The code of "LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagation"

Datasets

• ent_ids_1: ids for entities in source KG;
• ent_ids_2: ids for entities in target KG;
• sup_ent_ids: training entity pairs;
• ref_ent_ids: testing entity pairs;
• triples_1: relation triples encoded by ids in source KG;
• triples_2: relation triples encoded by ids in target KG;
• graph_cache.pkl: cache file of graphs
• translated_ent_name: entity names translated by Google translator

Due to the limitation of upload file size, the DBP1M dataset is not included here. You can download it from https://github.com/ZJU-DAILY/LargeEA.

Environment

• Jupyter notebook
• tensorflow == 2.6.0
• Python == 3.7.0
• faiss
• Numpy
• tqdm
• pickle

Just run LightEA.ipynb block by block.