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--- |
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language: |
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- id |
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license: cc-by-4.0 |
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task_categories: |
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- text-retrieval |
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- question-answering |
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tags: |
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- legal |
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- indonesian-law |
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- knowledge-graph |
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- sqlite |
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- database |
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size_categories: |
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- 100K<n<1M |
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--- |
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# Indonesian Legal Regulations - SQLite Database |
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## Dataset Description |
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This is a SQLite database version of the Indonesian Legal Regulations Knowledge Graph dataset, optimized for easy querying and integration. |
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### Database Statistics |
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- **Total Regulations**: 748,558 |
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- **Total Embeddings**: 748,558 |
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- **Total TF-IDF Vectors**: 748,558 |
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- **Database Size**: 10498.50 MB |
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### Database Schema |
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#### Main Tables |
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1. **regulations** - Core regulation data with KG features |
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2. **embeddings** - 1024D semantic embeddings (BLOB storage) |
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3. **tfidf_vectors** - 20000D TF-IDF vectors (BLOB storage) |
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4. **kg_json_data** - Knowledge Graph JSON data |
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5. **regulations_fts** - Full-Text Search virtual table |
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### Features |
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- **Optimized Indexing**: Fast queries on common fields |
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- **Full-Text Search**: FTS5 for content search |
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- **Normalized Storage**: Separate tables for vectors |
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- **BLOB Storage**: Efficient storage for large vectors |
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- **Foreign Keys**: Referential integrity |
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### Usage Example |
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```python |
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import sqlite3 |
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import numpy as np |
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from huggingface_hub import hf_hub_download |
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# Download database |
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db_path = hf_hub_download( |
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repo_id="Azzindani/ID_REG_DB_2510", |
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filename="id_regulations.db", |
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repo_type="dataset" |
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) |
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# Connect |
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conn = sqlite3.connect(db_path) |
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cursor = conn.cursor() |
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# Query regulations |
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cursor.execute(""" |
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SELECT global_id, content, kg_authority_score |
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FROM regulations |
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WHERE regulation_type = 'UU' |
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ORDER BY year DESC |
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LIMIT 10 |
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""") |
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for row in cursor.fetchall(): |
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print(row) |
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# Get embedding |
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cursor.execute(""" |
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SELECT embedding, dimension |
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FROM embeddings |
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WHERE global_id = ? |
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""", ('some_id',)) |
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row = cursor.fetchone() |
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if row: |
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embedding_blob, dim = row |
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embedding = np.frombuffer(embedding_blob, dtype=np.float32) |
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print(f"Embedding shape: {embedding.shape}") |
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# Full-text search |
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cursor.execute(""" |
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SELECT global_id, content |
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FROM regulations_fts |
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WHERE regulations_fts MATCH 'pajak OR perpajakan' |
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LIMIT 10 |
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""") |
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# Close |
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conn.close() |
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``` |
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### Query Examples |
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#### Find regulations by domain |
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```sql |
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SELECT * FROM regulations |
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WHERE kg_primary_domain = 'tax' |
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ORDER BY kg_authority_score DESC; |
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``` |
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#### Search content with FTS |
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```sql |
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SELECT * FROM regulations_fts |
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WHERE regulations_fts MATCH 'undang-undang pajak'; |
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``` |
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#### Get regulation with embedding |
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```sql |
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SELECT r.*, e.embedding |
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FROM regulations r |
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JOIN embeddings e ON r.global_id = e.global_id |
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WHERE r.regulation_type = 'UU' AND r.year >= 2020; |
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``` |
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#### Find highly cited regulations |
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```sql |
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SELECT * FROM regulations |
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WHERE kg_pagerank > 0.001 |
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ORDER BY kg_pagerank DESC |
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LIMIT 20; |
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``` |
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### Source Dataset |
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This database was created from: `Azzindani/ID_REG_KG_2511` |
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### License |
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CC-BY-4.0 |
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### Citation |
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```bibtex |
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@dataset{indonesian_legal_db_2024, |
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author = {Azzindani}, |
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title = {Indonesian Legal Regulations - SQLite Database}, |
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year = {2024}, |
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publisher = {HuggingFace}, |
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url = {https://huggingface.co/datasets/Azzindani/ID_REG_DB_2511} |
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} |
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``` |
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