Xavier Tannier


2021

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Classification multilabel de concepts médicaux pour l’identification du profil clinique du patient (Multilabel classification of medical concepts for patient’s clinical profile identification )
Christel Gérardin | Pascal Vaillant | Perceval Wajsbürt | Clément Gilavert | Ali Bellamine | Emmanuelle Kempf | Xavier Tannier
Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Atelier DÉfi Fouille de Textes (DEFT)

La première tâche du Défi fouille de textes 2021 a consisté à extraire automatiquement, à partir de cas cliniques, les phénotypes pathologiques des patients regroupés par tête de chapitre du MeSH-maladie. La solution présentée est celle d’un classifieur multilabel basé sur un transformer. Deux transformers ont été utilisés : le camembert-large classique (run 1) et le camembert-large fine-tuné (run 2) sur des articles biomédicaux français en accès libre. Nous avons également proposé un modèle « bout-enbout », avec une première phase d’extraction d’entités nommées également basée sur un transformer de type camembert-large et un classifieur de genre sur un modèle Adaboost. Nous obtenons un très bon rappel et une précision correcte, pour une F1-mesure autour de 0,77 pour les trois runs. La performance du modèle « bout-en-bout » est similaire aux autres méthodes.

2020

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Modèle neuronal pour la résolution de la coréférence dans les dossiers médicaux électroniques (Neural approach for coreference resolution in electronic health records )
Julien Tourille | Olivier Ferret | Aurélie Névéol | Xavier Tannier
Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 2 : Traitement Automatique des Langues Naturelles

La résolution de la coréférence est un élément essentiel pour la constitution automatique de chronologies médicales à partir des dossiers médicaux électroniques. Dans ce travail, nous présentons une approche neuronale pour la résolution de la coréférence dans des textes médicaux écrits en anglais pour les entités générales et cliniques en nous évaluant dans le cadre de référence pour cette tâche que constitue la tâche 1C de la campagne i2b2 2011.

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Participation de l’équipe du LIMICS à DEFT 2020 (Participation of team LIMICS in the DEFT 2020 challenge )
Perceval Wajsbürt | Yoann Taillé | Guillaume Lainé | Xavier Tannier
Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Atelier DÉfi Fouille de Textes

Nous présentons dans cet article les méthodes conçues et les résultats obtenus lors de notre participation à la tâche 3 de la campagne d’évaluation DEFT 2020, consistant en la reconnaissance d’entités nommées du domaine médical. Nous proposons deux modèles différents permettant de prendre en compte les entités imbriquées, qui représentent une des difficultés du jeu de données proposées, et présentons les résultats obtenus. Notre meilleur run obtient la meilleure performance parmi les participants, sur l’une des deux sous-tâches du défi.

2019

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Participation de l’équipe LAI à DEFT 2019 (Participation of team LAI in the DEFT 2019 challenge )
Jacques Hilbey | Louise Deléger | Xavier Tannier
Actes de la Conférence sur le Traitement Automatique des Langues Naturelles (TALN) PFIA 2019. Défi Fouille de Textes (atelier TALN-RECITAL)

Nous présentons dans cet article les méthodes conçues et les résultats obtenus lors de notre participation à la tâche 3 de la campagne d’évaluation DEFT 2019. Nous avons utilisé des approches simples à base de règles ou d’apprentissage automatique, et si nos résultats sont très bons sur les informations simples à extraire comme l’âge et le sexe du patient, ils restent mitigés sur les tâches plus difficiles.

2018

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Evaluation of a Sequence Tagging Tool for Biomedical Texts
Julien Tourille | Matthieu Doutreligne | Olivier Ferret | Aurélie Névéol | Nicolas Paris | Xavier Tannier
Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis

Many applications in biomedical natural language processing rely on sequence tagging as an initial step to perform more complex analysis. To support text analysis in the biomedical domain, we introduce Yet Another SEquence Tagger (YASET), an open-source multi purpose sequence tagger that implements state-of-the-art deep learning algorithms for sequence tagging. Herein, we evaluate YASET on part-of-speech tagging and named entity recognition in a variety of text genres including articles from the biomedical literature in English and clinical narratives in French. To further characterize performance, we report distributions over 30 runs and different sizes of training datasets. YASET provides state-of-the-art performance on the CoNLL 2003 NER dataset (F1=0.87), MEDPOST corpus (F1=0.97), MERLoT corpus (F1=0.99) and NCBI disease corpus (F1=0.81). We believe that YASET is a versatile and efficient tool that can be used for sequence tagging in biomedical and clinical texts.

