CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation:
- ATOMIC
- ConceptNet
- FrameNet
- Roget
- Visual Genome
- Wikidata (We use the Wikidata-CS subset)
- WordNet
CSKG is represented as a hyper-relational graph, by using the KGTK data model and file specification. Its creation is entirely supported by KGTK operations.
CSKG is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
- CSKG embeddings on google drive
- CSKG is integrated into PyKeen which allows easy computation of various (currently 25) state-of-the-art graph embeddings
- Tutorial on Commonsense Knowledge Graphs (ISWC'20)
- Tutorial on Commonsense Knowledge Acquisition and Representation (AAAI'21)
- Workshop on Commonsense Knowledge Graphs (AAAI'21)
- Setup your conda environment
conda create --name mowgli --file requirements.txt
conda activate mowgli
-
Download and store individual sources, except WordNet and FrameNet. By default, these should be stored in the
input
directory. -
Download the
mappings
from this folder and place them inside theinput
directory -
Customize and run create_cskg.sh.
@article{ilievski2021cskg,
title={CSKG: The CommonSense Knowledge Graph},
author={Ilievski, Filip and Szekely, Pedro and Zhang, Bin},
journal={Extended Semantic Web Conference (ESWC)},
year={2021}
}