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Deep Sequoia corpus - PARSEME-FR corpus - FrSemCor
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2
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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3
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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4
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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5
Controllable Sentence Simplification
In: LREC 2020 - 12th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-02678214 ; LREC 2020 - 12th Language Resources and Evaluation Conference, May 2020, Marseille, France ; http://www.lrec-conf.org/proceedings/lrec2020/index.html (2020)
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6
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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7
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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8
Universal Dependencies 2.7
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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9
Universal Dependencies 2.6
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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10
Controllable Sentence Simplification
In: https://hal.inria.fr/hal-02445874 ; 2019 (2019)
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11
CamemBERT: a Tasty French Language Model
In: https://hal.inria.fr/hal-02445946 ; 2019 (2019)
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12
Challenges of language change and variation: towards an extended treebank of Medieval French
In: TLT 2019 - 18th International Workshop on Treebanks and Linguistic Theories ; https://hal.inria.fr/hal-02272560 ; TLT 2019 - 18th International Workshop on Treebanks and Linguistic Theories, Aug 2019, Paris, France (2019)
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13
Syntactic Parsing versus MWEs: What can fMRI signal tell us
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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14
Annotation tools for syntax
In: Rhapsodie: A Prosodic and Syntactic Treebank for Spoken French ; https://hal.inria.fr/hal-02450311 ; Rhapsodie: A Prosodic and Syntactic Treebank for Spoken French, John Benjamins, 2019, ⟨10.1075/scl.89.08ger⟩ (2019)
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15
Universal Dependencies 2.5
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019
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16
Universal Dependencies 2.4
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019
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17
Reference-less Quality Estimation of Text Simplification Systems
In: 1st Workshop on Automatic Text Adaptation (ATA) ; https://hal.inria.fr/hal-01959054 ; 1st Workshop on Automatic Text Adaptation (ATA), Nov 2018, Tilburg, Netherlands ; https://www.ida.liu.se/~evere22/ATA-18/ (2018)
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18
ELMoLex: Connecting ELMo and Lexicon features for Dependency Parsing
In: CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies ; https://hal.inria.fr/hal-01959045 ; CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, Oct 2018, Brussels, Belgium. ⟨10.18653/v1/K18-2023⟩ (2018)
Abstract: International audience ; In this paper, we present the details of the neural dependency parser and the neu-ral tagger submitted by our team 'ParisNLP' to the CoNLL 2018 Shared Task on parsing from raw text to Universal Dependencies. We augment the deep Biaffine (BiAF) parser (Dozat and Manning, 2016) with novel features to perform competitively: we utilize an indomain version of ELMo features (Peters et al., 2018) which provide context-dependent word representations; we utilize disambiguated, embedded, morphosyntactic features from lexicons (Sagot, 2018), which complements the existing feature set. Henceforth , we call our system 'ELMoLex'. In addition to incorporating character embed-dings, ELMoLex leverage pre-trained word vectors, ELMo and morphosyntactic features (whenever available) to correctly handle rare or unknown words which are prevalent in languages with complex morphology. ELMoLex 1 ranked 11th by Labeled Attachment Score metric (70.64%), Morphology-aware LAS metric (55.74%) and ranked 9th by Bilexical dependency metric (60.70%). In an extrinsic evaluation setup, ELMoLex ranked 7 th for Event Extraction, Negation Resolution tasks and 11th for Opinion Analysis task by F1 score.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
URL: https://hal.inria.fr/hal-01959045/document
https://hal.inria.fr/hal-01959045
https://hal.inria.fr/hal-01959045/file/elmolex-connecting-elmo.pdf
https://doi.org/10.18653/v1/K18-2023
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19
Cheating a Parser to Death: Data-driven Cross-Treebank Annotation Transfer
In: Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ; https://hal.inria.fr/hal-01798801 ; Eleventh International Conference on Language Resources and Evaluation (LREC 2018), May 2018, Miyazaki, Japan (2018)
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20
ANCOR-AS: Enriching the ANCOR Corpus with Syntactic Annotations
In: LREC 2018 - 11th edition of the Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-01744572 ; LREC 2018 - 11th edition of the Language Resources and Evaluation Conference, May 2018, Miyazaki, Japan ; http://lrec2018.lrec-conf.org/en/ (2018)
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