2017

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Unsupervised Event Clustering and Aggregation from Newswire and Web Articles
Swen Ribeiro | Olivier Ferret | Xavier Tannier
Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism

In this paper, we present an unsupervised pipeline approach for clustering news articles based on identified event instances in their content. We leverage press agency newswire and monolingual word alignment techniques to build meaningful and linguistically varied clusters of articles from the web in the perspective of a broader event type detection task. We validate our approach on a manually annotated corpus of Web articles.

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LIMSI-COT at SemEval-2017 Task 12: Neural Architecture for Temporal Information Extraction from Clinical Narratives
Julien Tourille | Olivier Ferret | Xavier Tannier | Aurélie Névéol
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

In this paper we present our participation to SemEval 2017 Task 12. We used a neural network based approach for entity and temporal relation extraction, and experimented with two domain adaptation strategies. We achieved competitive performance for both tasks.

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Neural Architecture for Temporal Relation Extraction: A Bi-LSTM Approach for Detecting Narrative Containers
Julien Tourille | Olivier Ferret | Aurélie Névéol | Xavier Tannier
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

We present a neural architecture for containment relation identification between medical events and/or temporal expressions. We experiment on a corpus of de-identified clinical notes in English from the Mayo Clinic, namely the THYME corpus. Our model achieves an F-measure of 0.613 and outperforms the best result reported on this corpus to date.

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Apprendre des représentations jointes de mots et d’entités pour la désambiguïsation d’entités (Combining Word and Entity Embeddings for Entity Linking)
José G. Moreno | Romaric Besançon | Romain Beaumont | Eva D’Hondt | Anne-Laure Ligozat | Sophie Rosset | Xavier Tannier | Brigitte Grau
Actes des 24ème Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 - Articles longs

La désambiguïsation d’entités (ou liaison d’entités), qui consiste à relier des mentions d’entités d’un texte à des entités d’une base de connaissance, est un problème qui se pose, entre autre, pour le peuplement automatique de bases de connaissances à partir de textes. Une difficulté de cette tâche est la résolution d’ambiguïtés car les systèmes ont à choisir parmi un nombre important de candidats. Cet article propose une nouvelle approche fondée sur l’apprentissage joint de représentations distribuées des mots et des entités dans le même espace, ce qui permet d’établir un modèle robuste pour la comparaison entre le contexte local de la mention d’entité et les entités candidates.

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Temporal information extraction from clinical text
Julien Tourille | Olivier Ferret | Xavier Tannier | Aurélie Névéol
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

In this paper, we present a method for temporal relation extraction from clinical narratives in French and in English. We experiment on two comparable corpora, the MERLOT corpus and the THYME corpus, and show that a common approach can be used for both languages.

2016

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Extraction de relations temporelles dans des dossiers électroniques patient (Extracting Temporal Relations from Electronic Health Records)
Julien Tourille | Olivier Ferret | Aurélie Névéol | Xavier Tannier
Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 2 : TALN (Posters)

L’analyse temporelle des documents cliniques permet d’obtenir des représentations riches des informations contenues dans les dossiers électroniques patient. Cette analyse repose sur l’extraction d’événements, d’expressions temporelles et des relations entre eux. Dans ce travail, nous considérons que nous disposons des événements et des expressions temporelles pertinents et nous nous intéressons aux relations temporelles entre deux événements ou entre un événement et une expression temporelle. Nous présentons des modèles de classification supervisée pour l’extraction de des relations en français et en anglais. Les performances obtenues sont comparables dans les deux langues, suggérant ainsi que différents domaines cliniques et différentes langues pourraient être abordés de manière similaire.

