--- 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} } ```