@inbook {6287, title = {La notion d{\textquoteright}usage dans une linguistique de corpus}, booktitle = {L{\textquoteright}usage de l{\textquoteright}usage}, year = {Soumis}, publisher = {ISTE}, organization = {ISTE}, author = {Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e} and Juliette Thuilier}, editor = {B. Godart and Sandra Laugier} } @article {7482, title = {Assessing the Capacity of Transformer to Abstract Syntactic Representations: A Contrastive Analysis Based on Long-distance Agreement}, journal = {Transactions of the Association for Computational Linguistics}, volume = {11}, year = {2023}, pages = {18-33}, doi = {10.1162/tacl_a_00531}, url = {https://hal.science/hal-03957265}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @article {liAssessingCapacityTransformer2023, title = {Assessing the Capacity of Transformer to Abstract Syntactic Representations: A Contrastive Analysis Based on Long-distance Agreement}, journal = {Transactions of the Association for Computational Linguistics}, volume = {10}, year = {2023}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {crabbe:hal-03880533, title = {Ajout d{\textquoteright}un {\'e}tage d{\textquoteright}analyse syntaxique {\`a} un corpus POS-tagu{\'e} et lemmatis{\'e} de fran{\c c}ais classique}, year = {2022}, address = {Lyon, France}, url = {https://hal.archives-ouvertes.fr/hal-03880533}, author = {Beno{\^\i}t Crabb{\'e} and Falaise, Achille} } @inproceedings {grobol:hal-03736840, title = {BERTrade: Using Contextual Embeddings to Parse Old French}, year = {2022}, month = {Jun}, publisher = {European Language Resources Association}, address = {Marseille, France}, keywords = {Contextual word embeddings, dependency parsing, Old French, Part of Speech Tagging}, url = {https://hal.archives-ouvertes.fr/hal-03736840}, author = {Grobol, Lo{\"\i}c and Regnault, Mathilde and Ortiz Suarez, Pedro and Sagot, Beno{\^\i}t and Romary, Laurent and Beno{\^\i}t Crabb{\'e}} } @inproceedings {grobolBERTradeUsingContextual2022, title = {BERTrade: Using Contextual Embeddings to Parse Old French}, year = {2022}, month = {jun}, pages = {1104{\textendash}1113}, publisher = {European Language Resources Association}, address = {Marseille, France}, abstract = {

The successes of contextual word embeddings learned by training large-scale language models, while remarkable, have mostly occurred for languages where significant amounts of raw texts are available and where annotated data in downstream tasks have a relatively regular spelling. Conversely, it is not yet completely clear if these models are also well suited for lesser-resourced and more irregular languages. We study the case of Old French, which is in the interesting position of having relatively limited amount of available raw text, but enough annotated resources to assess the relevance of contextual word embedding models for downstream NLP tasks. In particular, we use POS-tagging and dependency parsing to evaluate the quality of such models in a large array of configurations, including models trained from scratch from small amounts of raw text and models pre-trained on other languages but fine-tuned on Medieval French data.

}, author = {Grobol, Lo{\"\i}c and Regnault, Mathilde and Ortiz Suarez, Pedro and Sagot, Beno{\^\i}t and Romary, Laurent and Beno{\^\i}t Crabb{\'e}} } @inproceedings {li:halshs-03755082, title = {How Distributed are Distributed Representations? An Observation on the Locality of Syntactic Information in Verb Agreement Tasks}, year = {2022}, month = {May}, pages = {501-507}, publisher = {Association for Computational Linguistics}, address = {Dublin, France}, doi = {10.18653/v1/2022.acl-short.54}, url = {https://halshs.archives-ouvertes.fr/halshs-03755082}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {li:halshs-03755082, title = {How Distributed are Distributed Representations? An Observation on the Locality of Syntactic Information in Verb Agreement Tasks}, year = {2022}, month = {May}, pages = {501-507}, publisher = {Association for Computational Linguistics}, address = {Dublin, France}, doi = {10.18653/v1/2022.acl-short.54}, url = {https://shs.hal.science/halshs-03755082}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {liHowDistributedAre2022a, title = {How Distributed Are Distributed Representations? An Observation on the Locality of Syntactic Information in Verb Agreement Tasks}, year = {2022}, month = {may}, pages = {501{\textendash}507}, publisher = {Association for Computational Linguistics}, address = {Dublin, Ireland}, abstract = {

This work addresses the question of the localization of syntactic information encoded in the transformers representations. We tackle this question from two perspectives, considering the object-past participle agreement in French, by identifying, first, in which part of the sentence and, second, in which part of the representation the syntactic information is encoded. The results of our experiments, using probing, causal analysis and feature selection method, show that syntactic information is encoded locally in a way consistent with the French grammar.

}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {7233, title = {How Distributed are Distributed Representations? An Observation on the Locality of Syntactic Information in Verb Agreement Tasks}, year = {2022}, pages = {501{\textendash}507}, publisher = {Association for Computational Linguistics}, address = {Dublin, Ireland}, abstract = {

This work addresses the question of the localization of syntactic information encoded in the transformers representations. We tackle this question from two perspectives, considering the object-past participle agreement in French, by identifying, first, in which part of the sentence and, second, in which part of the representation the syntactic information is encoded. The results of our experiments, using probing, causal analysis and feature selection method, show that syntactic information is encoded locally in a way consistent with the French grammar.

}, doi = {10.18653/v1/2022.acl-short.54}, url = {https://aclanthology.org/2022.acl-short.54}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {beauImpactLexicalGrammatical2022a, title = {The Impact of Lexical and Grammatical Processing on Generating Code from Natural Language}, year = {2022}, month = {05-2022}, pages = {2204{\textendash}2214}, publisher = {Association for Computational Linguistics}, address = {Dublin, Ireland}, abstract = {

Considering the seq2seq architecture of Yin and Neubig (2018) for natural language to code translation, we identify four key components of importance: grammatical constraints, lexical preprocessing, input representations, and copy mechanisms. To study the impact of these components, we use a state-of-the-art architecture that relies on BERT encoder and a grammar-based decoder for which a formalization is provided. The paper highlights the importance of the lexical substitution component in the current natural language to code systems.