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Datasets for Aspect-Based Sentiment Analysis in French
Marianna Apidianaki | Xavier Tannier | Cécile Richart
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Aspect Based Sentiment Analysis (ABSA) is the task of mining and summarizing opinions from text about specific entities and their aspects. This article describes two datasets for the development and testing of ABSA systems for French which comprise user reviews annotated with relevant entities, aspects and polarity values. The first dataset contains 457 restaurant reviews (2365 sentences) for training and testing ABSA systems, while the second contains 162 museum reviews (655 sentences) dedicated to out-of-domain evaluation. Both datasets were built as part of SemEval-2016 Task 5 “Aspect-Based Sentiment Analysis” where seven different languages were represented, and are publicly available for research purposes.

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A Dataset for Open Event Extraction in English
Kiem-Hieu Nguyen | Xavier Tannier | Olivier Ferret | Romaric Besançon
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This article presents a corpus for development and testing of event schema induction systems in English. Schema induction is the task of learning templates with no supervision from unlabeled texts, and to group together entities corresponding to the same role in a template. Most of the previous work on this subject relies on the MUC-4 corpus. We describe the limits of using this corpus (size, non-representativeness, similarity of roles across templates) and propose a new, partially-annotated corpus in English which remedies some of these shortcomings. We make use of Wikinews to select the data inside the category Laws & Justice, and query Google search engine to retrieve different documents on the same events. Only Wikinews documents are manually annotated and can be used for evaluation, while the others can be used for unsupervised learning. We detail the methodology used for building the corpus and evaluate some existing systems on this new data.

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SemEval-2016 Task 5: Aspect Based Sentiment Analysis
Maria Pontiki | Dimitris Galanis | Haris Papageorgiou | Ion Androutsopoulos | Suresh Manandhar | Mohammad AL-Smadi | Mahmoud Al-Ayyoub | Yanyan Zhao | Bing Qin | Orphée De Clercq | Véronique Hoste | Marianna Apidianaki | Xavier Tannier | Natalia Loukachevitch | Evgeniy Kotelnikov | Nuria Bel | Salud María Jiménez-Zafra | Gülşen Eryiğit
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

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LIMSI-COT at SemEval-2016 Task 12: Temporal relation identification using a pipeline of classifiers
Julien Tourille | Olivier Ferret | Aurélie Névéol | Xavier Tannier
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2015

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Automatic Extraction of Time Expressions Accross Domains in French Narratives
Mike Donald Tapi Nzali | Xavier Tannier | Aurélie Névéol
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

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Redundancy in French Electronic Health Records: A preliminary study
Eva D’hondt | Xavier Tannier | Aurélie Névéol
Proceedings of the Sixth International Workshop on Health Text Mining and Information Analysis

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Generative Event Schema Induction with Entity Disambiguation
Kiem-Hieu Nguyen | Xavier Tannier | Olivier Ferret | Romaric Besançon
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

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Analyse d’expressions temporelles dans les dossiers électroniques patients
Mike Donald Tapi Nzali | Aurélie Névéol | Xavier Tannier
Actes de la 22e conférence sur le Traitement Automatique des Langues Naturelles. Articles longs

Les références à des phénomènes du monde réel et à leur caractérisation temporelle se retrouvent dans beaucoup de types de discours en langue naturelle. Ainsi, l’analyse temporelle apparaît comme un élément important en traitement automatique de la langue. Cet article présente une analyse de textes en domaine de spécialité du point de vue temporel. En s’appuyant sur un corpus de documents issus de plusieurs dossiers électroniques patient désidentifiés, nous décrivons la construction d’une ressource annotée en expressions temporelles selon la norme TimeML. Par suite, nous utilisons cette ressource pour évaluer plusieurs méthodes d’extraction automatique d’expressions temporelles adaptées au domaine médical. Notre meilleur système statistique offre une performance de 0,91 de F-mesure, surpassant pour l’identification le système état de l’art HeidelTime. La comparaison de notre corpus de travail avec le corpus journalistique FR-Timebank permet également de caractériser les différences d’utilisation des expressions temporelles dans deux domaines de spécialité.

