---
title: "Discussion on \"How to Audit Publication Metadata for Entity Resolution\" | Hashnode"
description: "Discussion on \"How to Audit Publication Metadata for Entity Resolution\". A parameter-controlled WordPress audit for detecting missing, fragmented, empty, and ambiguous organization records."
url: "https://hashnode.com/posts/how-to-audit-publication-metadata-for-entity-resolution/6aa2a588ec9d68f6483f0dc2"
---

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# [How to Audit Publication Metadata for Entity Resolution](https://machinerelations.hashnode.dev/how-to-audit-publication-metadata-for-entity-resolution?utm_source=hashnode&utm_medium=feed)

A parameter-controlled WordPress audit for detecting missing, fragmented, empty, and ambiguous organization records.

Sep 10 · 7 min read · machinerelations.hashnode.dev  
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-   [#machine-relations](https://hashnode.com/tag/machine-relations)
-   [#metadata](https://hashnode.com/tag/metadata)
-   [#web-development](https://hashnode.com/tag/web-development)
-   [#data-engineering](https://hashnode.com/tag/data-engineering)
-   [#retrieval](https://hashnode.com/tag/retrieval)

## Written by

[Jaxon Parrott](https://hashnode.com/@jaxonparrott)

@jaxonparrott · Austin, USA

  
[View profile](https://hashnode.com/@jaxonparrott)

Founder of AuthorityTech and creator of Machine Relations, the parent category for GEO, AEO, AI SEO, and AI PR.

Founder of AuthorityTech and creator of Machine Relations, the parent category for GEO, AEO, AI SEO, LLM Optimization, and AI PR. Machine Relations (MR) is the discipline I coined in 2024 to describe how brands become legible, retrievable, and citable inside AI-driven discovery systems. As search shifts from human-mediated discovery to machine-mediated answers, most of the market describes fragments of the same change using labels like GEO, AEO, AI SEO, LLMO, and AI PR. My position is that these are not separate categories. They are tactics or layers inside the broader system of Machine Relations (MR).

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