---
language:
- id
license: cc-by-4.0
task_categories:
- text-retrieval
- question-answering
tags:
- legal
- indonesian-law
- knowledge-graph
- sqlite
- database
size_categories:
- 100K<n<1M
---

# Indonesian Legal Regulations - SQLite Database

## Dataset Description

This is a SQLite database version of the Indonesian Legal Regulations Knowledge Graph dataset, optimized for easy querying and integration.

### Database Statistics

- **Total Regulations**: 748,558
- **Total Embeddings**: 748,558
- **Total TF-IDF Vectors**: 748,558
- **Database Size**: 10498.50 MB

### Database Schema

#### Main Tables

1. **regulations** - Core regulation data with KG features
2. **embeddings** - 1024D semantic embeddings (BLOB storage)
3. **tfidf_vectors** - 20000D TF-IDF vectors (BLOB storage)
4. **kg_json_data** - Knowledge Graph JSON data
5. **regulations_fts** - Full-Text Search virtual table

### Features

- **Optimized Indexing**: Fast queries on common fields
- **Full-Text Search**: FTS5 for content search
- **Normalized Storage**: Separate tables for vectors
- **BLOB Storage**: Efficient storage for large vectors
- **Foreign Keys**: Referential integrity

### Usage Example

```python
import sqlite3
import numpy as np
from huggingface_hub import hf_hub_download

# Download database
db_path = hf_hub_download(
    repo_id="Azzindani/ID_REG_DB_2510",
    filename="id_regulations.db",
    repo_type="dataset"
)

# Connect
conn = sqlite3.connect(db_path)
cursor = conn.cursor()

# Query regulations
cursor.execute("""
    SELECT global_id, content, kg_authority_score 
    FROM regulations 
    WHERE regulation_type = 'UU' 
    ORDER BY year DESC 
    LIMIT 10
""")

for row in cursor.fetchall():
    print(row)

# Get embedding
cursor.execute("""
    SELECT embedding, dimension 
    FROM embeddings 
    WHERE global_id = ?
""", ('some_id',))

row = cursor.fetchone()
if row:
    embedding_blob, dim = row
    embedding = np.frombuffer(embedding_blob, dtype=np.float32)
    print(f"Embedding shape: {embedding.shape}")

# Full-text search
cursor.execute("""
    SELECT global_id, content 
    FROM regulations_fts 
    WHERE regulations_fts MATCH 'pajak OR perpajakan'
    LIMIT 10
""")

# Close
conn.close()
```

### Query Examples

#### Find regulations by domain
```sql
SELECT * FROM regulations 
WHERE kg_primary_domain = 'tax' 
ORDER BY kg_authority_score DESC;
```

#### Search content with FTS
```sql
SELECT * FROM regulations_fts 
WHERE regulations_fts MATCH 'undang-undang pajak';
```

#### Get regulation with embedding
```sql
SELECT r.*, e.embedding 
FROM regulations r
JOIN embeddings e ON r.global_id = e.global_id
WHERE r.regulation_type = 'UU' AND r.year >= 2020;
```

#### Find highly cited regulations
```sql
SELECT * FROM regulations 
WHERE kg_pagerank > 0.001 
ORDER BY kg_pagerank DESC 
LIMIT 20;
```

### Source Dataset

This database was created from: `Azzindani/ID_REG_KG_2511`

### License

CC-BY-4.0

### Citation

```bibtex
@dataset{indonesian_legal_db_2024,
  author = {Azzindani},
  title = {Indonesian Legal Regulations - SQLite Database},
  year = {2024},
  publisher = {HuggingFace},
  url = {https://huggingface.co/datasets/Azzindani/ID_REG_DB_2511}
}
```