Corentin Ribeyre


2018

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Butterfly Effects in Frame Semantic Parsing: impact of data processing on model ranking
Alexandre Kabbach | Corentin Ribeyre | Aurélie Herbelot
Proceedings of the 27th International Conference on Computational Linguistics

Knowing the state-of-the-art for a particular task is an essential component of any computational linguistics investigation. But can we be truly confident that the current state-of-the-art is indeed the best performing model? In this paper, we study the case of frame semantic parsing, a well-established task with multiple shared datasets. We show that in spite of all the care taken to provide a standard evaluation resource, small variations in data processing can have dramatic consequences for ranking parser performance. This leads us to propose an open-source standardized processing pipeline, which can be shared and reused for robust model comparison.

2016

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Accurate Deep Syntactic Parsing of Graphs: The Case of French
Corentin Ribeyre | Eric Villemonte de la Clergerie | Djamé Seddah
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Parsing predicate-argument structures in a deep syntax framework requires graphs to be predicted. Argument structures represent a higher level of abstraction than the syntactic ones and are thus more difficult to predict even for highly accurate parsing models on surfacic syntax. In this paper we investigate deep syntax parsing, using a French data set (Ribeyre et al., 2014a). We demonstrate that the use of topologically different types of syntactic features, such as dependencies, tree fragments, spines or syntactic paths, brings a much needed context to the parser. Our higher-order parsing model, gaining thus up to 4 points, establishes the state of the art for parsing French deep syntactic structures.

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Deeper syntax for better semantic parsing
Olivier Michalon | Corentin Ribeyre | Marie Candito | Alexis Nasr
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

Syntax plays an important role in the task of predicting the semantic structure of a sentence. But syntactic phenomena such as alternations, control and raising tend to obfuscate the relation between syntax and semantics. In this paper we predict the semantic structure of a sentence using a deeper syntax than what is usually done. This deep syntactic representation abstracts away from purely syntactic phenomena and proposes a structural organization of the sentence that is closer to the semantic representation. Experiments conducted on a French corpus annotated with semantic frames showed that a semantic parser reaches better performances with such a deep syntactic input.

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Valencer: an API to Query Valence Patterns in FrameNet
Alexandre Kabbach | Corentin Ribeyre
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations

This paper introduces Valencer: a RESTful API to search for annotated sentences matching a given combination of syntactic realizations of the arguments of a predicate – also called ‘valence pattern’ – in the FrameNet database. The API takes as input an HTTP GET request specifying a valence pattern and outputs a list of exemplifying annotated sentences in JSON format. The API is designed to be modular and language-independent, and can therefore be easily integrated to other (NLP) server-side or client-side applications, as well as non-English FrameNet projects. Valencer is free, open-source, and licensed under the MIT license.

2015

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Because Syntax Does Matter: Improving Predicate-Argument Structures Parsing with Syntactic Features
Corentin Ribeyre | Eric Villemonte de la Clergerie | Djamé Seddah
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Foreebank: Syntactic Analysis of Customer Support Forums
Rasoul Kaljahi | Jennifer Foster | Johann Roturier | Corentin Ribeyre | Teresa Lynn | Joseph Le Roux
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

2014

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Deep Syntax Annotation of the Sequoia French Treebank
Marie Candito | Guy Perrier | Bruno Guillaume | Corentin Ribeyre | Karën Fort | Djamé Seddah | Éric de la Clergerie
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We define a deep syntactic representation scheme for French, which abstracts away from surface syntactic variation and diathesis alternations, and describe the annotation of deep syntactic representations on top of the surface dependency trees of the Sequoia corpus. The resulting deep-annotated corpus, named deep-sequoia, is freely available, and hopefully useful for corpus linguistics studies and for training deep analyzers to prepare semantic analysis.

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Alpage: Transition-based Semantic Graph Parsing with Syntactic Features
Corentin Ribeyre | Eric Villemonte de la Clergerie | Djamé Seddah
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)

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Annotation scheme for deep dependency syntax of French (Un schéma d’annotation en dépendances syntaxiques profondes pour le français) [in French]
Guy Perrier | Marie Candito | Bruno Guillaume | Corentin Ribeyre | Karën Fort | Djamé Seddah
Proceedings of TALN 2014 (Volume 2: Short Papers)

2013

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Towards a generic graph rewriting system to enrich syntactic structures (Vers un système générique de réécriture de graphes pour l’enrichissement de structures syntaxiques) [in French]
Corentin Ribeyre
Proceedings of RECITAL 2013

2012

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A linguistically-motivated 2-stage Tree to Graph Transformation
Corentin Ribeyre | Djamé Seddah | Eric Villemonte de la Clergerie
Proceedings of the 11th International Workshop on Tree Adjoining Grammars and Related Formalisms (TAG+11)