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1
Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources
In: https://hal.inria.fr/hal-03550289 ; 2022 (2022)
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2
From FreEM to D'AlemBERT ; From FreEM to D'AlemBERT: a Large Corpus and a Language Model for Early Modern French
In: Proceedings of the 13th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-03596653 ; Proceedings of the 13th Language Resources and Evaluation Conference, European Language Resources Association, Jun 2022, Marseille, France (2022)
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3
Towards a Cleaner Document-Oriented Multilingual Crawled Corpus
In: https://hal.inria.fr/hal-03536361 ; 2022 (2022)
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4
A dataset for automatic detection of places in (early) modern French texts ; Un jeu de données pour la détection automatique de lieux dans les textes français modernes
In: NASSCFL 2021 - 50th Annual North American Society for Seventeenth-Century French Literature Conference ; https://hal.archives-ouvertes.fr/hal-03187097 ; NASSCFL 2021 - 50th Annual North American Society for Seventeenth-Century French Literature Conference, NASSCFL, May 2021, Iowa City / Virtual, United States. pp.5 (2021)
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5
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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6
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets
In: https://hal.inria.fr/hal-03177623 ; 2021 (2021)
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7
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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8
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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9
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)
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10
Building a User-Generated Content North-African Arabizi Treebank: Tackling Hell
In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-02889804 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, Canada. ⟨10.18653/v1/2020.acl-main.107⟩ (2020)
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11
SinNer@Clef-Hipe2020 : Sinful adaptation of SotA models for Named Entity Recognition in French and German
In: CLEF 2020 Working Notes. Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum ; https://hal.inria.fr/hal-02984746 ; CLEF 2020 Working Notes. Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum, Sep 2020, Thessaloniki / Virtual, Greece ; https://impresso.github.io/CLEF-HIPE-2020/ (2020)
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12
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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13
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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14
French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus
In: CMLC-8 - 8th Workshop on the Challenges in the Management of Large Corpora ; https://hal.inria.fr/hal-02678358 ; CMLC-8 - 8th Workshop on the Challenges in the Management of Large Corpora, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/media/proceedings/Workshops/Books/CMLC-8book.pdf (2020)
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15
Asynchronous pipelines for processing huge corpora on medium to low resource infrastructures
Ortiz Suárez, Pedro Javier [Verfasser]; Sagot, Benoît [Verfasser]; Romary, Laurent [Verfasser]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2019
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16
How OCR Performance can Impact on the Automatic Extraction of Dictionary Content Structures
In: 19th annual Conference and Members’ Meeting of the Text Encoding Initiative Consortium (TEI) -What is text, really? TEI and beyond ; https://hal.archives-ouvertes.fr/hal-02263276 ; 19th annual Conference and Members’ Meeting of the Text Encoding Initiative Consortium (TEI) -What is text, really? TEI and beyond, Sep 2019, Graz, Austria (2019)
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17
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)
Abstract: International audience ; Common Crawl is a considerably large, heterogeneous multilingual corpus comprised of crawled documents from the internet, surpassing 20TB of data and distributed as a set of more than 50 thousand plain text files where each contains many documents written in a wide variety of languages. Even though each document has a metadata block associated to it, this data lacks any information about the language in which each document is written, making it extremely difficult to use Common Crawl for monolingual applications. We propose a general, highly parallel, multithreaded pipeline to clean and classify Common Crawl by language; we specifically design it so that it runs efficiently on medium to low resource infrastructures where I/O speeds are the main constraint. We develop the pipeline so that it can be easily reapplied to any kind of heterogeneous corpus and so that it can be parameterised to a wide range of infrastructures. We also distribute a 6.3TB version of Common Crawl, filtered, classified by language, shuffled at line level in order to avoid copyright issues, and ready to be used for NLP applications.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
URL: https://hal.inria.fr/hal-02148693/file/Asynchronous_Pipeline_for_Processing_Huge_Corpora_on_Medium_to_Low_Resource_Infrastructures.pdf
https://doi.org/10.14618/IDS-PUB-9021
https://hal.inria.fr/hal-02148693
https://hal.inria.fr/hal-02148693/document
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18
CamemBERT: a Tasty French Language Model
In: https://hal.inria.fr/hal-02445946 ; 2019 (2019)
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19
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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20
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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