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Ru Patents Ner
R
Ru Patents Ner
Developed by Delicalib
This is a Russian patent named entity recognition model based on the spaCy framework, focusing on identifying specific entity types in patent texts.
Downloads 37
Release Time : 3/16/2025
Model Overview
This model is primarily used to process Russian patent texts and can identify and classify three types of entities in patents: systems, components, and attributes.
Model Features
Patent Text Optimization
Specially trained for Russian patent texts, it has strong entity recognition capabilities in the patent domain.
Multi-category Recognition
Can identify three types of entities in patent texts: SYSTEM, COMPONENT, and ATTRIBUTE.
spaCy Integration
Built on the popular spaCy framework, making it easy to integrate into existing NLP workflows.
Model Capabilities
Russian Text Processing
Patent Entity Recognition
Multi-category Entity Classification
Use Cases
Intellectual Property Analysis
Patent Information Extraction
Automatically extracts key system, component, and attribute information from Russian patent documents.
F1 score reaches 60.66%
Patent Database Construction
Automatically processes large volumes of Russian patent texts to build structured patent databases.
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