Knowledge Graph Embedding Methods for Entity Alignment: An Experimental Review

The source code of the survey:

N Fanourakis, Vasilis Efthymiou, Dimitris Kotzinos, Vassilis Christophides: Knowledge graph embedding methods for entity alignment: experimental review. Data Min. Knowl. Discov. (2023) [paper]

Dataset License

Due to licensing we are not allowed to distribute the datasets bbc-db, imdb-tmdb, tmdb-tvdb, imdb-tvdb, restaurants. To run the experiments, please download bbc-db, imdb, tmdb, tvdb and restaurants.

Getting Started

You should :

1. Install Anaconda 4.11.0
2. Download wiki-news-300d-1M.vec.zip from https://fasttext.cc/docs/en/english-vectors.html
3. Unzip wiki-news-300d-1M.vec.zip
4. Copy wiki-news-300d-1M.vec to OpenEA/datasets

AttrE Instructions

cd AttrE
conda env create --file install/AttrE.yml --name AttrE_env
conda activate AttrE_env
cd "dataset_name" (e.g., restaurants)
python KBA.py

RREA Instructions

cd RREA_versions
conda env create --file install/RREA.yml --name RREA_env
conda activate RREA_env
python RREA.py

OpenEA Instructions

cd OpenEA
conda env create --file install/openea.yml --name OpenEA_env
conda activate OpenEA_env
pip install -e .
cd run
python main_from_args.py "predefined_arguments" "dataset_name" "split"

For example, for MTransE on tmdb-tvdb for the first split, please execute the following:

python main_from_args.py ./args/mtranse_args_15K.json D_W_15K_V1 721_5fold/1/

PARIS Instructions:

cd PARIS
conda env create --file install/entity_match.yml -n entity_match
conda activate entity_match
cd src/experiments
mkdir results
python3 -u ../run_experiment.py \
        --method PARIS\
        --root_dataset "root of dataset folder"\
        --dataset "dataset_name"\
        --dataset_division 721_5fold\
        --out_folder ./results\
        --use_func > test.log

BERT_INT Instructions:

cd BERT_INT
conda env create --file install/bert_int.yml -n bert_int
python basic_bert_unit/main.py
bash interaction_model/run.sh

Analysis Instructions

cd analysis
conda env create --file install/analysis.yml --name analysis_env
conda activate analysis_env

For Nemenyi Diagrams

python nemenyi_diagrams.py

For Correlations

python correlation_analysis.py

For Time to Accuracy

python time_to_accuracy.py

For Trade Offs

python trade_offs.py

Statistics Instructions

please download descriptions_pickles.zip from https://www.dropbox.com/sh/7r2y1x8wx9y921e/AAAh3DabBguCzxk8OlZnL-Mza?dl=0
uzip descriptions_pickles.zip
copy to ./statistics/
cd statistics
conda env create --file install/statistics.yml --name statistics_env
conda activate statistics_env
python statistics.py