Knowledge Base Completion (kbc)
This code reproduces results in Tensor Decompositions for Temporal Knowledge Base Completion (ICLR 2020).
Installation
Create a conda environment with pytorch and scikit-learn :
conda create --name tkbc_env python=3.7
source activate tkbc_env
conda install --file requirements.txt -c pytorch
Then install the kbc package to this environment
python setup.py install
Datasets
To download the datasets, go to the tkbc/scripts folder and run:
chmod +x download_data.sh
./download_data.sh
Once the datasets are downloaded, add them to the package data folder by running :
python tkbc/process_icews.py
python tkbc/process_yago.py
python tkbc/process_wikidata.py # about 3 minutes.
This will create the files required to compute the filtered metrics.
Reproducing results
In order to reproduce the results on the smaller datasets in the paper, run the following commands
python tkbc/learner.py --dataset ICEWS14 --model TNTComplEx --rank 156 --emb_reg 1e-2 --time_reg 1e-2
python tkbc/learner.py --dataset ICEWS05-15 --model TNTComplEx --rank 128 --emb_reg 1e-3 --time_reg 1
python tkbc/learner.py --dataset yago15k --model TNTComplEx --rank 189 --no_time_emb --emb_reg 1e-2 --time_reg 1
License
tkbc is CC-BY-NC licensed, as found in the LICENSE file.