2019)
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10
Asynchronous pipelines for processing huge corpora on medium to low resource infrastructures ...
Ortiz Suárez, Pedro Javier; Sagot, Benoît; Romary, Laurent. - : Leibniz-Institut für Deutsche Sprache, 2019
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