MultiKE

Source code and datasets for IJCAI-2019 paper "Multi-view Knowledge Graph Embedding for Entity Alignment".

Dataset

We used two datasets, namely DBP-WD and DBP-YG, which are based on DWY100K proposed in BootEA.

DBP-WD and DBP-YG

In "data/BootEA_datasets.zip", we give the full data of the two datasets that we used. Each dataset has the following files:

• ent_links: all the entity links without training/test/valid splits;
• 631: entity links with training/test/valid splits, contains three files, namely train_links, test_links and valid_links;
• rel_triples_1: relation triples in the source KG, list of triples like (h \t r \t t);
• rel_triples_2: relation triples in the target KG;
• attr_triples_1: attribute triples in the source KG;
• attr_triples_2: attribute triples in the target KG;
• entity_local_name_1: entity local names in the source KG, list of pairs like (entity \t local_name);
• entity_local_name_2: entity local names in the target KG;
• predicate_local_name_1: predicate local names in the source KG, list of pairs like (predicate \t local_name);
• predicate_local_name_2: predicate local names in the target KG.

Raw datasets

The raw datasets of DWY100K can also be found here.

Dependencies

• Python 3
• Tensorflow 1.x
• Numpy

Run

To run the experiments, use:

bash run.sh -m mode -d dataset_folder_path

• mode: training mode, using either ITC or SSL;
• dataset_folder_path: the folder path of dataset to run.

For example, to run the experiments on DBP-WD with ITC mode, use:

bash run.sh -m ITC -d BootEA_DBP_WD_100K/

If you have any difficulty or question in running code or reproducing experimental results, please email to [email protected], [email protected] and [email protected].

Citation

If you use this model or code, please kindly cite it as follows:

@inproceedings{MultiKE,
  author    = {Qingheng Zhang and Zequn Sun and Wei Hu and Muhao Chen and Lingbing Guo and Yuzhong Qu},
  title     = {Multi-view Knowledge Graph Embedding for Entity Alignment},
  booktitle = {IJCAI},
  pages     = {5429--5435},
  year      = {2019}
}