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Désambiguïsation d’entités pour l’induction non supervisée de schémas événementiels
Kiem-Hieu Nguyen | Xavier Tannier | Olivier Ferret | Romaric Besançon
Actes de la 22e conférence sur le Traitement Automatique des Langues Naturelles. Articles longs

Cet article présente un modèle génératif pour l’induction non supervisée d’événements. Les précédentes méthodes de la littérature utilisent uniquement les têtes des syntagmes pour représenter les entités. Pourtant, le groupe complet (par exemple, ”un homme armé”) apporte une information plus discriminante (que ”homme”). Notre modèle tient compte de cette information et la représente dans la distribution des schémas d’événements. Nous montrons que ces relations jouent un rôle important dans l’estimation des paramètres, et qu’elles conduisent à des distributions plus cohérentes et plus discriminantes. Les résultats expérimentaux sur le corpus de MUC-4 confirment ces progrès.

2014

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Ranking Multidocument Event Descriptions for Building Thematic Timelines
Kiem-Hieu Nguyen | Xavier Tannier | Veronique Moriceau
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

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Extracting News Web Page Creation Time with DCTFinder
Xavier Tannier
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Web pages do not offer reliable metadata concerning their creation date and time. However, getting the document creation time is a necessary step for allowing to apply temporal normalization systems to web pages. In this paper, we present DCTFinder, a system that parses a web page and extracts from its content the title and the creation date of this web page. DCTFinder combines heuristic title detection, supervised learning with Conditional Random Fields (CRFs) for document date extraction, and rule-based creation time recognition. Using such a system allows further deep and efficient temporal analysis of web pages. Evaluation on three corpora of English and French web pages indicates that the tool can extract document creation times with reasonably high accuracy (between 87 and 92\%). DCTFinder is made freely available on http://sourceforge.net/projects/dctfinder/, as well as all resources (vocabulary and annotated documents) built for training and evaluating the system in English and French, and the English trained model itself.

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French Resources for Extraction and Normalization of Temporal Expressions with HeidelTime
Véronique Moriceau | Xavier Tannier
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In this paper, we describe the development of French resources for the extraction and normalization of temporal expressions with HeidelTime, a open-source multilingual, cross-domain temporal tagger. HeidelTime extracts temporal expressions from documents and normalizes them according to the TIMEX3 annotation standard. Several types of temporal expressions are extracted: dates, times, durations and temporal sets. French resources have been evaluated in two different ways: on the French TimeBank corpus, a corpus of newspaper articles in French annotated according to the ISO-TimeML standard, and on a user application for automatic building of event timelines. Results on the French TimeBank are quite satisfaying as they are comparable to those obtained by HeidelTime in English and Spanish on newswire articles. Concerning the user application, we used two temporal taggers for the preprocessing of the corpus in order to compare their performance and results show that the performances of our application on French documents are better with HeidelTime. The French resources and evaluation scripts are publicly available with HeidelTime.

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Evaluating Web-as-corpus Topical Document Retrieval with an Index of the OpenDirectory
Clément de Groc | Xavier Tannier
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This article introduces a novel protocol and resource to evaluate Web-as-corpus topical document retrieval. To the contrary of previous work, our goal is to provide an automatic, reproducible and robust evaluation for this task. We rely on the OpenDirectory (DMOZ) as a source of topically annotated webpages and index them in a search engine. With this OpenDirectory search engine, we can then easily evaluate the impact of various parameters such as the number of seed terms, queries or documents, or the usefulness of various term selection algorithms. A first fully automatic evaluation is described and provides baseline performances for this task. The article concludes with practical information regarding the availability of the index and resource files.