}, author = {Beau, Nathana{\"e}l and Beno{\^\i}t Crabb{\'e}} } @inbook {7401, title = {La notion d{\textquoteright}usage en linguistique : du corpus {\`a} l{\textquoteright}exp{\'e}rimental}, booktitle = {Les usages de l{\textquoteright}usage}, year = {2022}, publisher = {ISTE}, organization = {ISTE}, edition = {B{\'e}atrce Godart, Sandra Laugier}, chapter = {11}, address = {London}, isbn = {9781784058197}, author = {Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e} and Juliette Thuilier} } @inproceedings {li:hal-03701480, title = {Les repr{\'e}sentations distribu{\'e}es sont-elles vraiment distribu{\'e}es ? Observations sur la localisation de l{\textquoteright}information syntaxique dans les t{\^a}ches d{\textquoteright}accord du verbe en fran{\c c}ais}, year = {2022}, pages = {384-391}, publisher = {ATALA}, address = {Avignon, France}, abstract = {

Ce travail aborde la question de la localisation de l\&$\#$39;information syntaxique qui est encod\ée dans les repr\ésentations de transformers. En consid\érant la t\âche d\&$\#$39;accord objet-participe pass\é en fran\çais, les r\ésultats de nos sondes linguistiques montrent que les informations n\écessaires pour accomplir la t\âche sont encod\ées d\&$\#$39;une mani\ère locale dans les repr\ésentations de mots entre l\&$\#$39;ant\éc\édent du pronom relatif objet et le participe pass\é cible. En plus, notre analyse causale montre que le mod\èle s\&$\#$39;appuie essentiellement sur les \él\éments linguistiquement motiv\és (i.e. ant\éc\édent et pronom relatif) pour pr\édire le nombre du participe pass\é.

}, keywords = {analyse causale., information syntaxique, repr{\'e}sentation distribu{\'e}e, transformers}, url = {https://hal.archives-ouvertes.fr/hal-03701480}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}}, editor = {Est{\`e}ve, Yannick and Jim{\'e}nez, Tania and Parcollet, Titouan and Zanon Boito, Marcely} } @inproceedings {simoulinUnifyingParsingTreeStructured2022, title = {Unifying Parsing and Tree-Structured Models for Generating Sentence Semantic Representations}, year = {2022}, pages = {267{\textendash}276}, publisher = {Association for Computational Linguistics}, address = {Hybrid: Seattle, Washington + Online}, abstract = {

We introduce a novel tree-based model that learns its composition function together with its structure. The architecture produces sentence embeddings by composing words according to an induced syntactic tree. The parsing and the composition functions are explicitly connected and, therefore, learned jointly. As a result, the sentence embedding is computed according to an interpretable linguistic pattern and may be used on any downstream task. We evaluate our encoder on downstream tasks, and we observe that it outperforms tree-based models relying on external parsers. In some configurations, it is even competitive with Bert base model. Our model is capable of supporting multiple parser architectures. We exploit this property to conduct an ablation study by comparing different parser initializations. We explore to which extent the trees produced by our model compare with linguistic structures and how this initialization impacts downstream performances. We empirically observe that downstream supervision troubles producing stable parses and preserving linguistically relevant structures.

}, author = {Simoulin, Antoine and Beno{\^\i}t Crabb{\'e}} } @inproceedings {grobolAnalyseDependancesFrancais2021, title = {Analyse en d{\'e}pendances du fran{\c c}ais avec des plongements contextualis{\'e}s (French dependency parsing with contextualized embeddings)}, year = {2021}, pages = {106{\textendash}114}, publisher = {ATALA}, address = {Lille, France}, abstract = {Cet article pr{\'e}sente un analyseur syntaxique en d{\'e}pendances pour le fran{\c c}ais qui se compare favorablement {\`a} l{\textquoteright}{\'e}tat de l{\textquoteright}art sur la plupart des corpus de r{\'e}f{\'e}rence. L{\textquoteright}analyseur s{\textquoteright}appuie sur de riches repr{\'e}sentations lexicales issues notamment de BERT et de FASTTEXT. On remarque que les repr{\'e}sentations lexicales produites par FLAUBERT ont un caract{\`e}re auto-suffisant pour r{\'e}aliser la t{\^a}che d{\textquoteright}analyse syntaxique de mani{\`e}re optimale.}, author = {Grobol, Lo{\"\i}c and Beno{\^\i}t Crabb{\'e}} } @inproceedings {grobol:hal-03265893, title = {Analyse en d{\'e}pendances du fran{\c c}ais avec des plongements contextualis{\'e}s}, year = {2021}, pages = {106-114}, publisher = {ATALA}, address = {Lille, France}, keywords = {Analyse syntaxique en d{\'e}pendances du fran{\c c}ais, BERT, FastText.}, url = {https://hal.archives-ouvertes.fr/hal-03265893}, author = {Grobol, Lo{\"\i}c and Beno{\^\i}t Crabb{\'e}}, editor = {Denis, Pascal and Grabar, Natalia and Fraisse, Amel and Cardon, R{\'e}mi and Jacquemin, Bernard and Kergosien, Eric and Balvet, Antonio} } @inproceedings {grobol:hal-03223424, title = {Analyse en d{\'e}pendances du fran{\c c}ais avec des plongements contextualis{\'e}s}, year = {2021}, address = {Lille (virtuel), France}, keywords = {BERT, dependency parsing, FastText, Parsing French}, url = {https://hal.archives-ouvertes.fr/hal-03223424}, author = {Grobol, Lo{\"\i}c and Beno{\^\i}t Crabb{\'e}} } @inproceedings {li:halshs-03755089, title = {Are Transformers a Modern Version of ELIZA? Observations on French Object Verb Agreement}, year = {2021}, month = {Nov}, address = {Punta Cana, Dominican Republic}, doi = {10.18653/v1/2021.emnlp-main.377}, url = {https://shs.hal.science/halshs-03755089}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {liAreTransformersModern2021, title = {Are Transformers a Modern Version of ELIZA? Observations on French Object Verb Agreement}, year = {2021}, month = {nov}, pages = {4599{\textendash}4610}, publisher = {Association for Computational Linguistics}, address = {Online and Punta Cana, Dominican Republic}, abstract = {

Many recent works have demonstrated that unsupervised sentence representations of neural networks encode syntactic information by observing that neural language models are able to predict the agreement between a verb and its subject. We take a critical look at this line of research by showing that it is possible to achieve high accuracy on this agreement task with simple surface heuristics, indicating a possible flaw in our assessment of neural networks\&$\#$39; syntactic ability. Our fine-grained analyses of results on the long-range French object-verb agreement show that contrary to LSTMs, Transformers are able to capture a non-trivial amount of grammatical structure.

