On the Assessment of Deep Learning Models for Named Entity Recognition of Brazilian Legal Documents
Authors:
- Hidelberg O. AlbuquerqueHAHidelberg O. Albuquerque
- Ellen SouzaEllen Souza
- Adriano L. I. OliveiraAdriano L. I. Oliveira
- David MacêdoDMDavid Macêdo
- Cleber ZanchettinCleber Zanchettin
- Douglas VitórioDVDouglas Vitório
- Nádia F. F. da SilvaNSNádia F. F. da Silva
- André C. P. L. F. de CarvalhoACAndré C. P. L. F. de Carvalho
- 15 December 2023
- book chapter
- Published by Springer Nature
- p. 93-104
Abstract
No abstract availableKeywords
This publication has 10 references indexed in Scilit:
- Expanding UlyssesNER-Br Named Entity Recognition Corpus with Informal User-Generated Text2022
- UlyssesNER-Br: A Corpus of Brazilian Legislative Documents for Named Entity Recognition2022
- Text Classification in Legal Documents Extracted from Lawsuits in Brazilian Courts2021
- A Study on the Impact of Intradomain Finetuning of Deep Language Models for Legal Named Entity Recognition in Portuguese2020
- LeNER-Br: A Dataset for Named Entity Recognition in Brazilian Legal Text2018
- A Review of Machine Learning and Deep Learning Applications2018
- Natural Language Processing for the Semantic WebSynthesis Lectures on the Semantic Web: Theory and Technology, 2016
- Deep learning in neural networks: An overviewNeural Networks, 2015
- A Golden Resource for Named Entity Recognition in Portuguese2006
- Introduction to the CoNLL-2002 shared task2002