Record Linkage Measures in an Entity Centric World

For unsupervised clustering, traditional accuracy metrics based on the constituent records do not often reflect the accuracy at the cluster level. For a specific example, consider entity resolution where the goal is to cluster records across multiple, heterogeneous data sources into “entities.” Measuring the accuracy of entity resolution is not as simple as applying the well known record level metrics of precision and recall. Rather than using traditional tuple-based metrics for accuracy, we posit that new, entity-based metrics should be defined instead. Defining entitylevel metrics gains users a less source biased, yet deeper insight into entity resolution performance. We show that traditional record linkage metrics are not appropriate, and offer some early thoughts on entity-centric measurements that are more so.