arXiv:1705.05487

NeuroNER: an easy-to-use program for named-entity recognition based on neural networks

Franck Dernoncourt, Ji Young Lee, Peter Szolovits

제출 2017-05-16

원문 초록

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 easy-to-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 annotation-training-prediction flow smooth and accessible to anyone.

함께 살펴볼 논문

공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.

arXiv:2504.16007공통 태그 Named Entity Recognition (NER), NER, named-entity-recognition, Named Entity Recognition공식 코드 · Papers with Code

Methods for Recognizing Nested Terms

토론

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