Knowledge graph (KG) pipelines integrate heterogeneous data sources, diverse processing tasks, and multiple implementation strategies. Despite their importance, existing approaches provide limited support for systematically designing, comparing, and understanding such pipelines.

We present KGpipe Explorer, an interactive demonstrator for constructing, analyzing, and comparing KG integration pipelines. Users visually compose typed directed acyclic graphs, export executable configurations, inspect precomputed benchmark results and stage-specific metadata, and rank pipelines under customizable quality objectives.
The system supports responsive exploration of how pipeline choices affect KG quality and reveals trade-offs between alternative task and pipeline configurations.
Demo URL: https://vehnem.github.io/kgpipe-explorer/