}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {7231, title = {Are Transformers a Modern Version of ELIZA? Observations on French Object Verb Agreement}, year = {2021}, pages = {4599{\textendash}4610}, publisher = {Association for Computational Linguistics}, address = {Online and Punta Cana, Dominican Republic}, abstract = {

Many recent works have demonstrated that unsupervised sentence representations of neural networks encode syntactic information by observing that neural language models are able to predict the agreement between a verb and its subject. We take a critical look at this line of research by showing that it is possible to achieve high accuracy on this agreement task with simple surface heuristics, indicating a possible flaw in our assessment of neural networks\&$\#$39; syntactic ability. Our fine-grained analyses of results on the long-range French object-verb agreement show that contrary to LSTMs, Transformers are able to capture a non-trivial amount of grammatical structure.

}, doi = {10.18653/v1/2021.emnlp-main.377}, url = {https://aclanthology.org/2021.emnlp-main.377}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {li:halshs-03755089, title = {Are Transformers a Modern Version of ELIZA? Observations on French Object Verb Agreement}, year = {2021}, address = {Punta Cana, Dominican Republic}, doi = {10.18653/v1/2021.emnlp-main.377}, url = {https://halshs.archives-ouvertes.fr/halshs-03755089}, author = {Li, Bingzhi and Wisniewski, Guillaume and Beno{\^\i}t Crabb{\'e}} } @inproceedings {simoulin:hal-03601428, title = {Contrasting distinct structured views to learn sentence embeddings}, year = {2021}, address = {Kyiv, Ukraine}, url = {https://hal.archives-ouvertes.fr/hal-03601428}, author = {Simoulin, Antoine and Beno{\^\i}t Crabb{\'e}} } @inproceedings {simoulinContrastingDistinctStructured2021, title = {Contrasting Distinct Structured Views to Learn Sentence Embeddings}, year = {2021}, pages = {71{\textendash}79}, publisher = {Association for Computational Linguistics}, address = {Online}, abstract = {We propose a self-supervised method that builds sentence embeddings from the combination of diverse explicit syntactic structures of a sentence. We assume structure is crucial to building consistent representations as we expect sentence meaning to be a function of both syntax and semantic aspects. In this perspective, we hypothesize that some linguistic representations might be better adapted given the considered task or sentence. We, therefore, propose to learn individual representation functions for different syntactic frameworks jointly. Again, by hypothesis, all such functions should encode similar semantic information differently and consequently, be complementary for building better sentential semantic embeddings. To assess such hypothesis, we propose an original contrastive multi-view framework that induces an explicit interaction between models during the training phase. We make experiments combining various structures such as dependency, constituency, or sequential schemes. Our results outperform comparable methods on several tasks from standard sentence embedding benchmarks.}, author = {Simoulin, Antoine and Beno{\^\i}t Crabb{\'e}} } @article {7399, title = {French word order : the role of animacy}, journal = {Glossa: a journal of general linguistics}, volume = {6}, year = {2021}, pages = {1-55}, chapter = {1}, abstract = {

A major goal of the quantitative study of syntax has been to identify factors that have predictive power on speaker choices in the face of word-order or valence alternations (e.g. Arnold et al. 2000; Bresnan et al. 2007; Bresnan \& Ford 2010; Bader \& H\äussler 2010). In this paper, we study the role of animacy on the order of constituents in French. Animacy has been shown to affect sentence production in other languages, either directly (Feleki \& Branigan 1999; Kempen \& Harbusch 2004; Tanaka et al. 2011) or indirectly through grammatical role assignment (McDonald et al. 1993). Corpus studies however, have failed to find such an effect in French (Thuilier 2012a; Thuilier et al. 2014). Using a sentence recall task, we examined whether animacy has an impact on linear ordering or on grammatical function assignment. While we do find evidence for a role of animacy in the choice between active and passive voice, we do not find a preference to place animate arguments first with ditransitive verbs nor with nominal coordinations. While these findings tend to support the indirect hypothesis (McDonald et al. 1993; Kempen \& Harbusch 2004), we also find what may look like an anti-animacy effect: inanimate direct objects tend to precede animate indirect objects. We propose that canonical mappings between syntactic function and semantic role play a role in putting (inanimate theme) direct objects before (animate recipient) indirect objects, thus overriding the animacy first tendency in French.

}, doi = {https://doi.org/10.5334/gjgl.1155}, url = {https://www.glossa-journal.org/article/id/5435/}, author = {Juliette Thuilier and Grant, Margaret and Beno{\^\i}t Crabb{\'e} and Anne Abeill{\'e}} } @inproceedings {simoulinHowManyLayers2021, title = {How Many Layers and Why? An Analysis of the Model Depth in Transformers}, year = {2021}, pages = {221{\textendash}228}, publisher = {Association for Computational Linguistics}, address = {Online}, abstract = {

In this study, we investigate the role of the multiple layers in deep transformer models. We design a variant of Albert that dynamically adapts the number of layers for each token of the input. The key specificity of Albert is that weights are tied across layers. Therefore, the stack of encoder layers iteratively repeats the application of the same transformation function on the input. We interpret the repetition of this application as an iterative process where the token contextualized representations are progressively refined. We analyze this process at the token level during pre-training, fine-tuning, and inference. We show that tokens do not require the same amount of iterations and that difficult or crucial tokens for the task are subject to more iterations.

}, author = {Simoulin, Antoine and Beno{\^\i}t Crabb{\'e}} } @inproceedings {simoulin:hal-03601412, title = {How Many Layers and Why? An Analysis of the Model Depth in Transformers}, year = {2021}, address = {Bangkok, Thailand}, url = {https://hal.archives-ouvertes.fr/hal-03601412}, author = {Simoulin, Antoine and Beno{\^\i}t Crabb{\'e}} } @inproceedings {simoulin:hal-03265900, title = {Un mod{\`e}le Transformer G{\'e}n{\'e}ratif Pr{\'e}-entrain{\'e} pour le ______ fran{\c c}ais}, year = {2021}, pages = {246-255}, publisher = {ATALA}, address = {Lille, France}, keywords = {fran{\c c}ais., G{\'e}n{\'e}ratif, GPT, Pr{\'e}-entra{\^\i}n{\'e}, Transformer}, url = {https://hal.archives-ouvertes.fr/hal-03265900}, author = {Simoulin, Antoine and Beno{\^\i}t Crabb{\'e}}, editor = {Denis, Pascal and Grabar, Natalia and Fraisse, Amel and Cardon, R{\'e}mi and Jacquemin, Bernard and Kergosien, Eric and Balvet, Antonio} } @inproceedings {simoulinModeleTransformerGeneratif2021, title = {Un mod{\`e}le Transformer G{\'e}n{\'e}ratif Pr{\'e}-entrain{\'e} pour le fran{\c c}ais Generative Pre-trained Transformer in French (We introduce a French adaptation from the well-known GPT model)}, year = {2021}, month = {jun}, pages = {246{\textendash}255}, publisher = {ATALA}, address = {Lille, France}, abstract = {

