|Titre||FrSemCor: Annotating a French Corpus with Supersenses|
|Publication Type||Article dans des actes|
|Année de la conférence||2020|
|Authors||Barque, Lucie, Richard Huyghe, Delphine Tribout, Marie Candito, Benoît Crabbé, and Vincent Segonne|
|Nom de la conférence||Proceedings of the Twelfth Language Resources and Evaluation Conference|
|Publisher||European Language Resources Association|
|Conference Location||Marseille, France|
French, as many languages, lacks semantically annotated corpus data. Our aim is to provide the linguistic and NLP research communities with a gold standard sense-annotated corpus of French, using WordNet Unique Beginners as semantic tags, thus allowing for interoperability. In this paper, we report on the first phase of the project, which focused on the annotation of common nouns. The resulting dataset consists of more than 12,000 French noun occurrences which were annotated in double blind and adjudicated according to a carefully redefined set of supersenses. The resource is released online under a Creative Commons Licence.