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Thematic Cohesion: measuring terms discriminatory power toward themes
Clément de Groc | Xavier Tannier | Claude de Loupy
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We present a new measure of thematic cohesion. This measure associates each term with a weight representing its discriminatory power toward a theme, this theme being itself expressed by a list of terms (a thematic lexicon). This thematic cohesion criterion can be used in many applications, such as query expansion, computer-assisted translation, or iterative construction of domain-specific lexicons and corpora. The measure is computed in two steps. First, a set of documents related to the terms is gathered from the Web by querying a Web search engine. Then, we produce an oriented co-occurrence graph, where vertices are the terms and edges represent the fact that two terms co-occur in a document. This graph can be interpreted as a recommendation graph, where two terms occurring in a same document means that they recommend each other. This leads to using a random walk algorithm that assigns a global importance value to each vertex of the graph. After observing the impact of various parameters on those importance values, we evaluate their correlation with retrieval effectiveness.

2013

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Building Event Threads out of Multiple News Articles
Xavier Tannier | Véronique Moriceau
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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Extraction of temporal relations between clinical events in clinical documents (Extraction des relations temporelles entre événements médicaux dans des comptes rendus hospitaliers) [in French]
Pierre Zweigenbaum | Xavier Tannier
Proceedings of TALN 2013 (Volume 2: Short Papers)

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An Interface for Validating and Evaluating Thematic Timelines (Une interface pour la validation et l’évaluation de chronologies thématiques) [in French]
Xavier Tannier | Véronique Moriceau | Erwan Le Flem
Proceedings of TALN 2013 (Volume 3: System Demonstrations)

2012

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WebAnnotator, an Annotation Tool for Web Pages
Xavier Tannier
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This article presents WebAnnotator, a new tool for annotating Web pages. WebAnnotator is implemented as a Firefox extension, allowing annotation of both offline and inline pages. The HTML rendering fully preserved and all annotations consist in new HTML spans with specific styles. WebAnnotator provides an easy and general-purpose framework and is made available under CeCILL free license (close to GNU GPL), so that use and further contributions are made simple. All parts of an HTML document can be annotated: text, images, videos, tables, menus, etc. The annotations are created by simply selecting a part of the document and clicking on the relevant type and subtypes. The annotated elements are then highlighted in a specific color. Annotation schemas can be defined by the user by creating a simple DTD representing the types and subtypes that must be highlighted. Finally, annotations can be saved (HTML with highlighted parts of documents) or exported (in a machine-readable format).

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Event Nominals: Annotation Guidelines and a Manually Annotated Corpus in French
Béatrice Arnulphy | Xavier Tannier | Anne Vilnat
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

Within the general purpose of information extraction, detection of event descriptions is an important clue. A word refering to an event is more powerful than a single word, because it implies a location, a time, protagonists (persons, organizations\dots). However, if verbal designations of events are well studied and easier to detect than nominal ones, nominal designations do not claim as much definition effort and resources. In this work, we focus on nominals desribing events. As our application domain is information extraction, we follow a named entity approach to describe and annotate events. In this paper, we present a typology and annotation guidelines for event nominals annotation. We applied them to French newswire articles and produced an annotated corpus. We present observations about the designations used in our manually annotated corpus and the behavior of their triggers. We provide statistics concerning word ambiguity and context of use of event nominals, as well as machine learning experiments showing the difficulty of using lexicons for extracting events.

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Temporal Annotation: A Proposal for Guidelines and an Experiment with Inter-annotator Agreement
André Bittar | Caroline Hagège | Véronique Moriceau | Xavier Tannier | Charles Teissèdre
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This article presents work carried out within the framework of the ongoing ANR (French National Research Agency) project Chronolines, which focuses on the temporal processing of large news-wire corpora in English and French. The aim of the project is to create new and innovative interfaces for visualizing textual content according to temporal criteria. Extracting and normalizing the temporal information in texts through linguistic annotation is an essential step towards attaining this objective. With this goal in mind, we developed a set of guidelines for the annotation of temporal and event expressions that is intended to be compatible with the TimeML markup language, while addressing some of its pitfalls. We provide results of an initial application of these guidelines to real news-wire texts in French over several iterations of the annotation process. These results include inter-annotator agreement figures and an error analysis. Our final inter-annotator agreement figures compare favorably with those reported for the TimeBank 1.2 annotation project.

