Skip to content

Introduction to the Entity Resolution Check

The Entity Resolution check clusters records that describe the same real-world entity, even when their values vary, and asserts that every record in a cluster shares one value of a chosen distinction field. Use it to catch the same customer, supplier, or product living under several identifiers.

This section is the complete guide to the check. The Deep Dive covers the definition, properties, and full evaluation semantics, explains how anomalies are reported, walks through production examples, and collects best practices; the How-tos are step-by-step tutorials for creating, editing, and deleting a check; the API page documents the payload for programmatic use; and the FAQ answers the most frequent questions.

Next Steps

To build an Entity Resolution check step by step, validate it on a sample, and turn its results into a golden set, use the Entity Resolution Recipe.

  • How It Works

    The complete reference: definition, field scope, field roles, comparison types, weights, threshold, and clustering.

    How It Works

  • Anomaly Reporting

    The anomaly message the check produces, what each number means, and how non-compliant clusters appear in Source Records.

    Anomaly Reporting

  • Examples

    Production scenarios with sample records, cluster outcomes, and the resulting anomaly messages.

    Examples

  • Best Practices

    Guidelines for blocking, weighting, tuning the threshold, and normalizing values before resolution.

    Best Practices

  • Permissions

    The team permission each action needs: view, create, edit, archive, restore, and delete.

    Permissions

  • Create a Check

    Step-by-step tutorial for creating an Entity Resolution check with block fields, comparisons, and a threshold.

    Create a Check

  • Edit a Check

    Step-by-step tutorial for changing the fields, comparison types, weights, threshold, or filter.

    Edit a Check

  • Delete a Check

    Step-by-step tutorial for archiving a check and deleting it permanently.

    Delete a Check

  • Troubleshooting

    Common problems with over- and under-clustering, NULLs in block fields, scale limits, and anomaly reporting.

    Troubleshooting

  • API

    Payload shape and field notes for creating an Entity Resolution check programmatically.

    API

  • FAQ

    Short answers to questions about comparisons, thresholds, clusters, and anomaly reporting.

    FAQ