Enterprise NER Intelligence (CoNLL-2003)
Named Entity Recognition with BERT achieving 92% F1-score for financial, legal, and healthcare applications
Technology Stack
ROI
Document automation
Accuracy
91% precision, 93% recall
Key Performance Indicators
Business Impact Summary
| Return on Investment | Document automation |
| Model Accuracy | 91% precision, 93% recall |
| BERT vs Bi-LSTM | 92% vs 65% |
| Entity Types | PER, ORG, LOC, MISC |
| Confidence Scoring | Probabilistic outputs |
Overview
Production-ready Named Entity Recognition system with BERT Transformers and Bi-LSTM-CRF for extracting structured insights from unstructured text. Industry-specific modules for finance, legal, healthcare, and HR.
Live Demo
Live Demo
Interactive Streamlit application
Enterprise NER Intelligence (CoNLL-2003) Demo
Click below to load the interactive demo
This is a live, interactive demo deployed on Streamlit Cloud. You can:
- •Upload your own data for predictions
- •Explore model performance metrics
- •View interactive visualizations
- •Understand model predictions with explainability
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