OpenSanctions Pairs: Large-Scale Entity Matching with LLMs

arXiv:2603.11051 · cs.IR, cs.AI, cs.CL, cs.LG · Submitted 2026-02-24 · Read on arXiv

cs.IR, cs.AI, cs.CL, cs.LG

Submitted: 2026-02-24

Updated: 2026-08-25

Code: https://github.com/chansmi/OSINT_entity_resolution

Terminology

• Benchmark — 18× in this paper · explained in 2 episodes
• Clustering — 6× in this paper · explained in 2 episodes
• Failure Modes — 5× in this paper · explained in 3 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• F1 Score — 4× in this paper · explained in 3 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• In-Context Learning — 2× in this paper · explained in 4 episodes
• Provenance — 2× in this paper · explained in 4 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Ensemble Approach — 1× in this paper · explained in 3 episodes
• Explainability — 1× in this paper · explained in 3 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Human-in-the-Loop — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• LEMON: Explainable Entity Matching
• Cost-Effective In-Context Learning for Entity Resolution: A Design Space Exploration
• On Leveraging Large Language Models for Enhancing Entity Resolution: A Cost-efficient Approach
• A Survey of Blocking and Filtering Techniques for Entity Resolution
• WDC Products: A Multi-Dimensional Entity Matching Benchmark
• Can Foundation Models Wrangle Your Data?
• Fine-tuning Large Language Models for Entity Matching

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