François Lareau


2019

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Multilingual sentence-level bias detection in Wikipedia
Desislava Aleksandrova | François Lareau | Pierre André Ménard
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)

We propose a multilingual method for the extraction of biased sentences from Wikipedia, and use it to create corpora in Bulgarian, French and English. Sifting through the revision history of the articles that at some point had been considered biased and later corrected, we retrieve the last tagged and the first untagged revisions as the before/after snapshots of what was deemed a violation of Wikipedia’s neutral point of view policy. We extract the sentences that were removed or rewritten in that edit. The approach yields sufficient data even in the case of relatively small Wikipedias, such as the Bulgarian one, where 62k articles produced 5k biased sentences. We evaluate our method by manually annotating 520 sentences for Bulgarian and French, and 744 for English. We assess the level of noise and analyze its sources. Finally, we exploit the data with well-known classification methods to detect biased sentences. Code and datasets are hosted at https://github.com/crim-ca/wiki-bias.

2018

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GenDR: A Generic Deep Realizer with Complex Lexicalization
François Lareau | Florie Lambrey | Ieva Dubinskaite | Daniel Galarreta-Piquette | Maryam Nejat
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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Retrieving Information from the French Lexical Network in RDF/OWL Format
Alexsandro Fonseca | Fatiha Sadat | François Lareau
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2016

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Encoding a syntactic dictionary into a super granular unification grammar
Sylvain Kahane | François Lareau
Proceedings of the Workshop on Grammar and Lexicon: interactions and interfaces (GramLex)

We show how to turn a large-scale syntactic dictionary into a dependency-based unification grammar where each piece of lexical information calls a separate rule, yielding a super granular grammar. Subcategorization, raising and control verbs, auxiliaries and copula, passivization, and tough-movement are discussed. We focus on the semantics-syntax interface and offer a new perspective on syntactic structure.

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Lexfom: a lexical functions ontology model
Alexsandro Fonseca | Fatiha Sadat | François Lareau
Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)

A lexical function represents a type of relation that exists between lexical units (words or expressions) in any language. For example, the antonymy is a type of relation that is represented by the lexical function Anti: Anti(big) = small. Those relations include both paradigmatic relations, i.e. vertical relations, such as synonymy, antonymy and meronymy and syntagmatic relations, i.e. horizontal relations, such as objective qualification (legitimate demand), subjective qualification (fruitful analysis), positive evaluation (good review) and support verbs (pay a visit, subject to an interrogation). In this paper, we present the Lexical Functions Ontology Model (lexfom) to represent lexical functions and the relation among lexical units. Lexfom is divided in four modules: lexical function representation (lfrep), lexical function family (lffam), lexical function semantic perspective (lfsem) and lexical function relations (lfrel). Moreover, we show how it combines to Lexical Model for Ontologies (lemon), for the transformation of lexical networks into the semantic web formats. So far, we have implemented 100 simple and 500 complex lexical functions, and encoded about 8,000 syntagmatic and 46,000 paradigmatic relations, for the French language.

2015

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La séparation des composantes lexicale et flexionnelle des vecteurs de mots
François Lareau | Gabriel Bernier-Colborne | Patrick Drouin
Actes de la 22e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

En sémantique distributionnelle, le sens des mots est modélisé par des vecteurs qui représentent leur distribution en corpus. Les modèles étant souvent calculés sur des corpus sans pré-traitement linguistique poussé, ils ne permettent pas de rendre bien compte de la compositionnalité morphologique des mots-formes. Nous proposons une méthode pour décomposer les vecteurs de mots en vecteurs lexicaux et flexionnels.

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Le traitement des collocations en génération de texte multilingue
Florie Lambrey | François Lareau
Actes de la 22e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

Pour concevoir des générateurs automatiques de texte génériques qui soient facilement réutilisables d’une langue et d’une application à l’autre, il faut modéliser les principaux phénomènes linguistiques qu’on retrouve dans les langues en général. Un des phénomènes fondamentaux qui demeurent problématiques pour le TAL est celui des collocations, comme grippe carabinée, peur bleue ou désir ardent, où un sens (ici, l’intensité) ne s’exprime pas de la même façon selon l’unité lexicale qu’il modifie. Dans la lexicographie explicative et combinatoire, on modélise les collocations au moyen de fonctions lexicales qui correspondent à des patrons récurrents de collocations. Par exemple, les expressions mentionnées ici se décrivent au moyen de la fonction Magn : Magn(PEUR) = BLEUE, Magn(GRIPPE) = CARABINÉE, etc. Il existe des centaines de fonctions lexicales. Dans cet article, nous nous intéressons à l’implémentation d’un sous-ensemble de fonctions qui décrivent les verbes supports et certains types de modificateurs.

2012

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Is Bad Structure Better Than No Structure?: Unsupervised Parsing for Realisation Ranking
Yasaman Motazedi | Mark Dras | François Lareau
Proceedings of COLING 2012

2011

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Detecting Interesting Event Sequences for Sports Reporting
François Lareau | Mark Dras | Robert Dale
Proceedings of the 13th European Workshop on Natural Language Generation

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Collocations in Multilingual Natural Language Generation: Lexical Functions meet Lexical Functional Grammar
François Lareau | Mark Dras | Benjamin Börschinger | Robert Dale
Proceedings of the Australasian Language Technology Association Workshop 2011