Search Results for author: Anne-Lyse Minard

Found 13 papers, 1 papers with code

DOING@DEFT : utilisation de lexiques pour une classification efficace de cas cliniques (In this paper, we present our participation to the DEFT 2021 task 1)

no code implementations JEP/TALN/RECITAL 2021 Nicolas Hiot, Anne-Lyse Minard, Flora Badin

Nous présentons dans cet article notre participation à la tâche 1 de la campagne d’évaluation francophone DEFT 2021, sur l’identification du profil clinique du patient.

DOING@DEFT : cascade de CRF pour l'annotation d'entit\'es cliniques imbriqu\'ees (DOING@DEFT : cascade of CRF for the annotation of nested clinical entities)

no code implementations JEPTALNRECITAL 2020 Anne-Lyse Minard, Andr{\'e}ane Roques, Nicolas Hiot, Mirian Halfeld Ferrari Alves, Agata Savary

Cet article pr{\'e}sente le syst{\`e}me d{\'e}velopp{\'e} par l{'}{\'e}quipe DOING pour la campagne d{'}{\'e}valuation DEFT 2020 portant sur la similarit{\'e} s{\'e}mantique et l{'}extraction d{'}information fine.

Participation de l'IRISA \`a DeFT 2018 : classification et annotation d'opinion dans des tweets (IRISA at DeFT 2018: classifying and tagging opinion in tweets )

no code implementations JEPTALNRECITAL 2018 Anne-Lyse Minard, Christian Raymond, Vincent Claveau

L{'}{\'e}quipe a particip{\'e} {\`a} 3 des 4 t{\^a}ches de la campagne : (i) classification des tweets selon s{'}ils concernent les transports ou non, (ii) classification des tweets selon leur polarit{\'e} et (iii) annotation des marqueurs d{'}opinion et de l{'}objet {\`a} propos duquel est exprim{\'e}e l{'}opinion.

The Scope and Focus of Negation: A Complete Annotation Framework for Italian

no code implementations WS 2017 Bego{\~n}a Altuna, Anne-Lyse Minard, Manuela Speranza

In this paper we present a complete framework for the annotation of negation in Italian, which accounts for both negation scope and negation focus, and also for language-specific phenomena such as negative concord.

Decision Making Sentiment Analysis

TextPro-AL: An Active Learning Platform for Flexible and Efficient Production of Training Data for NLP Tasks

no code implementations COLING 2016 Bernardo Magnini, Anne-Lyse Minard, Mohammed R. H. Qwaider, Manuela Speranza

This paper presents TextPro-AL (Active Learning for Text Processing), a platform where human annotators can efficiently work to produce high quality training data for new domains and new languages exploiting Active Learning methodologies.

Active Learning Domain Adaptation

The Event and Implied Situation Ontology (ESO): Application and Evaluation

no code implementations LREC 2016 Roxane Segers, Marco Rospocher, Piek Vossen, Egoitz Laparra, German Rigau, Anne-Lyse Minard

This paper presents the Event and Implied Situation Ontology (ESO), a manually constructed resource which formalizes the pre and post situations of events and the roles of the entities affected by an event.

MEANTIME, the NewsReader Multilingual Event and Time Corpus

no code implementations LREC 2016 Anne-Lyse Minard, Manuela Speranza, Ruben Urizar, Bego{\~n}a Altuna, Marieke van Erp, Anneleen Schoen, Chantal van Son

The {``}First CLIN Dutch Shared Task{''} at CLIN26 was based on the Dutch section, while the EVALITA 2016 FactA (Event Factuality Annotation) shared task, based on the Italian section, is currently being organized.

Document-level Semantic Role Labeling

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