Christian Retoré


2025

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Neurosymbolic AI for Natural Language Inference in French : combining LLMs and theorem provers for semantic parsing and natural language reasoning
Maximos Skandalis | Lasha Abzianidze | Richard Moot | Christian Retoré | Simon Robillard
Proceedings of the 16th International Conference on Computational Semantics

In this article, we describe the first comprehensive neurosymbolic pipeline for the task of Natural Language Inference (NLI) for French, with the synergy of Large Language Models (CamemBERT) and automated theorem provers (GrailLight, LangPro). LLMs prepare the input for GrailLight by tagging each token with Part-of-Speech and grammatical information based on the Type-Logical Grammar formalism. GrailLight then produces the lambda-terms given as input to the LangPro theorem prover, a tableau-based theorem prover for natural logic originally developped for English. Currently, the proposed system works on the French version of SICK dataset. The results obtained are comparable to the ones on the English and Dutch versions of SICK with the same LangPro theorem prover, and are better than the results of recent transformers on this specific dataset.Finally, we have identified ways to further improve the results obtained, such as giving access to the theorem prover to lexical knowledge via a knowledge base for French.

2024

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New Datasets for Automatic Detection of Textual Entailment and of Contradictions between Sentences in French
Maximos Skandalis | Richard Moot | Christian Retoré | Simon Robillard
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

This paper introduces DACCORD, an original dataset in French for automatic detection of contradictions between sentences. It also presents new, manually translated versions of two datasets, namely the well known dataset RTE3 and the recent dataset GQNLI, from English to French, for the task of natural language inference / recognising textual entailment, which is a sentence-pair classification task. These datasets help increase the admittedly limited number of datasets in French available for these tasks. DACCORD consists of 1034 pairs of sentences and is the first dataset exclusively dedicated to this task and covering among others the topic of the Russian invasion in Ukraine. RTE3-FR contains 800 examples for each of its validation and test subsets, while GQNLI-FR is composed of 300 pairs of sentences and focuses specifically on the use of generalised quantifiers. Our experiments on these datasets show that they are more challenging than the two already existing datasets for the mainstream NLI task in French (XNLI, FraCaS). For languages other than English, most deep learning models for NLI tasks currently have only XNLI available as a training set. Additional datasets, such as ours for French, could permit different training and evaluation strategies, producing more robust results and reducing the inevitable biases present in any single dataset.

2019

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Proceedings of the IWCS 2019 Workshop on Computing Semantics with Types, Frames and Related Structures
Rainer Osswald | Christian Retoré | Peter Sutton
Proceedings of the IWCS 2019 Workshop on Computing Semantics with Types, Frames and Related Structures

2017

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Proceedings of the 12th International Conference on Computational Semantics (IWCS) — Long papers
Claire Gardent | Christian Retoré
Proceedings of the 12th International Conference on Computational Semantics (IWCS) — Long papers

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Proceedings of the 12th International Conference on Computational Semantics (IWCS) — Short papers
Claire Gardent | Christian Retoré
Proceedings of the 12th International Conference on Computational Semantics (IWCS) — Short papers

2013

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On the semantics of determiners in a rich type-theoretical framework (Sémantique des déterminants dans un cadre richement typé) [in French]
Christian Retoré
Proceedings of TALN 2013 (Volume 1: Long Papers)

2012

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Traitement automatique sur corpus de récits de voyages pyrénéens : Une analyse syntaxique, sémantique et temporelle (Processing of a Pyrenees Travel Novels Corpus : a Syntactical, Semantical and Temporal Analysis.) [in French]
Anaïs Lefeuvre | Richard Moot | Christian Retoré | Noémie-Fleur Sandillon-Rezer
Proceedings of the Joint Conference JEP-TALN-RECITAL 2012, volume 2: TALN

2011

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Un calcul de termes typés pour la pragmatique lexicale: chemins et voyageurs fictifs dans un corpus de récits de voyage (A calculation of typed terms for lexical pragmatics: paths and fictional travellers in a travel stories corpus)
Richard Moot | Laurent Prévot | Christian Retoré
Actes de la 18e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

Ce travail s’inscrit dans l’analyse automatique d’un corpus de récits de voyage. À cette fin, nous raffinons la sémantique de Montague pour rendre compte des phénomènes d’adaptation du sens des mots au contexte dans lequel ils apparaissent. Ici, nous modélisons les constructions de type ‘le chemin descend pendant une demi-heure’ où ledit chemin introduit un voyageur fictif qui le parcourt, en étendant des idées que le dernier auteur a développé avec Bassac et Mery. Cette introduction du voyageur utilise la montée de type afin que le quantificateur introduisant le voyageur porte sur toute la phrase et que les propriétés du chemin ne deviennent pas des propriétés du voyageur, fût-il fictif. Cette analyse sémantique (ou plutôt sa traduction en lambda-DRT) est d’ores et déjà implantée pour une partie du lexique de Grail.

2001

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Extending Lambek Grammars: a Logical Account of Minimalist Grammars
Alain Lecomte | Christian Retoré
Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics