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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.