  Recently, knowledge-enhanced methods leveraging auxiliary knowledge graphs
have emerged in relation extraction, surpassing traditional text-based
approaches. However, to our best knowledge, there is currently no public
dataset available that encompasses both evidence sentences and knowledge graphs
for knowledge-enhanced relation extraction. To address this gap, we introduce
the Knowledge-Enhanced Relation Extraction Dataset (KERED). KERED annotates
each sentence with a relational fact, and it provides knowledge context for
entities through entity linking. Using our curated dataset, We compared
contemporary relation extraction methods under two prevalent task settings:
sentence-level and bag-level. The experimental result shows the knowledge
graphs provided by KERED can support knowledge-enhanced relation extraction
methods. We believe that KERED offers high-quality relation extraction datasets
with corresponding knowledge graphs for evaluating the performance of
knowledge-enhanced relation extraction methods. Our dataset is available at:
\url{https://figshare.com/projects/KERED/134459}
