학술논문
Named Entity Recognition for Russian Judicial Rulings Text
Document Type
Conference
Source
2022 32nd Conference of Open Innovations Association (FRUCT) Open Innovations Association (FRUCT), 2022 32nd Conference of. :49-55 Nov, 2022
Subject
Language
ISSN
2305-7254
Abstract
The article presents the solution of named entity recognition problem for legal Russian-language texts. We studied CRF, LSTM, BERT and BiLSTM and their combinations. The models were tested with various parameters of text preprocessing and words vector representations. The best result was shown by fastext vectorization with BiLSTM and CRF model, the value $F-score$ is 0.86.