OpenEA Benchmark

该数据集是在OpenEA库中发布的一个基准数据集，用于实体对齐评估。它遵循真实世界知识图谱的数据分布。数据集的划分包括20%的参考对齐用于训练，10%用于验证，以及70%用于测试。该数据集涵盖了两种跨语言设置（英语到法语和英语到德语）和两种单语言设置（DBpedia到Wikidata和DBpedia到YAGO），分别包含15K和100K对参考实体对齐。这项任务的目标是实体对齐。

This dataset is a benchmark released in the OpenEA library for entity alignment evaluation, adhering to the data distribution of real-world knowledge graphs. The dataset is partitioned into three subsets: 20% of reference alignments for training, 10% for validation, and 70% for testing. It covers two cross-lingual settings (English to French and English to German) and two monolingual settings (DBpedia to Wikidata and DBpedia to YAGO), with 15K and 100K reference entity alignment pairs respectively. The core objective of this task is entity alignment.