Named Entity Recognition for French medieval charters - Archive ouverte HAL Access content directly
Conference Papers Year : 2021

Named Entity Recognition for French medieval charters

Sergio Torres Aguilar


This paper presents the process of annotating and modelling a corpus to automatically detect named entities in medieval charters in French. It introduces a new annotated corpus and a new system which outperforms state-of-the art libraries. Charters are legal documents and among the most important historical sources for medieval studies as they reflect economic and social dynamics as well as the evolution of literacy and writing practices. Automatic detection of named entities greatly improves the access to these unstructured texts and facilitates historical research. The experiments described here are based on a corpus encompassing about 500k words (1200 charters) coming from three charter collections of the 13th and 14th centuries. We annotated the corpus and then trained two state-of-the art NLP libraries for Named Entity Recognition (Spacy and Flair) and a custom neural model (Bi-LSTM-CRF). The evaluation shows that all three models achieve a high performance rate on the test set and a high generalization capacity against two external corpora unseen during training. This paper describes the corpus and the annotation model, and discusses the issues related to the linguistic processing of medieval French and formulaic discourse, so as to interpret the results within a larger historical perspective.
Fichier principal
Vignette du fichier
ACL_2020_French_charters_NER_cameraready2.pdf (457.65 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03503055 , version 1 (27-12-2021)


Attribution - NonCommercial


  • HAL Id : hal-03503055 , version 1


Sergio Torres Aguilar, Dominique Stutzmann. Named Entity Recognition for French medieval charters. Workshop on Natural Language Processing for Digital Humanities, Dec 2021, Helsinki, Finland. ⟨hal-03503055⟩
187 View
411 Download


Gmail Facebook X LinkedIn More