NeuroNER: an easy-to-use program for named-entity recognition based on neural networks
Franck Dernoncourt, Ji Young Lee, Peter Szolovits · 2017
Named-entity recognition (NER) aims at identifying entities of interest in a text.Artificial neural networks (ANNs) have recently been shown to outperform existing NER systems.However, ANNs remain challenging to use for non-expert users.In this paper, we present NeuroNER, an easyto-use named-entity recognition tool based on ANNs.Users can annotate entities using a graphical web-based user interface (BRAT): the annotations are then used to train an ANN, which in turn predict entities' locations and categories in new texts.NeuroNER makes this annotationtraining-prediction flow smooth and accessible to anyone.