| --- |
| title: Normalized ConceptNet Explorer |
| emoji: ⚡ |
| colorFrom: green |
| colorTo: blue |
| sdk: gradio |
| sdk_version: 5.49.1 |
| app_file: app.py |
| pinned: true |
| license: cc-by-sa-4.0 |
| tags: |
| - conceptnet |
| - knowledge-graph |
| - sqlite |
| - normalized |
| - gradio |
| - fast-queries |
| --- |
| |
| # ⚡ Normalized ConceptNet Explorer (V7) |
|
|
| This application is a high-performance explorer for a normalized, filtered, and optimized version of the ConceptNet 5.5 knowledge graph. |
|
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| It is designed to be **extremely fast**, returning queries in milliseconds instead of minutes. It queries a 1.78 GB optimized SQLite database with integer-based joins, not the 23.6 GB un-normalized file. |
|
|
| ## Features |
|
|
| This app provides a full suite of tools to explore the normalized database: |
|
|
| - **⚡ Semantic Profile**: Explore relations for any word in real-time. This now runs in ~4 fast SQL queries instead of 24+ slow ones. |
| - **⚡ Query Builder**: Build custom queries (start node, relation, end node) that are executed with fast, integer-based joins. |
| - **⚡ Raw SQL**: Execute SQL queries directly against the new, normalized database schema (see schema below). |
| - **⚡ Schema**: Browse the new, efficient database schema, including all tables, indexes, and row counts. |
|
|
| ## How It Works: The Normalized Database |
|
|
| This app's speed and correctness come from the new database it queries: [cstr/conceptnet-normalized-multi](https://huggingface.co/datasets/cstr/conceptnet-normalized-multi). |
|
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| This database was created by a V7 normalization script that fixed critical issues found in the original data: |
|
|
| 1. **Normalization (Speed & Size)**: The original 23.6 GB `edge` table (34M rows) was bloated with text URLs. The new 1.78 GB `edge_norm` table replaces these with tiny integer foreign keys. |
|
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| 2. **Data Correctness (V7 Fix)**: The original `node` table (28M rows) was used as the source of truth. We migrated all 28M nodes and their authoritative `language` columns. |
|
|
| 3. **Preserves Cross-Language Links**: The 34M edges were filtered to keep any edge where at least one node (start or end) was in our 11 target languages (`en`, `de`, `fr`, `it`, `es`, `ar`, `fa`, `grc`, `he`, `la`, `hbo`). This is critical, as it correctly preserves cross-language connections (e.g., `犬 (ja) -> hund (de)`), which were broken in previous attempts. |
|
|
| The result is a clean, fast, and data-correct database that contains all relevant connections for our target languages. |
|
|
| ## Supported Languages |
|
|
| This normalized version includes edges for 11 languages: |
| - English (en) |
| - German (de) |
| - French (fr) |
| - Italian (it) |
| - Spanish (es) |
| - Arabic (ar) |
| - Persian (fa) |
| - Ancient Greek (grc) |
| - Hebrew (he) |
| - Latin (la) |
| - Biblical Hebrew (hbo) |
|
|
| Cross-language connections from other languages to these target languages are preserved. |
|
|
| ## 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. |
|
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| 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} |
| } |
| ``` |
