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Ner4legal SRB

Developed by kalusev
A named entity recognition model optimized for Serbian legal documents, fine-tuned based on BERT architecture, used for automatically extracting key entity information from legal texts.
Downloads 54
Release Time : 2/14/2025

Model Overview

This model is specifically designed to identify predefined entity categories in Serbian legal documents, supporting automated tasks such as document archiving and retrieval. It is suitable for users such as lawyers, law firms, and government agencies.

Model Features

Legal Domain Optimization
Trained specifically for Serbian legal documents, it can accurately identify specific entity categories in legal texts.
High-precision Performance
Achieves an average F1 score of 0.96 in cross-validation, demonstrating excellent performance.
Robustness Validation
Verified through adversarial text testing to ensure stability under noisy inputs.

Model Capabilities

Legal Text Entity Recognition
Serbian Language Processing
Court Ruling Analysis

Use Cases

Legal Document Processing
Court Ruling Archiving
Automatically identifies key information such as court names and case numbers in ruling documents.
Improves document classification and retrieval efficiency.
Legal Information Extraction
Extracts structured data such as involved parties and judgment results from legal documents.
Supports legal analysis and research.
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