---
language:
- en
- fr
- es
- de
- it
- pt
- zh
- ar
- ru
tags:
- text-classification
- intent-classification
- enterprise-ai
- voice-ai
- multilingual
- distilbert
license: mit
---

# ConceptNet Intent Classifier

Fine-tuned `distilbert-base-multilingual-cased` on the ConceptNet 4-layer enterprise voice intent taxonomy.

## Accuracy
- Standard test set: **100%** (epochs 4 and 5)
- Adversarial holdout: **99.3%** (independently verified — Hugging Face community)
- Fast-path classifier: **83%** · <5ms latency
- Dataset: 757 examples across 9 languages

## Independent Evaluation
Independently tested by the Hugging Face community (john6666):
- Confirmed 99.315% on reconstructed public test split
- Grouped lexical-family holdout: 99.78%
- Conclusion: "The obvious train/test leakage explanation did not survive that check"
- All 4 identified improvements implemented within 24 hours

## Cascade Performance
| Threshold | Fast coverage | Fast accuracy | Final accuracy |
|-----------|--------------|---------------|----------------|
| 0.50 | 69.2% | 95.0% | 95.9% |
| 0.55 | 60.3% | 98.9% | 99.3% |
| 0.65 | 43.2% | 100% | 100% |

## Layer Precedence
Mixed semantics: **L4 > L3 > L2 > L1**

## The 4 Layers
- **L1 Basic** — "Do X" — immediate execution
- **L2 Context-Aware** — "Do X when Y" — conditional
- **L3 Predictive** — "Do X before/ahead of/prior to Y" — proactive
- **L4 Autonomous** — "Do X always" — persistent agent

## Languages
English · French · Spanish · German · Italian · Portuguese · Chinese · Arabic · Russian

## Usage
```python
from transformers import pipeline
classifier = pipeline("text-classification", model="conceptnetUk/intent-classifier")
classifier("Send the report when the contract is signed")
```

## Links
- Sandbox: https://conceptnet.co.uk/sandbox/
- GitHub: https://github.com/wushu75/ConceptNet
- Website: https://conceptnet.co.uk

*© 2026 ConceptNet Ltd · Patents pending*