Nous proposons une adaptation en fran\çais du fameux mod\èle Generative Pre-trained Transformer (GPT). Ce dernier appartient \à la cat\égorie des architectures transformers qui ont significativement transform\é les m\éthodes de traitement automatique du langage. Ces architectures sont en particulier pr\é-entra\în\ées sur des t\âches auto-supervis\ées et sont ainsi sp\écifiques pour une langue donn\ée. Si certaines sont disponibles en fran\çais, la plupart se d\éclinent avant tout en anglais. GPT est particuli\èrement efficace pour les t\âches de g\én\ération de texte. Par ailleurs, il est possible de l\&$\#$39;appliquer \à de nombreux cas d\&$\#$39;usages. Ses propri\ét\és g\én\ératives singuli\ères permettent de l\&$\#$39;utiliser dans des conditions originales comme l\&$\#$39;apprentissage sans exemple qui ne suppose aucune mise \à jour des poids du mod\èle, ou modification de l\&$\#$39;architecture.

}, author = {Simoulin, Antoine and Beno{\^\i}t Crabb{\'e}} } @article {thuilierWordOrderFrench2021, title = {Word Order in {French: The Role of Animacy}, journal = {Glossa: a journal of general linguistics}, volume = {6}, number = {1}, year = {2021}, month = {apr}, publisher = {Open Library of Humanities}, abstract = {A major goal of the quantitative study of syntax has been to identify factors that have predictive power on speaker choices in the face of word-order or valence alternations (e.g. Arnold et al. 2000; Bresnan et al. 2007; Bresnan \& Ford 2010; Bader \& H{\"a}ussler 2010). In this paper, we study the role of animacy on the order of constituents in French. Animacy has been shown to affect sentence production in other languages, either directly (Feleki \& Branigan 1999; Kempen \& Harbusch 2004; Tanaka et al. 2011) or indirectly through grammatical role assignment (McDonald et al. 1993). Corpus studies however, have failed to find such an effect in French (Thuilier 2012a; Thuilier et al. 2014). Using a sentence recall task, we examined whether animacy has an impact on linear ordering or on grammatical function assignment. While we do find evidence for a role of animacy in the choice between active and passive voice, we do not find a preference to place animate arguments first with ditransitive verbs nor with nominal coordinations. While these findings tend to support the indirect hypothesis (McDonald et al. 1993; Kempen \& Harbusch 2004), we also find what may look like an anti-animacy effect: inanimate direct objects tend to precede animate indirect objects. We propose that canonical mappings between syntactic function and semantic role play a role in putting (inanimate theme) direct objects before (animate recipient) indirect objects, thus overriding the animacy first tendency in French.}, author = {Juliette Thuilier and Grant, Margaret and Beno{\^\i}t Crabb{\'e} and Anne Abeill{\'e}} } @inproceedings {leFlauBERTModelesLangue2020, title = {FlauBERT : des mod{\`e}les de langue contextualis{\'e}s pr{\'e}-entra{\^\i}n{\'e}s pour le fran{\c c}ais (FlauBERT : Unsupervised Language Model Pre-training for French)}, year = {2020}, month = {jun}, pages = {268{\textendash}278}, publisher = {ATALA et AFCP}, address = {Nancy, France}, abstract = {Les mod{\`e}les de langue pr{\'e}-entra{\^\i}n{\'e}s sont d{\'e}sormais indispensables pour obtenir des r{\'e}sultats {\`a} l{\textquoteright}{\'e}tat-de-l{\textquoteright}art dans de nombreuses t{\^a}ches du TALN. Tirant avantage de l{\textquoteright}{\'e}norme quantit{\'e} de textes bruts disponibles, ils permettent d{\textquoteright}extraire des repr{\'e}sentations continues des mots, contextualis{\'e}es au niveau de la phrase. L{\textquoteright}efficacit{\'e} de ces repr{\'e}sentations pour r{\'e}soudre plusieurs t{\^a}ches de TALN a {\'e}t{\'e} d{\'e}montr{\'e}e r{\'e}cemment pour l{\textquoteright}anglais. Dans cet article, nous pr{\'e}sentons et partageons FlauBERT, un ensemble de mod{\`e}les appris sur un corpus fran{\c c}ais h{\'e}t{\'e}rog{\`e}ne et de taille importante. Des mod{\`e}les de complexit{\'e} diff{\'e}rente sont entra{\^\i}n{\'e}s {\`a} l{\textquoteright}aide du nouveau supercalculateur Jean Zay du CNRS. Nous {\'e}valuons nos mod{\`e}les de langue sur diverses t{\^a}ches en fran{\c c}ais (classification de textes, paraphrase, inf{\'e}rence en langage naturel, analyse syntaxique, d{\'e}sambigu{\"\i}sation automatique) et montrons qu{\textquoteright}ils surpassent souvent les autres approches sur le r{\'e}f{\'e}rentiel d{\textquoteright}{\'e}valuation FLUE {\'e}galement pr{\'e}sent{\'e} ici.}, author = {Le, Hang and Vial, Lo{\"\i}c and Frej, Jibril and Segonne, Vincent and Coavoux, Maximin and Lecouteux, Benjamin and Allauzen, Alexandre and Beno{\^\i}t Crabb{\'e} and Besacier, Laurent and Schwab, Didier} } @inproceedings {leFlauBERTUnsupervisedLanguage2020, title = {FlauBERT: Unsupervised Language Model Pre-training for French}, year = {2020}, month = {may}, pages = {2479{\textendash}2490}, publisher = {European Language Resources Association}, address = {Marseille, France}, abstract = {

Language models have become a key step to achieve state-of-the art results in many different Natural Language Processing (NLP) tasks. Leveraging the huge amount of unlabeled texts nowadays available, they provide an efficient way to pre-train continuous word representations that can be fine-tuned for a downstream task, along with their contextualization at the sentence level. This has been widely demonstrated for English using contextualized representations (Dai and Le, 2015; Peters et al., 2018; Howard and Ruder, 2018; Radford et al., 2018; Devlin et al., 2019; Yang et al., 2019b). In this paper, we introduce and share FlauBERT, a model learned on a very large and heterogeneous French corpus. Models of different sizes are trained using the new CNRS (French National Centre for Scientific Research) Jean Zay supercomputer. We apply our French language models to diverse NLP tasks (text classification, paraphrasing, natural language inference, parsing, word sense disambiguation) and show that most of the time they outperform other pre-training approaches. Different versions of FlauBERT as well as a unified evaluation protocol for the downstream tasks, called FLUE (French Language Understanding Evaluation), are shared to the research community for further reproducible experiments in French NLP.

