Spanish Datasets for Sensitive Entity Detection in the Legal Domain

no code implementations • LREC 2022 • Ona de Gibert Bonet, Aitor García Pablos, Montse Cuadros, Maite Melero

In order to assess the quality of the generated datasets, we have used them to fine-tune a battery of entity-detection models, using as foundation different pre-trained language models: one multilingual, two general-domain monolingual and one in-domain monolingual.

De-identification

MAPA Project: Ready-to-Go Open-Source Datasets and Deep Learning Technology to Remove Identifying Information from Text Documents

no code implementations • LEGAL (LREC) 2022 • Victoria Arranz, Khalid Choukri, Montse Cuadros, Aitor García Pablos, Lucie Gianola, Cyril Grouin, Manuel Herranz, Patrick Paroubek, Pierre Zweigenbaum

This paper presents the outcomes of the MAPA project, a set of annotated corpora for 24 languages of the European Union and an open-source customisable toolkit able to detect and substitute sensitive information in text documents from any domain, using state-of-the art, deep learning-based named entity recognition techniques.

De-identification named-entity-recognition +2