Inductive Freebase and Wikidata for KG Completion

UPD 2.0: Regenerated datasets free of potential test set leakages

This repository contains 10 inductive link prediction datasets (graphs only) published in "Inductive Logical Query Answering in Knowledge Graphs" (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% 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 complex the task is. The Wikikg split has a fixed 133% ratio.

Each dataset is a zip archive containing 5 files:

train_graph.txt (pt for wikikg) - original training graph

val_inference.txt (pt) - inference graph (validation split), new nodes in validation are disjoint with the test inference graph

val_predict.txt (pt) - missing edges in the validation inference graph to be predicted. 

test_intference.txt (pt) - inference graph (test splits), new nodes in test are disjoint with the validation inference graph

test_predict.txt (pt) - missing edges in the test inference graph to be predicted;

This is a light-weight version of the full datasets for inductive query answering published here: https://zenodo.org/record/7231344 

Here, we only provide graph data for training inductive link prediction models.

Paper pre-print: https://arxiv.org/abs/2210.08008

The full source code of training/inference models is available at https://github.com/DeepGraphLearning/InductiveQE