}, isbn = {979-10-95546-34-4}, author = {Le, Hang and Vial, Lo{\"\i}c and Frej, Jibril and Segonne, Vincent and Coavoux, Maximin and Lecouteux, Benjamin and Allauzen, Alexandre and Beno{\^\i}t Crabb{\'e} and Besacier, Laurent and Schwab, Didier} } @inproceedings {barqueFrSemCorAnnotatingFrench2020, title = {FrSemCor: Annotating a French Corpus with Supersenses}, year = {2020}, pages = {5912{\textendash}5918}, publisher = {European Language Resources Association}, address = {Marseille, France}, abstract = {

French, as many languages, lacks semantically annotated corpus data. Our aim is to provide the linguistic and NLP research communities with a gold standard sense-annotated corpus of French, using WordNet Unique Beginners as semantic tags, thus allowing for interoperability. In this paper, we report on the first phase of the project, which focused on the annotation of common nouns. The resulting dataset consists of more than 12,000 French noun occurrences which were annotated in double blind and adjudicated according to a carefully redefined set of supersenses. The resource is released online under a Creative Commons Licence.

}, isbn = {979-10-95546-34-4}, author = {Lucie Barque and Richard Huyghe and Delphine Tribout and Marie Candito and Beno{\^\i}t Crabb{\'e} and Segonne, Vincent} } @article {simonenkoAgreementSyncretisationLoss2019, title = {Agreement Syncretisation and the Loss of Null Subjects : Quantificational Models for {Medieval French}, journal = {Language Variation and Change}, volume = {31}, number = {3}, year = {2019}, pages = {275{\textendash}301}, abstract = {This paper examines the nature of the dependency between the availability of null subjects and the {\textquoteleft}{\textquoteleft}richness{\textquoteright}{\textquoteright} of verbal subject agreement, known as Taraldsen{\textquoteright}s Generalisation (Adams, 1987; Rizzi, 1986; Roberts, 2014; Taraldsen, 1980). We present a corpus-based quantitative model of the syncretization of verbal subject agreement spanning the Medieval French period and evaluate two hypotheses relating agreement and null subjects: one relating the two as reflexes of the same grammatical property and a variational learning-based hypothesis whereby phonology-driven syncretization of agreement marking creates a learning bias against the null subject grammar. We show that only the latter approach has the potential to reconcile the intuition behind Taraldsen{\textquoteright}s Generalisation with the fact that it has proven nontrivial to formulate the notion of agreement richness in a way that would unequivocally predict whether a language has null subjects.}, author = {Simonenko, Alexandra and Beno{\^\i}t Crabb{\'e} and Sophie Pr{\'e}vost} } @article {coavouxUnlexicalizedTransitionbasedDiscontinuous2019a, title = {Unlexicalized Transition-based Discontinuous Constituency Parsing}, journal = {Transactions of the Association for Computational Linguistics}, volume = {7}, year = {2019}, pages = {73{\textendash}89}, abstract = {

Lexicalized parsing models are based on the assumptions that (i) constituents are organized around a lexical head and (ii) bilexical statistics are crucial to solve ambiguities. In this paper, we introduce an unlexicalized transition-based parser for discontinuous constituency structures, based on a structure-label transition system and a bi-LSTM scoring system. We compare it with lexicalized parsing models in order to address the question of lexicalization in the context of discontinuous constituency parsing. Our experiments show that unlexicalized models systematically achieve higher results than lexicalized models, and provide additional empirical evidence that lexicalization is not necessary to achieve strong parsing results. Our best unlexicalized model sets a new state of the art on English and German discontinuous constituency treebanks. We further provide a per-phenomenon analysis of its errors on discontinuous constituents.

}, author = {Coavoux, Maximin and Beno{\^\i}t Crabb{\'e} and Cohen, Shay B.} } @inproceedings {segonne:hal-02436417, title = {Using Wiktionary as a resource for WSD : the case of French verbs}, year = {2019}, pages = {259-270}, publisher = {Association for Computational Linguistics}, address = {Gothenburg, Sweden}, doi = {10.18653/v1/W19-0422}, url = {https://hal.archives-ouvertes.fr/hal-02436417}, author = {Segonne, Vincent and Marie Candito and Beno{\^\i}t Crabb{\'e}} } @inproceedings {segonneUsingWiktionaryResource2019, title = {Using Wiktionary as a Resource for WSD : The Case of French Verbs}, year = {2019}, month = {may}, pages = {259{\textendash}270}, publisher = {Association for Computational Linguistics}, address = {Gothenburg, Sweden}, abstract = {

As opposed to word sense induction, word sense disambiguation (WSD) has the advantage of us-ing interpretable senses, but requires annotated data, which are quite rare for most languages except English (Miller et al. 1993; Fellbaum, 1998). In this paper, we investigate which strategy to adopt to achieve WSD for languages lacking data that was annotated specifically for the task, focusing on the particular case of verb disambiguation in French. We first study the usability of Eurosense (Bovi et al. 2017) , a multilingual corpus extracted from Europarl (Kohen, 2005) and automatically annotated with BabelNet (Navigli and Ponzetto, 2010) senses. Such a resource opened up the way to supervised and semi-supervised WSD for resourceless languages like French. While this perspective looked promising, our evaluation on French verbs was inconclusive and showed the annotated senses\&$\#$39; quality was not sufficient for supervised WSD on French verbs. Instead, we propose to use Wiktionary, a collaboratively edited, multilingual online dictionary, as a resource for WSD. Wiktionary provides both sense inventory and manually sense tagged examples which can be used to train supervised and semi-supervised WSD systems. Yet, because senses\&$\#$39; distribution differ in lexicographic examples found in Wiktionary with respect to natural text, we then focus on studying the impact on WSD of the training data size and senses\&$\#$39; distribution. Using state-of-the art semi-supervised systems, we report experiments of Wiktionary-based WSD for French verbs, evaluated on FrenchSemEval (FSE), a new dataset of French verbs manually annotated with wiktionary senses.

