Over the last several years, the field of natural language processing has been propelled
forward by an explosion in the use of deep learning models. This article provides a brief …

Textual information is becoming available in abundance on the web, arising the requirement
of techniques and tools to extract the meaningful information. One of such an important …

Recent advances in language representation using neural networks have made it viable to
transfer the learned internal states of a trained model to downstream natural language …

This survey covers fifteen years of research in the Named Entity Recognition and
Classification (NERC) field, from 1991 to 2006. We report observations about languages …

This paper presents an extended overview of the first edition of HIPE (Identifying Historical
People, Places and other Entities), a pioneering shared task dedicated to the evaluation of …

Recent advances in language representation using neural networks have made it viable to
transfer the learned internal states of large pretrained language models (LMs) to …

In natural language processing (NLP), there is a need for more resources in Portuguese,
since much of the data used in the state-of-the-art research is in other languages. In this …

Identifying named entities such as a person, location or organization, in documents can
highlight key information to readers. Training Named Entity Recognition (NER) models …

Named Entity Recognition (NER) aims to extract and to classify rigid designators in text such
as proper names, biological species, and temporal expressions. There has been growing …

Le traitement des entités nommées fait aujourd'hui figure d'incontournable en Traitement
Automatique des Langues. Apparue au milieu des années 1990 à la faveur des dernières …