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arXiv · 2606.08926

PROBE-Web: An Interactive System for Probing Evaluation Landscapes of Knowledge Graph Completion Models

Sooho Moon·Yunyong Ko
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Abstract

Knowledge graph completion (KGC) models are commonly evaluated using rank-based metrics such as MRR and Hits@K, despite different users often requiring different evaluation perspectives. In this demo, we present PROBE-Web, an interactive system for probing diverse evaluation landscapes for KGC models. PROBE-Web enables users to flexibly evaluate KGC models by adjusting two critical perspectives: (P1) predictive sharpness and (P2) popularity-bias robustness. Through a user-friendly GUI, users easily evaluate multiple KGC models and analyze their strengths and weaknesses. PROBE-Web provides four key functionalities: (1) conventional evaluation toolkit, (2) flexible perspective-aware evaluation, (3) explainable case studies, and (4) evaluation landscape exploration. We believe that PROBE-Web can help users better understand KGC models aligning with their objectives.

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Sooho Moon, Yunyong Ko. 2026-08-21. PROBE-Web: An Interactive System for Probing Evaluation Landscapes of Knowledge Graph Completion Models. https://doi.org/10.1145/3799682.3840276

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