}, author = {Segonne, Vincent and Marie Candito and Beno{\^\i}t Crabb{\'e}} } @inproceedings {crabbeVariableBeamSearch2019a, title = {Variable Beam Search for Generative Neural Parsing and Its Relevance for the Analysis of Neuro-Imaging Signal}, year = {2019}, pages = {1150{\textendash}1160}, publisher = {Association for Computational Linguistics}, address = {Hong Kong, China}, abstract = {

This paper describes a method of variable beam size inference for Recurrent Neural Network Grammar (rnng) by drawing inspiration from sequential Monte-Carlo methods such as particle filtering. The paper studies the relevance of such methods for speeding up the computations of direct generative parsing for rnng. But it also studies the potential cognitive interpretation of the underlying representations built by the search method (beam activity) through analysis of neuro-imaging signal.

}, author = {Beno{\^\i}t Crabb{\'e} and Fabre, Murielle and Christophe Pallier} } @article {simonenkoTextFormGrammatical2018, title = {Text Form and Grammatical Changes in Medieval French : A Treebank-Based Diachronic Study}, journal = {Diachronica}, volume = {35}, number = {3}, year = {2018}, pages = {393{\textendash}428}, abstract = {

This paper presents a treebank-based study of the effect the text form (prose vs. verse) has on the course of two grammatical changes in Medieval French: the loss of null subjects and the loss of OV word order. By means of statistical analysis, we demonstrate that naive estimates of the spread of overt subjects and VO orders give the impression that there is a significant difference between the rates of development in prose vs. verse. By contrast, estimates based on an abstract grammar competition model which distinguishes between grammar-ambiguous surface forms (overt personal subjects, null subjects in coordination contexts) and grammar-unambiguous surface forms (overt expletive subjects, null subjects in non-coordination contexts) show prose-verse parallelism, prose having an earlier change onset, in line with traditional intuitions. At a more general level, these results suggest that the product of the interaction of a particular grammar with universal pragmatic laws is constant, which can be observed if the factors responsible for variation in grammatical choices are controlled for.

}, author = {Simonenko, Alexandra and Beno{\^\i}t Crabb{\'e} and Sophie Pr{\'e}vost} } @inproceedings {5627, title = {Incremental Discontinuous Phrase Structure Parsing with the GAP Transition}, year = {2017}, month = {April}, pages = {1259{\textendash}1270}, publisher = {Association for Computational Linguistics}, address = {Valencia, Spain}, abstract = {

This article introduces a novel transition system for discontinuous lexicalized constituent parsing called SR-GAP. It is an extension of the shift-reduce algorithm with an additional gap transition. Evaluation on two German treebanks shows that SR-GAP outperforms the previous best transition-based discontinuous parser (Maier, 2015) by a large margin (it is notably twice as accurate on the prediction of discontinuous constituents), and is competitive with the state of the art (Fern\ández-Gonz\ález and Martins, 2015). As a side contribution, we adapt span features (Hall et al., 2014) to discontinuous parsing.

}, url = {http://www.aclweb.org/anthology/E17-1118}, author = {Coavoux, Maximin and Beno{\^\i}t Crabb{\'e}} } @inproceedings {5628, title = {Multilingual Lexicalized Constituency Parsing with Word-Level Auxiliary Tasks}, year = {2017}, month = {April}, pages = {331{\textendash}336}, publisher = {Association for Computational Linguistics}, address = {Valencia, Spain}, abstract = {

We introduce a constituency parser based on a bi-LSTM encoder adapted from re- cent work (Cross and Huang, 2016b; Kiperwasser and Goldberg, 2016), which can incorporate a lower level character bi- LSTM (Ballesteros et al., 2015; Plank et al., 2016). We model two important in- terfaces of constituency parsing with aux- iliary tasks supervised at the word level: (i) part-of-speech (POS) and morpholog- ical tagging, (ii) functional label predic- tion. On the SPMRL dataset, our parser obtains above state-of-the-art results on constituency parsing without requiring ei- ther predicted POS or morphological tags, and outputs labelled dependency trees.

