Overview
This Guidance demonstrates an automated approach for generating rule recommendations to match, link, and enhance related records using AWS Entity Resolution rule-based matching. It showcases an AWS Glue notebook that streamlines the process of creating effective matching rules. The Guidance reads input data from Amazon S3, performs data quality analysis, and harnesses the power of a large language model (LLM) on Amazon Bedrock to produce customized rule recommendations. Each recommendation comes with accompanying reasoning, providing insights into the suggested rules. Furthermore, the Guidance implements a sampling approach to test the generated rules and resolve entities.
How it works
Overview
This architecture diagram shows an overview of how to generate rule recommendations using an LLM hosted on Amazon Bedrock and an AWS Glue notebook and how to use these rules in a rule-based matching workflow in AWS Entity Resolution.

Incremental rule-based workflow
This architecture diagram shows how to run an incremental rule-based matching workflow in AWS Entity Resolution using an AWS Step Functions workflow.

Deploy with confidence
Ready to deploy? Review the sample code on GitHub for detailed deployment instructions to deploy as-is or customize to fit your needs.
Well-Architected Pillars
The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.
Disclaimer
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