Inductive Freebase and Wikidata for KG Completion

<p>UPD 2.0: Regenerated datasets free of potential test set leakages</p> <p>This repository contains 10 inductive link prediction datasets (graphs only)&nbsp;published in &quot;Inductive Logical Query Answering in Knowledge Graphs&quot; (NeurIPS 2022). 9 datasets (106-550) were created from FB15k-237, the wikikg dataset was created from OGB WikiKG 2 graph. In the datasets, all inference graphs extend training graphs and include new nodes and edges. Dataset numbers indicate a relative size of the inference graph compared to the training graph, e.g., in 175, the number of nodes in the inference graph is 175%&nbsp;compared to the number of nodes in the training graph. The higher the ratio, the more new unseen nodes appear at inference time, the more&nbsp;complex the task is. The Wikikg split has a fixed 133% ratio.</p> <p>Each dataset is a zip archive containing 5&nbsp;files:</p> <ul> <li>train_graph.txt (pt for wikikg) - original training graph</li> <li>val_inference.txt (pt) - inference graph (validation split), new nodes in validation are disjoint with the test inference graph</li> <li>val_predict.txt (pt) - missing edges in the validation inference graph to be predicted.&nbsp;</li> <li>test_intference.txt (pt) - inference graph (test splits), new nodes in test are disjoint with the validation inference graph</li> <li>test_predict.txt (pt) - missing edges in the test inference graph to be predicted;</li> </ul> <p>This is a light-weight version of the full datasets for inductive query answering published here: https://zenodo.org/record/7231344&nbsp;</p> <p>Here, we only provide graph data for training inductive link prediction models.</p> <p>Paper pre-print:&nbsp;https://arxiv.org/abs/2210.08008</p> <p>The full source code of training/inference models is available at&nbsp;https://github.com/DeepGraphLearning/InductiveQE</p>