The FB15k dataset contains knowledge base relation triples and textual mentions of Freebase entity pairs. It has a total of 592,213 triplets with 14,951 entities and 1,345 relationships. FB15K-237 is a variant of the original dataset where inverse relations are removed, since it was found that a large number of test triplets could be obtained by inverting triplets in the training set.
573 PAPERS • 9 BENCHMARKS
MMKG is a collection of three knowledge graphs for link prediction and entity matching research. Contrary to other knowledge graph datasets, these knowledge graphs contain both numerical features and images for all entities as well as entity alignments between pairs of KGs. While MMKG is intended to perform relational reasoning across different entities and images, previous resources are intended to perform visual reasoning within the same image.
44 PAPERS • 5 BENCHMARKS
OGB Large-Scale Challenge (OGB-LSC) is a collection of three real-world datasets for advancing the state-of-the-art in large-scale graph ML. OGB-LSC provides graph datasets that are orders of magnitude larger than existing ones and covers three core graph learning tasks -- link prediction, graph regression, and node classification.
31 PAPERS • 3 BENCHMARKS
This relational database consists of 24 unique names in two families (they have equivalent structures).
10 PAPERS • NO BENCHMARKS YET
We present a further analysis of visual modality incompleteness, benchmarking latest MMEA models on our proposed dataset MMEA-UMVM.
5 PAPERS • 7 BENCHMARKS
KG20C is a Knowledge Graph about high quality papers from 20 top computer science Conferences. It can serve as a standard benchmark dataset in scholarly data analysis for several tasks, including knowledge graph embedding, link prediction, recommendation systems, and question answering .
4 PAPERS • 1 BENCHMARK
The FB15k-237-low dataset is a variation of the FB15k-237 dataset where relations with a low number of triplets are kept.
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Biographical is a semi-supervised dataset for RE. The dataset, which is aimed towards digital humanities (DH) and historical research, is automatically compiled by aligning sentences from Wikipedia articles with matching structured data from sources including Pantheon and Wikidata.
2 PAPERS • NO BENCHMARKS YET
The FB1.5M dataset is a benchmark for Knowledge Graph Completion. It is based on Freebase and it contains 30 relations with less than 500 triplets as low-resource relations.
1 PAPER • NO BENCHMARKS YET
The KACC benchmark consists of three subtasks that can be applied to knowledge graphs: knowledge abstraction, knowledge concretization and knowledge completion.
TextWorld KG is a dynamic Knowledge Graph (KG) extraction dataset. It is based on a set of text-based games generated using. That framework allows to extract the underlying partial KG for every state, i.e., the subgraph that represents the agent’s partial knowledge of the world – what it has observed so far. All games share the same overarching theme: the agent finds itself hungry in a simple modern house with the goal of gathering ingredients and cooking a meal.