  Constructing and serving knowledge graphs (KGs) is an iterative and
human-centered process involving on-demand programming and analysis. In this
paper, we present Kyurem, a programmable and interactive widget library that
facilitates human-in-the-loop knowledge acquisition and integration to enable
continuous curation a knowledge graph (KG). Kyurem provides a seamless
environment within computational notebooks where data scientists explore a KG
to identify opportunities for acquiring new knowledge and verify
recommendations provided by AI agents for integrating the acquired knowledge in
the KG. We refined Kyurem through participatory design and conducted case
studies in a real-world setting for evaluation. The case-studies show that
introduction of Kyurem within an existing HR knowledge graph construction and
serving platform improved the user experience of the experts and helped
eradicate inefficiencies related to knowledge acquisition and integration tasks
