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 fa...
Main Authors: | Maria Averina, Olga Levanova, Natalia Kasatkina |
---|---|
Format: | Article |
Language: | English |
Published: |
FRUCT
2022-11-01
|
Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
Subjects: | |
Online Access: | https://www.fruct.org/publications/volume-32/fruct32/files/Ave.pdf |
Similar Items
-
Deep learning with language models improves named entity recognition for PharmaCoNER
by: Cong Sun, et al.
Published: (2021-12-01) -
Named Entity Recognition in User-Generated Text: A Systematic Literature Review
by: Naji Esmaail, et al.
Published: (2024-01-01) -
PNER: Applying the Pipeline Method to Resolve Nested Issues in Named Entity Recognition
by: Hongjian Yang, et al.
Published: (2024-02-01) -
A Comparison of Approaches for Measuring the Semantic Similarity of Short Texts Based on Word Embeddings
by: Karlo Babić, et al.
Published: (2020-01-01) -
Chinese Fine‐Grained Geological Named Entity Recognition With Rules and FLAT
by: Siying Chen, et al.
Published: (2022-12-01)