no code implementations • ACL 2020 • Rapha{\"e}l Bailly, Kata G{\'a}bor
This paper is a theoretical contribution to the debate on the learnability of syntax from a corpus without explicit syntax-specific guidance.
no code implementations • SEMEVAL 2018 • Kata G{\'a}bor, Davide Buscaldi, Anne-Kathrin Schumann, Behrang Qasemizadeh, Ha{\"\i}fa Zargayouna, Thierry Charnois
This paper describes the first task on semantic relation extraction and classification in scientific paper abstracts at SemEval 2018.
no code implementations • EMNLP 2017 • Kata G{\'a}bor, Ha{\"\i}fa Zargayouna, Isabelle Tellier, Davide Buscaldi, Thierry Charnois
Word embeddings are used with success for a variety of tasks involving lexical semantic similarities between individual words.
no code implementations • JEPTALNRECITAL 2016 • Kata G{\'a}bor, Isabelle Tellier, Thierry Charnois, Ha{\"\i}fa Zargayouna, Davide Buscaldi
Une analyse manuelle nous a permis de proposer une typologie des relations s{\'e}mantiques, et de classifier un {\'e}chantillon d{'}instances de relations.
no code implementations • LREC 2016 • Kata G{\'a}bor, Ha{\"\i}fa Zargayouna, Davide Buscaldi, Isabelle Tellier, Thierry Charnois
This paper describes the process of creating a corpus annotated for concepts and semantic relations in the scientific domain.
no code implementations • LREC 2012 • Kata G{\'a}bor, Marianna Apidianaki, Beno{\^\i}t Sagot, {\'E}ric Villemonte de la Clergerie
In this article, we present a distributional analysis method for extracting nominalization relations from monolingual corpora.