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+# NER Benchmark Results
+**Model:** Minibase-NER-Standard
+**Dataset:** ner_benchmark_dataset.jsonl
+**Sample Size:** 100
+**Date:** 2025-10-07T13:41:36.866891
+
+## Overall Performance
+
+| Metric | Score | Description |
+|--------|-------|-------------|
+| F1 Score | 0.951 | Overall NER performance (harmonic mean of precision and recall) |
+| Precision | 0.915 | Accuracy of entity predictions |
+| Recall | 1.000 | Ability to find all entities |
+| Average Latency | 323.3ms | Response time performance |
+
+## Entity Type Performance
+
+| Entity Type | Accuracy | Correct/Total |
+|-------------|----------|---------------|
+| PERSON | 1.000 | 100/100 |
+| ORG | 1.000 | 100/100 |
+| LOC | 0.660 | 66/100 |
+| MISC | 1.000 | 34/34 |
+
+## Key Improvements
+
+- **BIO Tagging**: Model outputs entities in BIO (Beginning-Inside-Outside) format
+- **Multiple Entity Types**: Supports PERSON, ORG, LOC, and MISC entities
+- **Entity-Level Evaluation**: Metrics calculated at entity level rather than token level
+- **Comprehensive Coverage**: Evaluates across different text domains
+
+## Example Results
+
+### Example 1
+**Input:** John Smith works at Google in New York and uses Python programming language....
+**Predicted:** { "PER": ["John Smith"], "ORG": ["Google"], "LOC": ["New York"], "MISC": ["Python"] }...
+**F1 Score:** 0.857
+
+### Example 2
+**Input:** Microsoft Corporation announced that Satya Nadella will visit London next week....
+**Predicted:** { "PER": ["Satya Nadella"], "ORG": ["Microsoft Corporation"], "LOC": ["London"], "MISC": [] }...
+**F1 Score:** 1.000
+
+### Example 3
+**Input:** The University of Cambridge is located in the United Kingdom and was founded by King Henry III....
+**Predicted:** { "PER": ["King Henry III"], "ORG": ["University of Cambridge"], "LOC": ["United Kingdom"], "MISC": [] }...
+**F1 Score:** 1.000
+