no code implementations • ICLR 2019 • Damien Sileo, Tim Van De Cruys, Camille Pradel, Philippe Muller
In this work, we show that textual relational models implicitly use compositions from baseline SRL models.
1 code implementation • EMNLP 2021 • Lila Gravellier, Julie Hunter, Philippe Muller, Thomas Pellegrini, Isabelle Ferrané
Discourse segmentation, the first step of discourse analysis, has been shown to improve results for text summarization, translation and other NLP tasks.
no code implementations • JEP/TALN/RECITAL 2021 • Tom Bourgeade, Philippe Muller, Tim Van De Cruys
De nombreuses tâches sémantiques en TAL font usage de données collectées de manière semiautomatique, ce qui est souvent source d’artefacts indésirables qui peuvent affecter négativement les modèles entraînés sur celles-ci.
no code implementations • EMNLP (DISRPT) 2021 • Morteza Kamaladdini Ezzabady, Philippe Muller, Chloé Braud
Building on the most successful architecture from the 2019 similar shared task, we leverage datasets in the same or similar languages to augment training data and improve on the best systems from the previous campaign on 3 out of 4 subtasks, with a mean improvement on all 16 datasets of 0. 85%.
no code implementations • EMNLP (DISRPT) 2021 • Amir Zeldes, Yang Janet Liu, Mikel Iruskieta, Philippe Muller, Chloé Braud, Sonia Badene
In 2021, we organized the second iteration of a shared task dedicated to the underlying units used in discourse parsing across formalisms: the DISRPT Shared Task (Discourse Relation Parsing and Treebanking).
1 code implementation • COLING (CODI, CRAC) 2022 • Nicolas Devatine, Philippe Muller, Chloé Braud
With the growing number of information sources, the problem of media bias becomes worrying for a democratic society.
1 code implementation • LREC 2020 • Damien Sileo, Tim Van De Cruys, Camille Pradel, Philippe Muller
In this work, we take another perspective: using a model trained to predict discourse markers between sentence pairs, we predict plausible markers between sentence pairs with a known semantic relation (provided by existing classification datasets).
no code implementations • WS 2019 • Charlotte Roze, Chlo{\'e} Braud, Philippe Muller
Discourse relation classification has proven to be a hard task, with rather low performance on several corpora that notably differ on the relation set they use.
2 code implementations • LREC 2022 • Damien Sileo, Tim Van-De-Cruys, Camille Pradel, Philippe Muller
New models for natural language understanding have recently made an unparalleled amount of progress, which has led some researchers to suggest that the models induce universal text representations.
no code implementations • JEPTALNRECITAL 2019 • Catherine Thompson, Nicholas Asher, Philippe Muller, J{\'e}r{\'e}my Auguste
Nous nous int{\'e}ressons ici {\`a} l{'}analyse de conversation par chat dans un contexte orient{\'e}-t{\^a}che avec un conseiller technique s{'}adressant {\`a} un client, o{\`u} l{'}objectif est d{'}{\'e}tiqueter les {\'e}nonc{\'e}s en actes de dialogue, pour alimenter des analyses des conversations en aval.
no code implementations • JEPTALNRECITAL 2019 • Tom Bourgeade, Philippe Muller
Les mesures de similarit{\'e} textuelle ont une place importante en TAL, du fait de leurs nombreuses applications, en recherche d{'}information et en classification notamment.
no code implementations • JEPTALNRECITAL 2019 • Damien Sileo, Tim Van De Cruys, Philippe Muller, Camille Pradel
Nous pr{\'e}sentons le syst{\`e}me utilis{\'e} par l{'}{\'e}quipe Synapse/IRIT dans la comp{\'e}tition DEFT2019 portant sur deux t{\^a}ches li{\'e}es {\`a} des cas cliniques r{\'e}dig{\'e}s en fran{\c{c}}ais : l{'}une d{'}appariement entre des cas cliniques et des discussions, l{'}autre d{'}extraction de mots-clefs.
no code implementations • WS 2019 • Philippe Muller, Chlo{\'e} Braud, Mathieu Morey
Segmentation is the first step in building practical discourse parsers, and is often neglected in discourse parsing studies.
no code implementations • SEMEVAL 2019 • Damien Sileo, Tim Van De Cruys, Camille Pradel, Philippe Muller
In this article, we show that previous work on relation prediction between texts implicitly uses compositions from baseline SRL models.
no code implementations • 4 Apr 2019 • Damien Sileo, Tim Van-De-Cruys, Camille Pradel, Philippe Muller
In this article, we show that previous work on relation prediction between texts implicitly uses compositions from baseline SRL models.