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Evolution of Event Designation in Media: Preliminary Study
Xavier Tannier | Véronique Moriceau | Béatrice Arnulphy | Ruixin He
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

Within the general purpose of information extraction, detection of event descriptions is often an important clue. An important characteristic of event designation in texts, and especially in media, is that it changes over time. Understanding how these designations evolve is important in information retrieval and information extraction. Our first hypothesis is that, when an event first occurs, media relate it in a very descriptive way (using verbal designations) whereas after some time, they use shorter nominal designations instead. Our second hypothesis is that the number of different nominal designations for an event tends to stabilize itself over time. In this article, we present our methodology concerning the study of the evolution of event designations in French documents from the news agency AFP. For this preliminary study, we focused on 7 topics which have been relatively important in France. Verbal and nominal designations of events have been manually annotated in manually selected topic-related passages. This French corpus contains a total of 2064 annotations. We then provide preliminary interesting statistical results and observations concerning these evolutions.

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A Rough Set Formalization of Quantitative Evaluation with Ambiguity
Patrick Paroubek | Xavier Tannier
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

In this paper, we present the founding elements of a formal model of the evaluation paradigm in natural language processing. We propose an abstract model of objective quantitative evaluation based on rough sets, as well as the notion of potential performance space for describing the performance variations corresponding to the ambiguity present in hypothesis data produced by a computer program, when comparing it to the reference data created by humans. A formal model of the evaluation paradigm will be useful for comparing evaluations protocols, investigating evaluation constraint relaxation and getting a better understanding of the evaluation paradigm, provided it is general enough to be able to represent any natural language processing task.

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Finding Salient Dates for Building Thematic Timelines
Rémy Kessler | Xavier Tannier | Caroline Hagège | Véronique Moriceau | André Bittar
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Un critère de cohésion thématique fondé sur un graphe de cooccurrences (Topical Cohesion using Graph Random Walks) [in French]
Clément de Groc | Xavier Tannier | Claude de Loupy
Proceedings of the Joint Conference JEP-TALN-RECITAL 2012, volume 2: TALN

2011

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GrawlTCQ: Terminology and Corpora Building by Ranking Simultaneously Terms, Queries and Documents using Graph Random Walks
Xavier Tannier | Javier Couto | Clément de Groc
Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing

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Génération automatique de questions à partir de textes en français (Automatic generation of questions from texts in French)
Louis de Viron | Delphine Bernhard | Véronique Moriceau | Xavier Tannier
Actes de la 18e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

Nous présentons dans cet article un générateur automatique de questions pour le français. Le système de génération procède par transformation de phrases déclaratives en interrogatives et se base sur une analyse syntaxique préalable de la phrase de base. Nous détaillons les différents types de questions générées. Nous présentons également une évaluation de l’outil, qui démontre que 41 % des questions générées par le système sont parfaitement bien formées.

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Un lexique pondéré des noms d’événements en français (A weighted lexicon of event names in French)
Béatrice Arnulphy | Xavier Tannier | Anne Vilnat
Actes de la 18e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

Cet article décrit une étude sur l’annotation automatique des noms d’événements dans les textes en français. Plusieurs lexiques existants sont utilisés, ainsi que des règles syntaxiques d’extraction, et un lexique composé de façon automatique, permettant de fournir une valeur sur le niveau d’ambiguïté du mot en tant qu’événement. Cette nouvelle information permettrait d’aider à la désambiguïsation des noms d’événements en contexte.

2010

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FIDJI: Web Question-Answering at Quaero 2009
Xavier Tannier | Véronique Moriceau
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

This paper presents the participation of FIDJI system to the Web Question-Answering evaluation campaign organized by Quaero in 2009. FIDJI is an open-domain question-answering system which combines syntactic information with traditional QA techniques such as named entity recognition and term weighting in order to validate answers through multiple documents. It was originally designed to process ``clean'' document collections. Overall results are significantly lower than in traditional campaigns but results (for French evaluation) are quite good compared to other state-of-the-art systems. They show that a syntax-based strategy, applied on uncleaned Web data, can still obtain good results. Moreover, we obtain much higher scores on ``complex'' questions, i.e. `how' and `why' questions, which are more representative of real user needs. These results show that questioning the Web with advanced linguistic techniques can be done without heavy pre-processing and with results that come near to best systems that use strong resources and large structured indexes.

