The Knowledge Graph Track at OAEI -- Gold Standards, Baselines, and the Golden Hammer Bias
This work identifies a critical bias in ontology matching tools, impacting researchers and practitioners in knowledge graph integration.
The paper analyzes the Knowledge Graph track at OAEI, revealing that all submitted tools suffer from a bias called the golden hammer bias, which affects their performance in ontology matching.
The Ontology Alignment Evaluation Initiative (OAEI) is an annual evaluation of ontology matching tools. In 2018, we have started the Knowledge Graph track, whose goal is to evaluate the simultaneous matching of entities and schemas of large-scale knowledge graphs. In this paper, we discuss the design of the track and two different strategies of gold standard creation. We analyze results and experiences obtained in first editions of the track, and, by revealing a hidden task, we show that all tools submitted to the track (and probably also to other tracks) suffer from a bias which we name the golden hammer bias.