}, url = {http://www.aclweb.org/anthology/E17-2053}, author = {Coavoux, Maximin and Beno{\^\i}t Crabb{\'e}} } @inproceedings {bawden:hal-01391743, title = {Boosting for Efficient Model Selection for Syntactic Parsing}, year = {2016}, pages = {1-11}, address = {Osaka, Japan}, url = {https://hal.inria.fr/hal-01391743}, author = {Bawden, Rachel and Beno{\^\i}t Crabb{\'e}} } @conference {simonenko:hal-01365263, title = {Effects of literary form on grammatical changes: A treebank study}, year = {2016}, address = {Naples, Italy}, url = {https://hal.inria.fr/hal-01365263}, author = {Simonenko, Alexandra and Beno{\^\i}t Crabb{\'e} and Sophie Pr{\'e}vost} } @booklet {danlos:hal-01392829, title = {Natural Language Processing, 60 years after the Chomsky-Sch{\"u}tzenberger hierarchy}, year = {2016}, publisher = {{Robert Cori and Dominique Perrin}}, keywords = {Formal grammars, Language hierarchy}, url = {https://hal.inria.fr/hal-01392829}, author = {Danlos, Laurence and Beno{\^\i}t Crabb{\'e}} } @inproceedings {coavoux:hal-01353734, title = {{Neural Greedy Constituent Parsing with Dynamic Oracles}}, year = {2016}, address = {Berlin, Germany}, keywords = {NLP, parsing}, url = {https://hal.inria.fr/hal-01353734}, author = {Coavoux, Maximin and Beno{\^\i}t Crabb{\'e}} } @inproceedings {5630, title = {Neural Greedy Constituent Parsing with Dynamic Oracles}, year = {2016}, month = {August}, pages = {172{\textendash}182}, publisher = {Association for Computational Linguistics}, address = {Berlin, Germany}, url = {http://www.aclweb.org/anthology/P16-1017}, author = {Coavoux, Maximin and Beno{\^\i}t Crabb{\'e}} } @article {5632, title = {Pr{\'e}diction structur{\'e}e pour l{\textquoteright}analyse syntaxique en constituants par transitions : mod{\`e}les denses et mod{\`e}les creux}, journal = {Traitement Automatique des Langues}, volume = {57}, year = {2016}, url = {https://hal.inria.fr/hal-01365252}, author = {Coavoux, Maximin and Beno{\^\i}t Crabb{\'e}} } @conference {simonenko:hal-01353738, title = {{Quantificational dimension of Taraldsen{\textquoteright}s Generalisation}}, year = {2016}, address = {Ghent, Belgium}, url = {https://hal.inria.fr/hal-01353738}, author = {Simonenko, Alexandra and Beno{\^\i}t Crabb{\'e} and Sophie Pr{\'e}vost} } @inproceedings {simonenko:hal-01353736, title = {Taraldsen{\textquoteright}s Generalisation in Medieval French}, year = {2016}, address = {Ghent, Belgium}, url = {https://hal.inria.fr/hal-01353736}, author = {Simonenko, Alexandra and Beno{\^\i}t Crabb{\'e} and Sophie Pr{\'e}vost} } @article {gutman:hal-01105141, title = {Bootstrapping the Syntactic Bootstrapper: Probabilistic Labeling of Prosodic Phrases}, journal = {{Language Acquisition}}, volume = {22}, number = {3}, year = {2015}, pages = {25}, publisher = {{Taylor \& Francis (Routledge)}}, doi = {10.1080/10489223.2014.971956}, url = {https://hal.inria.fr/hal-01105141}, author = {Gutman, Ariel and Dautriche, Isabelle and Beno{\^\i}t Crabb{\'e} and Anne, Christophe} } @inproceedings {5631, title = {Comparaison d{\textquoteright}architectures neuronales pour l{\textquoteright}analyse syntaxique en constituants}, year = {2015}, month = {June}, pages = {293{\textendash}304}, publisher = {Association pour le Traitement Automatique des Langues}, address = {Caen, France}, url = {http://www.atala.org/taln_archives/TALN/TALN-2015/taln-2015-long-025}, author = {Coavoux, Maximin and Beno{\^\i}t Crabb{\'e}} } @inproceedings {coavoux:hal-01174613, title = {{Comparaison d{\textquoteright}architectures neuronales pour l{\textquoteright}analyse syntaxique en constituants}}, year = {2015}, address = {Caen, France}, keywords = {Analyse syntaxique en constituants lexicalis{\'e}e, plongements lexicaux, r{\'e}seaux de neurones}, url = {https://hal.inria.fr/hal-01174613}, author = {Coavoux, Maximin and Beno{\^\i}t Crabb{\'e}} } @inproceedings {gulordava:hal-01174617, title = {{Dependency length minimisation effects in short spans: a large-scale analysis of adjective placement in complex noun phrases}}, year = {2015}, month = {Jul}, address = {Beijing, China}, url = {https://hal.inria.fr/hal-01174617}, author = {Gulordava, Kristina and Merlo, Paola and Beno{\^\i}t Crabb{\'e}} } @inproceedings {simonenko:hal-01240245, title = {{Morphological triggers of syntactic changes: Treebank-based Information Theoretic approach}}, year = {2015}, month = {Dec}, address = {Varsovie, Poland}, keywords = {corpus-based modelling, declension, Diachrony of French, Subject expression, word order}, url = {https://hal.inria.fr/hal-01240245}, author = {Simonenko, Alexandra and Beno{\^\i}t Crabb{\'e} and Sophie Pr{\'e}vost}, editor = {Markus Dickinson and Erhard Hinrichs and Agnieszka Patejuk and Adam Przepi{\'o}rkowski} } @inproceedings {crabbe:hal-01186018, title = {{Multilingual discriminative lexicalized parsing}}, year = {2015}, address = {Lisbon, Portugal}, url = {https://hal.inria.fr/hal-01186018}, author = {Beno{\^\i}t Crabb{\'e}} } @inbook {6639, title = {Ordering preferences for postverbal complements }, booktitle = {Ecological and Data-Driven Perspectives in French Language Studies}, year = {2015}, pages = {77-104}, edition = {Tyne Henri, Andr{\'e} Virgine, Benzitoun Christophe}, author = {Anne Abeill{\'e} and Juliette Thuilier and Beno{\^\i}t Crabb{\'e}} } @inbook {4895, title = {Ordering preferences for postverbal complements}, booktitle = {Ecological and Data-Driven Perspectives in French Language Studies}, year = {2015}, publisher = {Cambridge U P}, organization = {Cambridge U P}, edition = {Tyne}, author = {Juliette Thuilier and Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e}} } @inbook {crabbe:hal-01059206, title = {{Constraint-driven Grammar Description}}, booktitle = {{Constraints and Language}}, year = {2014}, pages = {93-121}, publisher = {{Cambridge Scholar Publishing}}, organization = {{Cambridge Scholar Publishing}}, keywords = {Constraints, Formal Grammar, Metagrammar}, url = {https://hal.archives-ouvertes.fr/hal-01059206}, author = {Beno{\^\i}t Crabb{\'e} and Denys Duchier and Parmentier, Yannick and Petitjean, Simon}, editor = {Philippe Blache and Henning Christiansen and Ver{\'o}nica Dahl and Denys Duchier and J{\o}rgen Villadsen} } @inproceedings {crabbe:hal-01105142, title = {{An LR-inspired generalized lexicalized phrase structure parser}}, year = {2014}, address = {Dublin, Ireland}, url = {https://hal.inria.fr/hal-01105142}, author = {Beno{\^\i}t Crabb{\'e}} } @booklet {crabbe:hal-01105345, title = {{Multilingual discriminative shift reduce phrase structure parsing for the SPMRL 2014 shared task}}, year = {2014}, note = {Poster}, url = {https://hal.inria.fr/hal-01105345}, author = {Beno{\^\i}t Crabb{\'e} and Seddah, Djam{\'e}} } @inbook {thuilier:hal-01451705, title = {Ordering preferences for postverbal complements in French}, booktitle = {French through Corpora - Ecological and Data-Driven Perspectives in French Language Studies}, year = {2014}, month = {Jun}, publisher = {Cambridge Scholars Publishing}, organization = {Cambridge Scholars Publishing}, keywords = {animacy, caract{\`e}re anim{\'e}, caract{\`e}re d{\'e}fini, complexit{\'e} syntaxique, corpus linguistics, definiteness, exp{\'e}rience psycholinguistique, fran{\c c}ais, French, length, linguistique de corpus, logistic regression, longueur des constituant, mixed-effect model, mod{\`e}le {\`a} effets mixtes, mod{\'e}lisation statistique, ordre de mots, pronominalit{\'e}, pronominally, psycholinguistic experiment, questionnaire, r{\'e}gression logistique, syntactic complexity, syntactic weight, word order}, url = {https://hal.archives-ouvertes.fr/hal-01451705}, author = {Juliette Thuilier and Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e}}, editor = {Henry Tyne} } @booklet {grant:hal-01451838, title = {{The role of animacy in sentence production: Evidence from French}}, year = {2014}, note = {Poster}, publisher = {{Universit{\'e} Brock}}, keywords = {animacy, coordination, Ditransitive construction, French, Voice Alternation (active/passive), word order, Word Order Variations}, url = {https://hal.archives-ouvertes.fr/hal-01451838}, author = {Grant, Margaret and Juliette Thuilier and Beno{\^\i}t Crabb{\'e} and Anne Abeill{\'e}} } @conference {grant:hal-01451790, title = {The role of conceptual accessibility on word order alternations in French: Evidence from sentence recall Complement order}, year = {2014}, note = {Poster}, month = {07/2014}, publisher = {{Universit{\'e} de Gen{\`e}ve}}, address = {Gen{\`e}ve}, keywords = {animacy, coordination, Ditransitive construction, French, Voice Alternation (active/passive), word order}, url = {https://hal.archives-ouvertes.fr/hal-01451790}, author = {Grant, Margaret and Juliette Thuilier and Beno{\^\i}t Crabb{\'e} and Anne Abeill{\'e}} } @inproceedings {crabbe:hal-01105143, title = {{Un analyseur discriminant de la famille LR pour l{\textquoteright}analyse en constituants}}, year = {2014}, address = {Marseille, France}, url = {https://hal.inria.fr/hal-01105143}, author = {Beno{\^\i}t Crabb{\'e}} } @inproceedings {abeille:hal-00936493, title = {French Polar Questions : a corpus study}, year = {2013}, month = {Jul}, address = {Gen{\`e}ve, Switzerland}, url = {https://hal.inria.fr/hal-00936493}, author = {Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e} and Godard, Dani{\`e}le and Jean-Marie Marandin} } @inproceedings {abeille:hal-00936490, title = {{Vers un treebank du fran{\c c}ais parl{\'e}}, year = {2013}, month = {Jun}, address = {Sables d{\textquoteright}Olonne, France}, keywords = {Corpus arbor{\'e}, corpus oral, fran{\c c}ais parl{\'e}, {analyse syntaxique automatique}, url = {https://hal.inria.fr/hal-00936490}, author = {Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e}} } @conference {5051, title = {Vers un treebank du fran{\c c}ais parl{\'e}}, year = {2013}, address = {Les Sables d{\textquoteright}Olonnes}, url = {http://www.taln2013.org/actes/www/T ALN-2013/}, author = {Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e}} } @article {crabbe:hal-00768224, title = {XMG : eXtensible MetaGrammar}, journal = {Computational Linguistics}, volume = {39}, number = {3}, year = {2013}, month = {Sep}, pages = {591-629}, publisher = {{Massachusetts Institute of Technology Press (MIT Press)}}, keywords = {Grammar formalism}, url = {https://hal.archives-ouvertes.fr/hal-00768224}, author = {Beno{\^\i}t Crabb{\'e} and Denys Duchier and Gardent, Claire and Le Roux, Joseph and Parmentier, Yannick} } @inproceedings {abeille:hal-00936496, title = {French questioning declaratives : a corpus study}, year = {2012}, month = {Sep}, address = {Paris, France}, url = {https://hal.inria.fr/hal-00936496}, author = {Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e} and Godard, Dani{\`e}le and Jean-Marie Marandin}, editor = {Sarah Brown-Schmidt and Jonathan Ginzburg and Staffan Larsson} } @article {thuilier:hal-00698896, title = {{Pr{\'e}dire la position de l{\textquoteright}adjectif {\'e}pith{\`e}te en fran{\c c}ais : approche quantitative}}, journal = {{Lingvisticae Investigationes}}, volume = {35}, number = {1}, year = {2012}, month = {Jun}, publisher = {{John Benjamins Publishing Company}}, url = {https://hal.inria.fr/hal-00698896}, author = {Juliette Thuilier and Fox, Gwendoline and Beno{\^\i}t Crabb{\'e}} } @inproceedings {seddah:hal-00780899, title = {Ubiquitous Usage of a French Large Corpus: Processing the Est Republicain Corpus}, year = {2012}, month = {May}, publisher = {{ELRA}}, address = {Istambul, Turkey}, keywords = {corpus, out-of-domain, parsing}, url = {https://hal.inria.fr/hal-00780899}, author = {Seddah, Djam{\'e} and Marie Candito and Beno{\^\i}t Crabb{\'e} and Anguiano Enrique, Henestroza} } @booklet {thuilier:hal-01451725, title = {{Do animate arguments come first ?}}, howpublished = {2011}, year = {2011}, note = {Poster}, publisher = {{Barbara Hemforth, Saveria Colonna, Harry Tily, Manuel Gimenes}}, keywords = {animacy, French, word order}, url = {https://hal.archives-ouvertes.fr/hal-01451725}, author = {Juliette Thuilier and Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e}} } @inproceedings {1067, title = {Do animate arguments come first ? the case of French ditransitive verbs}, year = {2011}, address = {Paris}, author = {Juliette Thuilier and Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e}}, editor = {Barbara Hemforth} } @inproceedings {1068, title = {Pr{\'e}f{\'e}rences concernant l{\textquoteright}ordre relatif des compl{\'e}ments du verbe en fran{\c c}ais}, year = {2011}, address = {Nancy}, author = {Juliette Thuilier and Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e}} } @inproceedings {thuilier:halshs-01441248, title = {{Pr{\'e}f{\'e}rences concernant l{\textquoteright}ordre relatif des compl{\'e}ments du verbe en fran{\c c}ais}}, year = {2011}, address = {Nancy, Unknown or Invalid Region}, keywords = {Linguistics}, url = {https://halshs.archives-ouvertes.fr/halshs-01441248}, author = {Juliette Thuilier and Anne Abeill{\'e} and Beno{\^\i}t Crabb{\'e}} } @inproceedings {boruta:inria-00605806, title = {{Testing the Robustness of Online Word Segmentation: Effects of Linguistic Diversity and Phonetic Variation}}, year = {2011}, pages = {1-9}, address = {Portland, United States}, url = {https://hal.inria.fr/inria-00605806}, author = {Boruta, Luc and Peperkamp, Sharon and Beno{\^\i}t Crabb{\'e} and Dupoux, Emmanuel}, editor = {Keller, Frank and Reitter, David} } @booklet {fox:hal-01451891, title = {{Alternating the position of adjectives in French: An item-based phenomenon}}, year = {2010}, note = {Poster}, publisher = {{Max Planck Institute for Evolutionary Anthropology}}, keywords = {Attributive adjective alternation, Construction based approaches, Corpus linguistic, French, Word Order Variations}, url = {https://hal.archives-ouvertes.fr/hal-01451891}, author = {Fox, Gwendoline and Juliette Thuilier and Beno{\^\i}t Crabb{\'e}} }