POPCORN (POPCORN: Fictional and Synthetic Intelligence Reports for Named Entity Recognition and Relation Extraction Tasks)

POPCORN is a French dataset consisting of 400 validation texts and 400 training texts, all written and annotated manually. The texts are concise and factual, resembling information reports. The annotations, based on the ontology described below, allow for the training and evaluation of models in Information Extraction tasks, including Named Entity Recognition, Coreference Resolution, and Relation Extraction.

Additionally, 400 more texts have been provided for the TextMine 2025 challenge on Relation Extraction, which can be accessed via the following link: https://www.kaggle.com/competitions/defi-text-mine-2025/