Create README.md

README.md

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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}
+}
+```