README.md

---
license: mit
tags:
  - knowledge-graph
  - hypergraph
  - legal-evidence
  - graph-neural-network
  - unicosys
language:
  - en
library_name: transformers
pipeline_tag: graph-ml
---

# Unicosys Hypergraph Knowledge Model

A trainable knowledge graph embedding model encoding the unified evidence
hypergraph for Case 2025-137857.

## Model Description

This model encodes a **unified hypergraph** linking financial transactions,
email communications, legal evidence, and entity relationships into a
single trainable knowledge representation.

### Architecture

| Component | Details |
|---|---|
| Node Embedding | 128-dim structural + 256-dim text |
| Hidden Dimension | 256 |
| Text Encoder | 2-layer Transformer, 4 heads |
| Graph Attention | 2-layer GAT, 4 heads |
| Link Predictor | 2-layer MLP with margin ranking loss |
| Total Parameters | **36,023,937** |

### Knowledge Graph Statistics

| Metric | Count |
|---|---|
| Total Nodes | 300,843 |
| Total Edges | 14,439 |
| Cross-Links | 3,628 |
| Entities | 16 |
| Emails | 199,217 |
| Financial Documents | 12,103 |
| Timeline Events | 59,955 |
| LEX Schemes | 13 |
| Legal Filings | 5 |

### Subsystems

| Subsystem | Nodes |
|---|---|
| Core (Entities) | 16 |
| Fincosys (Financial) | 101,429 |
| Comcosys (Communications) | 199,217 |
| RevStream1 (Evidence) | 150 |
| Ad-Res-J7 (Legal) | 31 |

## Training

The model can be fine-tuned on link prediction tasks:

```python
from model.unicosys_model import UnicosysHypergraphModel, UnicosysConfig

model = UnicosysHypergraphModel.from_pretrained("hyperholmes/unicosys-hypergraph")
# ... prepare training data ...
# model.forward(node_ids, node_type_ids, subsystem_ids, edge_index, edge_type_ids,
#               pos_edge_index=pos, neg_edge_index=neg, labels=labels)
```

## Files

- `model.safetensors` — Model weights
- `config.json` — Model configuration
- `graph_data.safetensors` — Encoded graph tensors (nodes, edges)
- `tokenizer.json` — Character-level tokenizer for node labels
- `node_id_mapping.json` — Node ID string to integer index mapping
- `model_summary.json` — Compact statistics summary

## Source

Generated by the [Unicosys](https://github.com/hyperholmes/unicosys) intelligence pipeline.