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Hybrid Citation Extraction from Patents
Olivier Galibert | Sophie Rosset | Xavier Tannier | Fanny Grandry
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

The Quaero project organized a set of evaluations of Named Entity recognition systems in 2009. One of the sub-tasks consists in extracting citations from patents, i.e. references to other documents, either other patents or general literature from English-language patents. We present in this paper the participation of LIMSI in this evaluation, with a complete system description and the evaluation results. The corpus shown that patent and non-patent citations have a very different nature. We then separated references to other patents and to general literature papers and we created a hybrid system. For patent citations, the system used rule-based expert knowledge on the form of regular expressions. The system for detecting non-patent citations, on the other hand, is purely stochastic (machine learning with CRF++). Then we mixed both approaches to provide a single output. 4 teams participated to this task and our system obtained the best results of this evaluation campaign, even if the difference between the first two systems is poorly significant.

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Question Answering on Web Data: The QA Evaluation in Quæro
Ludovic Quintard | Olivier Galibert | Gilles Adda | Brigitte Grau | Dominique Laurent | Véronique Moriceau | Sophie Rosset | Xavier Tannier | Anne Vilnat
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

In the QA and information retrieval domains progress has been assessed via evaluation campaigns(Clef, Ntcir, Equer, Trec).In these evaluations, the systems handle independent questions and should provide one answer to each question, extracted from textual data, for both open domain and restricted domain. Quæro is a program promoting research and industrial innovation on technologies for automatic analysis and classification of multimedia and multilingual documents. Among the many research areas concerned by Quæro. The Quaero project organized a series of evaluations of Question Answering on Web Data systems in 2008 and 2009. For each language, English and French the full corpus has a size of around 20Gb for 2.5M documents. We describe the task and corpora, and especially the methodologies used in 2008 to construct the test of question and a new one in the 2009 campaign. Six types of questions were addressed, factual, Non-factual(How, Why, What), List, Boolean. A description of the participating systems and the obtained results is provided. We show the difficulty for a question-answering system to work with complex data and questions.

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Named and Specific Entity Detection in Varied Data: The Quæro Named Entity Baseline Evaluation
Olivier Galibert | Ludovic Quintard | Sophie Rosset | Pierre Zweigenbaum | Claire Nédellec | Sophie Aubin | Laurent Gillard | Jean-Pierre Raysz | Delphine Pois | Xavier Tannier | Louise Deléger | Dominique Laurent
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

The Quæro program that promotes research and industrial innovation on technologies for automatic analysis and classification of multimedia and multilingual documents. Within its context a set of evaluations of Named Entity recognition systems was held in 2009. Four tasks were defined. The first two concerned traditional named entities in French broadcast news for one (a rerun of ESTER 2) and of OCR-ed old newspapers for the other. The third was a gene and protein name extraction in medical abstracts. The last one was the detection of references in patents. Four different partners participated, giving a total of 16 systems. We provide a synthetic descriptions of all of them classifying them by the main approaches chosen (resource-based, rules-based or statistical), without forgetting the fact that any modern system is at some point hybrid. The metric (the relatively standard Slot Error Rate) and the results are also presented and discussed. Finally, a process is ongoing with preliminary acceptance of the partners to ensure the availability for the community of all the corpora used with the exception of the non-Quæro produced ESTER 2 one.

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A Corpus for Studying Full Answer Justification
Arnaud Grappy | Brigitte Grau | Olivier Ferret | Cyril Grouin | Véronique Moriceau | Isabelle Robba | Xavier Tannier | Anne Vilnat | Vincent Barbier
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Question answering (QA) systems aim at retrieving precise information from a large collection of documents. To be considered as reliable by users, a QA system must provide elements to evaluate the answer. This notion of answer justification can also be useful when developping a QA system in order to give criteria for selecting correct answers. An answer justification can be found in a sentence, a passage made of several consecutive sentences or several passages of a document or several documents. Thus, we are interesting in pinpointing the set of information that allows to verify the correctness of the answer in a candidate passage and the question elements that are missing in this passage. Moreover, the relevant information is often given in texts in a different form from the question form: anaphora, paraphrases, synonyms. In order to have a better idea of the importance of all the phenomena we underlined, and to provide enough examples at the QA developer's disposal to study them, we decided to build an annotated corpus.

