俄罗斯司法判决书文本的命名实体识别

2022 32nd Conference of Open Innovations Association (FRUCT) Pub Date : 2022-11-09 DOI:10.23919/FRUCT56874.2022.9953892

M. Averina, O.V. Levanova, Natalia Kasatkina

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引用次数: 0

摘要

本文提出了俄文合法文本的命名实体识别问题的解决方案。我们研究了CRF、LSTM、BERT和BiLSTM及其组合。用文本预处理和词向量表示的各种参数对模型进行了测试。采用BiLSTM和CRF模型进行快速文本矢量化效果最好，F-score为0.86。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Named Entity Recognition for Russian Judicial Rulings Text

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.

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2022 32nd Conference of Open Innovations Association (FRUCT)

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