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---
license: cc-by-4.0
pretty_name: ConceptNet 5 (Un-normalized SQLite, Full Archive)
multilinguality: multilingual
tags:
- conceptnet
- knowledge-graph
- sqlite
- un-normalized
- archival
- all-languages
---
# ConceptNet 5 (Un-normalized SQLite, 23.6 GB)
This repository contains the complete, un-normalized ConceptNet 5.5 knowledge graph in SQLite format. Unlike the filtered version, this dataset includes **all languages** from the original ConceptNet release.
The database `conceptnet-de-indexed.db` is a 23.6 GB un-normalized SQLite file containing the full knowledge graph with all 28.3 million nodes and 34 million edges across all languages.
## When to Use This Dataset
**Use this dataset if you:**
- Need access to **all languages** in ConceptNet (not just the 11 languages in the normalized version)
- Require the complete, unfiltered knowledge graph
- Are doing cross-linguistic research across many language pairs
- Need the original data structure for compatibility reasons
**Use the normalized version ([cstr/conceptnet-normalized-multi](https://huggingface.co/datasets/cstr/conceptnet-normalized-multi)) if you:**
- Only need 11 specific languages (en, fr, it, de, es, ar, fa, grc, he, la, hbo)
- Want faster query performance (normalized schema with integer keys)
- Need a smaller file size (~1.8 GB vs 23.6 GB)
- Prefer optimized, production-ready data
## Dataset Description
This repository contains the `conceptnet-de-indexed.db` file, a large (23.6 GB) SQLite database of the ConceptNet 5.5 knowledge graph.
- **Nodes**: The `node` table contains 28.3 million nodes from all ConceptNet languages.
- **Edges**: The `edge` table contains 34 million un-filtered edges.
- **Schema**: This database is un-normalized. The `edge` table stores full text URLs for its `start_id`, `end_id`, and `rel_id` columns, resulting in its large size and slower query performance compared to normalized alternatives.
- **Data Quality**: This database contains all original edges, including both high-quality assertions (e.g., `hund IsA raubtier`) and low-quality metadata (e.g., `hund IsA n`).
## Database Schema
### node (28.3M rows)
- `id` (VARCHAR): The full ConceptNet URL (e.g., `/c/en/dog/n`).
- `label` (VARCHAR): The human-readable label.
- `language` (VARCHAR): The language code (e.g., `en`, `de`).
- `sense_label` (VARCHAR): e.g., `n`, `v`.
- `term_id` (VARCHAR): The URL without the POS tag (e.g., `/c/en/dog`).
- ...and other metadata columns.
### relation (50 rows)
- `id` (VARCHAR): The relation URL (e.g., `/r/IsA`).
- `label` (VARCHAR): The relation name (e.g., `IsA`).
- `symmetric` (BOOLEAN): If the relation is symmetric.
### edge (34M rows)
- `id` (VARCHAR): The unique edge URL.
- `rel_id` (VARCHAR): Foreign key (as text URL) to `relation.id`.
- `start_id` (VARCHAR): Foreign key (as text URL) to `node.id`.
- `end_id` (VARCHAR): Foreign key (as text URL) to `node.id`.
- `weight` (FLOAT): The edge weight.
- ...and other metadata columns.
## Example Query
**Note**: Queries on this un-normalized database use text-based keys and may be slower than the normalized version.
```python
import sqlite3
import pandas as pd
DB_PATH = "conceptnet-de-indexed.db" # Or path from hf_hub_download
conn = sqlite3.connect(f"file:{DB_PATH}?mode=ro", uri=True)
query = """
SELECT
e.start_id,
e.end_id,
e.weight
FROM edge e
WHERE
e.start_id LIKE 'http://conceptnet.io/c/de/hund%'
AND e.rel_id = 'http://conceptnet.io/r/IsA'
ORDER BY e.weight DESC
LIMIT 10;
"""
df = pd.read_sql_query(query, conn)
print(df)
conn.close()
```
## Original Dataset Information
This work includes data from ConceptNet 5, which was compiled by the Commonsense Computing Initiative. ConceptNet 5 is freely available under the Creative Commons Attribution-ShareAlike license (CC BY SA 4.0) from http://conceptnet.io.
For a full list of licenses and attributions for included resources such as WordNet, Open Multilingual WordNet, and Wikimedia projects, please see the original dataset card.
## Citation Information
If you use this data in your work, please cite the original ConceptNet 5.5 paper:
```bibtex
@inproceedings{speer2017conceptnet,
author = {Robyn Speer and Joshua Chin and Catherine Havasi},
title = {ConceptNet 5.5: An Open Multilingual Graph of General Knowledge},
booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
year = {2017},
pages = {4444--4451},
url = {http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14972}
}
``` |