This paper presents an initial study on explaining multi-entity relationships using Knowledge Graphs (KGs). We introduce a novel dataset ( https://github.com/aistairc/multi-entity-relationship-explanation ) designed to clarify relationships between multiple entities as an essential task given the rapidly growing number of entities across the web. As web content such as articles and blogs expands, understanding how the entities relate to one another becomes crucial for users to navigate and interpret online information while browsing the web. Often, online information is presented in a non-self-contained manner as it sometimes lacks context and does not present the connections between the entities involved. In this study, we emphasize the importance of improving user comprehension through explicit explanations of multi-entity relationships. To address this, we propose a dataset that lays the foundation for developing a system capable of providing clear and informative relationship explanations among entities as text. Unlike existing studies which typically focus on pairs of entities, our dataset includes over 9,400 entity sets, each containing 3 to 5 entities, along with textual descriptions of their relationships. Additionally, we extract Freebase KGs for each entity set using multi-hop expansion to gather supporting entities crucial for comprehensive explanations. This paper outlines the study’s objectives, the dataset construction process, and the data quality enhancements, and provides a detailed dataset analysis.