/DATTI

Primary LanguageJupyter Notebook

The code of DATTI: "An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor Isomorphism" https://aclanthology.org/2022.acl-long.405/

Datasets

  • ent_ids_1: ids for entities in source KG;

  • ent_ids_2: ids for entities in target KG;

  • rel_ids_1: ids for relations in source KG;

  • rel_ids_2: ids for relations 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;

  • The datasets and pre-trained embeddings could be downloaded from https://github.com/MaoXinn/DATTI/releases

Environment

  • Jupyter notebook
  • tensorly
  • tensorflow == 2.4.1
  • Python == 3.6.5
  • Numba
  • Scipy
  • Numpy
  • tqdm

Just run Tensor_decoder.ipynb block by block.