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French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English
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In: ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03629677 ; ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics, May 2022, Dublin, Ireland (2022)
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Establishing a New State-of-the-Art for French Named Entity Recognition
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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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SinNer@Clef-Hipe2020 : Sinful adaptation of SotA models for Named Entity Recognition in French and German
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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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CamemBERT: a Tasty French Language Model
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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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CamemBERT: a Tasty French Language Model
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In: https://hal.inria.fr/hal-02445946 ; 2019 (2019)
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Syntactic Parsing versus MWEs: What can fMRI signal tell us
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In: PARSEME-FR 2019 consortium meeting ; https://hal.inria.fr/hal-02272288 ; PARSEME-FR 2019 consortium meeting, Jun 2019, Blois, France ; https://parsemefr.lis-lab.fr/doku.php?id=meeting-20190613 (2019)
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Adapting a system for Named Entity Recognition and Linking for 19th century French Novels
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In: Digital Humanities 2019 ; https://hal.archives-ouvertes.fr/hal-02187283 ; Digital Humanities 2019, Jul 2019, Utrecht, Netherlands. 2019 ; https://dev.clariah.nl/files/dh2019/boa/0904.html (2019)
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| 8 |
Un corpus libre, évolutif et versionné en entités nommées du français
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In: TALN 2019 - Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-02448590 ; TALN 2019 - Traitement Automatique des Langues Naturelles, Jul 2019, Toulouse, France (2019)
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Adaptation et évaluation de systèmes de reconnaissance et de résolution des entités nommées pour le cas de textes littéraires français du 19ème siècle
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In: Atelier Humanités Numériques Spatialisées (HumaNS’2018) ; https://hal.archives-ouvertes.fr/hal-01925816 ; Atelier Humanités Numériques Spatialisées (HumaNS’2018), Nov 2018, Montpellier, France ; http://psig.huma-num.fr/HumaNS/ (2018)
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| 10 |
Description et modélisation des chaînes de référence. Le projet ANR Democrat (2016-2020) et ses avancées à mi-parcours
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In: Cinquième édition du Salon de l’Innovation en TAL (Traitement Automatique des Langues) et RI (Recherche d’Informations) ; https://hal.archives-ouvertes.fr/hal-01797982 ; Cinquième édition du Salon de l’Innovation en TAL (Traitement Automatique des Langues) et RI (Recherche d’Informations), May 2018, Rennes, France. 2018 (2018)
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Structured Named Entity Recognition by Cascading CRFs
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In: Intelligent Text Processing and Computational Linguistics (CICling) ; https://hal.archives-ouvertes.fr/hal-01579109 ; Intelligent Text Processing and Computational Linguistics (CICling), Apr 2017, Budapest, Hungary (2017)
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Abstract:
International audience ; NER is an important task in NLP, often used as a basis for further treatments. A new challenge has emerged in the last few years: structured named entity recognition, where not only named entities must be identied but also their hierarchical components. In this article, we describe a cascading CRFs approach to address this challenge. It reaches the state of the art while remaining very simple on a structured NER challenge. We then oer an error analysis of our system based on a detailed, yet simple, error classication. 1 Introduction In this paper, we present a linear CRF cascade approach for structured named entity recognition (SNER) on Quaero v1 and v2 corpora, used in the ETAPE evaluation campaigns [10]. Named Entity Recognition (NER) is a fundamental NLP task, its structured variant being increasingly popular. We can overall distinguish two main approaches used to address this task, the rst one being cascading multiple annotations with either the same or dierent methods. In this respect, we can cite [19], which cascaded rules in order to gradually build the structure. We can also cite [5], where a CRF and a PCFG were used, the former giving the leaves while the latter built the rest of the tree. And nally [22], the winner of ETAPE, used one CRF per entity type, for a total of 68 CRFs, and then aligned their annotations. The second approach to annotate tree-structured named entities is to directly retrieve the structure, as was done by [20], who used partial annotation rules for predicting beginnings and ends of entities and then built the tree in one pass. Finally, we can cite [8], who used a tree-CRF to learn nested biomedical entities on the GENIA corpus [14]. Cascading linear CRFs have also been applied for syntactic parsing, as did [25]. At each step, they retrieved chunks and then only kept their respective heads for the next iteration until only one chunk covering the whole sentence was found (with the class sentence). The tree was then reconstructed by simply unfolding chunks at each step. In this paper, we design a new, more general and eective cascade of CRFs adapted to the ETAPE evaluation campaign (sections 2 and 3), evaluate its eciency and analyse its errors (section 4) and nally conclude (section 5).
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Keyword:
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; CRF; machine learning; Quaero; structured named entity recognition
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URL: https://hal.archives-ouvertes.fr/hal-01579109/document
https://hal.archives-ouvertes.fr/hal-01579109/file/2017_CICling_CRFCascade.pdf
https://hal.archives-ouvertes.fr/hal-01579109
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Label-Dependencies Aware Recurrent Neural Networks
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In: Intelligent Text Processing and Computational Linguistics (CICling) ; https://hal.archives-ouvertes.fr/hal-01579071 ; Intelligent Text Processing and Computational Linguistics (CICling), Apr 2017, Budapest, Hungary ; http://www.cicling.org/2017/ (2017)
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| 13 |
Structuration in named entities ; La structuration dans les entités nommées
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In: https://tel.archives-ouvertes.fr/tel-01772268 ; Linguistique. Université Sorbonne Paris Cité, 2017. Français. ⟨NNT : 2017USPCA100⟩ (2017)
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DEMOCRAT : description et modélisation des chaînes de référence ; DEMOCRAT : description et modélisation des chaînes de référence: Outils pour l'annotation de corpus et le traitement automatique
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In: Salon Partenariats Recherche et Industries de la Langue (PAREIL), Vingt-troisième conférence sur le traitement automatique des langues naturelles (TALN 2016) ; https://hal.archives-ouvertes.fr/hal-01384485 ; Salon Partenariats Recherche et Industries de la Langue (PAREIL), Vingt-troisième conférence sur le traitement automatique des langues naturelles (TALN 2016), Jul 2016, Paris, France. 2016 (2016)
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Sequential Patterns of POS Labels Help to Characterize Language Acquisition
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In: DMNLP (ECML/PKDD Workshop) ; https://hal.archives-ouvertes.fr/hal-01140542 ; DMNLP (ECML/PKDD Workshop), 2014, Nancy, France (2014)
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Caractériser l'acquisition d'une langue avec des patrons d'étiquettes morpho-syntaxiques
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In: JADT (JOURNÉE D'ANALYSE DES DOCUMENTS TEXTUELS) ; https://hal.archives-ouvertes.fr/hal-01140342 ; JADT (JOURNÉE D'ANALYSE DES DOCUMENTS TEXTUELS), Jun 2014, PARIS, France (2014)
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| 17 |
Peut-on bien chunker avec de mauvaises étiquettes POS ?
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In: TALN 2014 ; https://hal.archives-ouvertes.fr/hal-01024274 ; TALN 2014, Jul 2014, Marseille, France. pp.125-136 (2014)
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| 18 |
Adapt a Text-Oriented Chunker for Oral Data: How Much Manual Effort is Necessary?
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In: 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL) ; https://hal.archives-ouvertes.fr/hal-01174605 ; 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Oct 2013, Hefei, China (2013)
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Intégrer des connaissances linguistiques dans un CRF : application à l'apprentissage d'un segmenteur-étiqueteur du français
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In: TALN2011 ; TALN ; https://hal.archives-ouvertes.fr/hal-00620923 ; TALN, Jun 2011, Montpellier, France. pp.321 (2011)
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