/DualMatch

Primary LanguagePythonApache License 2.0Apache-2.0

DualMatch

Source code for "Unsupervised Entity Alignment for Temporal Knowledge Graphs".

Dataset

-ICEWS05-15

-YAGO-WIKI50K

-YAGO-WIKI20K

ent_ids_1: ids for entities in source KG;
ent_ids_2: ids for entities in target KG;
ref_ent_ids: entity links encoded by ids;
triples_1: relation triples encoded by ids in source KG;
triples_2: relation triples encoded by ids in target KG;
rel_ids_1: ids for entities in source KG;
rel_ids_2: ids for entities in target KG;
sup_pairs + ref_pairs: entity alignments

Run

To perform EA on ICEWS05-15 in unsupervised manner:

python main.py --ds 0 --unsup

To perform EA on YAGO-WIKI50K in Less seed setting:

python main.py --ds 1 --train_ratio 20

To perform EA on YAGO-WIKI20K in Normal setting and evaluate separately:

python main.py --ds 2 --sep_eval

Acknowledgements

We refer to the code of Dual-AMN, TEA-GNN, and SEU. Thanks for their great contributions!