1 code implementation • NAACL 2019 • Damien Sileo, Tim Van-De-Cruys, Camille Pradel, Philippe Muller
Current state of the art systems in NLP heavily rely on manually annotated datasets, which are expensive to construct.
Ranked #1 on
Relation Classification
on Discovery Dataset
no code implementations • CL 2018 • Mathieu Morey, Philippe Muller, Nicholas Asher
This allows us to characterize families of parsing strategies across the different frameworks, in particular with respect to the notion of headedness.
no code implementations • JEPTALNRECITAL 2018 • Damien Sileo, Tim Van De Cruys, Philippe Muller, Camille Pradel
Nous pr{\'e}sentons le syst{\`e}me utilis{\'e} par l{'}{\'e}quipe Melodi/Synapse D{\'e}veloppement dans la comp{\'e}tition DEFT2018 portant sur la classification de th{\'e}matique ou de sentiments de tweets en fran{\c{c}}ais.
no code implementations • 14 Sep 2017 • Damien Sileo, Camille Pradel, Philippe Muller, Tim Van De Cruys
We present our system for the CAp 2017 NER challenge which is about named entity recognition on French tweets.
no code implementations • EMNLP 2017 • Mathieu Morey, Philippe Muller, Nicholas Asher
This article evaluates purported progress over the past years in RST discourse parsing.
no code implementations • JEPTALNRECITAL 2017 • Damien Sileo, Camille Pradel, Philippe Muller, Tim Van De Cruys
Plusieurs t{\^a}ches en traitement du langage naturel impliquent de modifier des phrases en conservant au mieux leur sens, comme la reformulation, la compression, la simplification, chacune avec leurs propres donn{\'e}es et mod{\`e}les.
no code implementations • COLING 2016 • Shafqat Mumtaz Virk, Philippe Muller, Juliette Conrath
Frame semantics is a theory of linguistic meanings, and is considered to be a useful framework for shallow semantic analysis of natural language.
no code implementations • LREC 2016 • Laure Vieu, Philippe Muller, C, Marie ito, Marianne Djemaa
We present here a general set of semantic frames to annotate causal expressions, with a rich lexicon in French and an annotated corpus of about 5000 instances of causal lexical items with their corresponding semantic frames.
no code implementations • LREC 2016 • Marianne Djemaa, C, Marie ito, Philippe Muller, Laure Vieu
This paper reports on the development of a French FrameNet, within the ASFALDA project.
no code implementations • JEPTALNRECITAL 2014 • C{\'e}cile Fabre, Nabil Hathout, Lydia-Mai Ho-Dac, Fran{\c{c}}ois Morlane-Hond{\`e}re, Philippe Muller, Franck Sajous, Ludovic Tanguy, Tim Van De Cruys
no code implementations • LREC 2014 • C, Marie ito, Pascal Amsili, Lucie Barque, Farah Benamara, Ga{\"e}l de Chalendar, Marianne Djemaa, Pauline Haas, Richard Huyghe, Yvette Yannick Mathieu, Philippe Muller, Beno{\^\i}t Sagot, Laure Vieu
The Asfalda project aims to develop a French corpus with frame-based semantic annotations and automatic tools for shallow semantic analysis.
no code implementations • 16 Jan 2014 • Xavier Tannier, Philippe Muller
Temporal information has been the focus of recent attention in information extraction, leading to some standardization effort, in particular for the task of relating events in a text.
no code implementations • LREC 2012 • Stergos Afantenos, Nicholas Asher, Farah Benamara, Myriam Bras, C{\'e}cile Fabre, Mai Ho-dac, Anne Le Draoulec, Philippe Muller, Marie-Paule P{\'e}ry-Woodley, Laurent Pr{\'e}vot, Josette Rebeyrolles, Ludovic Tanguy, Marianne Vergez-Couret, Laure Vieu
This paper describes the ANNODIS resource, a discourse-level annotated corpus for French.