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Une étude des questions “complexes” en question-réponse
Véronique Moriceau | Xavier Tannier | Mathieu Falco
Actes de la 17e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

La plupart des systèmes de question-réponse ont été conçus pour répondre à des questions dites “factuelles” (réponses précises comme des dates, des lieux), et peu se sont intéressés au traitement des questions complexes. Cet article présente une typologie des questions en y incluant les questions complexes, ainsi qu’une typologie des formes de réponses attendues pour chaque type de questions. Nous présentons également des expériences préliminaires utilisant ces typologies pour les questions complexes, avec de bons résultats.

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Les entités nommées événement et les verbes de cause-conséquence
Béatrice Arnulphy | Xavier Tannier | Anne Vilnat
Actes de la 17e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

L’extraction des événements désignés par des noms est peu étudiée dans des corpus généralistes. Si des lexiques de noms déclencheurs d’événements existent, les problèmes de polysémie sont nombreux et beaucoup d’événements ne sont pas introduits par des déclencheurs. Nous nous intéressons dans cet article à une hypothèse selon laquelle les verbes induisant la cause ou la conséquence sont de bons indices quant à la présence d’événements nominaux dans leur cotexte.

2009

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Apport de la syntaxe dans un système de question-réponse : étude du système FIDJI.
Véronique Moriceau | Xavier Tannier
Actes de la 16ème conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

Cet article présente une série d’évaluations visant à étudier l’apport d’une analyse syntaxique robuste des questions et des documents dans un système de questions-réponses. Ces évaluations ont été effectuées sur le système FIDJI, qui utilise à la fois des informations syntaxiques et des techniques plus “traditionnelles”. La sélection des documents, l’extraction de la réponse ainsi que le comportement selon les différents types de questions ont été étudiés.

2008

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Evaluation Metrics for Automatic Temporal Annotation of Texts
Xavier Tannier | Philippe Muller
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Recent years have seen increasing attention in temporal processing of texts as well as a lot of standardization effort of temporal information in natural language. A central part of this information lies in the temporal relations between events described in a text, when their precise times or dates are not known. Reliable human annotation of such information is difficult, and automatic comparisons must follow procedures beyond mere precision-recall of local pieces of information, since a coherent picture can only be considered at a global level. We address the problem of evaluation metrics of such information, aiming at fair comparisons between systems, by proposing some measures taking into account the globality of a text.

2007

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XRCE-T: XIP Temporal Module for TempEval campaign.
Caroline Hagège | Xavier Tannier
Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007)

2006

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Natural Language Processing and XML Retrieval
Alan Woodley | Xavier Tannier | Marcus Hassler | Shlomo Geva
Proceedings of the Australasian Language Technology Workshop 2006

2004

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Une méthode pour l’annotation de relations temporelles dans des textes et son évaluation
Philippe Muller | Xavier Tannier
Actes de la 11ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs

Cet article traite de l’annotation automatique d’informations temporelles dans des textes et vise plus particulièrement les relations entre événements introduits par les verbes dans chaque clause. Si ce problème a mobilisé beaucoup de chercheurs sur le plan théorique, il reste en friche pour ce qui est de l’annotation automatique systématique (et son évaluation), même s’il existe des débuts de méthodologie pour faire réaliser la tâche par des humains. Nous proposons ici à la fois une méthode pour réaliser la tâche automatiquement et une manière de mesurer à quel degré l’objectif est atteint. Nous avons testé la faisabilité de ceci sur des dépêches d’agence avec des premiers résultats encourageants.

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Annotating and measuring temporal relations in texts
Philippe Muller | Xavier Tannier
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics