Better Retrieval, Limited Clustering Gains: A Controlled Study of Multilingual Company Entity Resolution

Excerpt

arXiv:2610.05573v1 Announce Type: new Abstract: Improved name retrieval may have little effect on company clusters when the pair classifier remains unchanged. We examine this dependency by adapting multilingual E5 encoders under fixed candidate budgets and downstream decision rules. Random-negative and hard-negative training use identical positive schedules. Checkpoints are selected before collecting a new GLEIF sample of 3,633 names, 2,880 source identities and 882 silver-positive pairs. At 72,