{"id":9116,"date":"2026-06-01T21:41:25","date_gmt":"2026-06-01T13:41:25","guid":{"rendered":"http:\/\/longzhuplatform.com\/?p=9116"},"modified":"2026-06-01T21:41:25","modified_gmt":"2026-06-01T13:41:25","slug":"entitymap-the-open-standard-that-gives-ai-systems-a-structured-view-of-your-business-via-sejournal-dixon_jones","status":"publish","type":"post","link":"http:\/\/longzhuplatform.com\/?p=9116","title":{"rendered":"EntityMap: The Open Standard That Gives AI Systems A Structured View Of Your Business via @sejournal, @Dixon_Jones"},"content":{"rendered":"<p><\/p> <div id=\"narrow-cont\"> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">AI systems are now answering questions about your business. The problem is that they are often getting it wrong.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Consider the typical situation. A brand\u2019s products, services, expertise, locations, leadership, and relationships are distributed across dozens of pages. An AI model retrieves fragments from those pages, stitches them together probabilistically, and generates an answer. The result is often hallucinated product names, invented executives, misquoted capabilities, and weak or absent attribution.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">This is not a failure of AI models. It is a failure of the medium itself. We have built the web around pages, links, and prose. AI retrieval systems need something fundamentally different: a structured layer of meaning and evidence.<\/p> <h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">The Proposal: EntityMap<\/h2> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">EntityMap has just entered public consultation. It is a new open standard that gives organizations a way to publish a single structured file. This file declares what the organization knows, maps how its key entities relate to one another, and links every claim back to its source evidence.<\/p> <p><iframe class=\"sej-iframe-auto-height\" id=\"in-content-iframe\" scrolling=\"no\" src=\"https:\/\/www.searchenginejournal.com\/wp-json\/sscats\/v2\/tk\/Middle_Post_Text\"><\/iframe><\/p> <figure id=\"attachment_576147\" class=\"wp-caption aligncenter\" style=\"width: 1920px\"><img decoding=\"async\" src=\"https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433.png\"  width=\"1920\" height=\"892\" class=\"wp-image-576147 size-full\" srcset=\"https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-384x178.png 384w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-425x197.png 425w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-480x223.png 480w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-680x316.png 680w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-768x357.png 768w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-850x395.png 850w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-1024x476.png 1024w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-1280x720.png 1280w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-1300x680.png 1300w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-1536x714.png 1536w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433-1600x743.png 1600w, https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/entitymap-visualization-433.png 1920w\" sizes=\"auto, (max-width: 1920px) 100vw, 1920px\" loading=\"lazy\" title=\"EntityMap: The Open Standard That Gives AI Systems A Structured View Of Your Business via @sejournal, @Dixon_Jones\u63d2\u56fe\" alt=\"EntityMap: The Open Standard That Gives AI Systems A Structured View Of Your Business via @sejournal, @Dixon_Jones\u63d2\u56fe\" \/><figcaption class=\"wp-caption-text\">Image from author, May 2026<\/figcaption><\/figure> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The consultation runs until 30 June 2026, with formal launch scheduled for July 1. For the next 33 days, the project is actively seeking implementation feedback, technical critique, and real-world testing from developers, SEO professionals, publishers, structured-data specialists, and anyone building or relying on AI retrieval systems.<\/p> <h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">Where EntityMap Sits In The Standards Landscape<\/h2> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">EntityMap is not a replacement for existing web standards. It fills a gap that sitemap.xml and schema.org were never designed to address.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Sitemap.xml tells crawlers which pages exist on a website. Schema.org describes what appears on individual pages. EntityMap tells AI systems what an organization is, what it knows, and how that knowledge connects across the entire website.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">This distinction matters. Consider a healthcare organization publishing treatment protocols. With schema.org, you can annotate a single page. With EntityMap, you can say the following: \u201cHere are our core treatment areas. These are the relationships between them. Here is the peer-reviewed evidence supporting each claim. Here is where that evidence lives on our site.\u201d An AI system reading that file gets a structured view of institutional knowledge rather than reconstructing it from page fragments.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Or, consider a SaaS company concerned about how AI systems describe its product. EntityMap allows the company to declare: \u201cWe offer feature X. It differs from competitors in Y. Here is the proof: link to documentation, link to case study, link to comparison page.\u201d No longer must the company rely on an LLM to infer differentiation from scattered web content.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The same logic applies to publishers protecting attribution, legal firms clarifying expertise boundaries, financial services firms navigating regulatory nuance, and brands concerned about AI misrepresentation.<\/p> <h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">How EntityMap Works<\/h2> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">EntityMap is a JSON file published at a predictable location on a domain. It contains three core elements.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Entities<\/strong> are named things the organization covers: products, services, people, concepts, locations, regulations, areas of expertise.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Relations<\/strong> map how those entities connect. Examples: \u201cthis product improves this outcome,\u201d \u201cthis person leads this team,\u201d \u201cthis regulation governs this service.\u201d<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Evidence chunks<\/strong> are supporting passages from the website, linked to their source URL.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Each chunk carries attribution metadata: the publisher name, the source page, the retrieval timestamp. This metadata survives extraction, aggregation, and storage in vector databases. When an AI system generates a response using your content, the chain of evidence remains intact.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The specification is deliberately minimal. The conformance floor consists of roughly 12 required fields across three objects. Everything else is optional enrichment: custom predicates, cross-shard resolution, verification status declarations, changelog tracking.<\/p> <h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">Who Should Pay Attention<\/h2> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">If you are building Retrieval Augmented Generation (RAG) systems, cleaner source data means better reasoning chains and fewer hallucinations.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">If you are an SEO professional, this represents a new lever for AI visibility. It works with traditional content and link strategies rather than replacing them.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">If you are a publisher, this is a way to declare what you know and preserve attribution as your content gets disaggregated across AI platforms.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">If you are concerned about how AI systems represent your organization, this is a tool to assert control.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The standard is published under CC BY 4.0. There is no vendor lock-in, no subscription, no proprietary software requirement. Community contribution is open. The source code, specification, and validation tools are all available at GitHub.<\/p> <h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">What The Project Needs From You<\/h2> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The consultation period is not ceremonial. The project team is actively seeking specific forms of feedback.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Technical implementation feedback<\/strong>: Have you tried building an EntityMap for your site or product? What broke? What felt awkward in practice?<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Use-case validation<\/strong>: Does this solve a problem you actually face? Does it miss something critical to your domain or industry?<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Predicate critique<\/strong>: The standard defines 24 core predicates (IMPROVES, DEPENDS_ON, MEASURES, and others). Are these the right semantic abstractions for your work? Should we add or remove from this list?<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Integration ideas<\/strong>: Are you building a generator? A validator? A dashboard for managing EntityMaps? The project wants to know what tooling you are considering.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Sector-specific applications<\/strong>: If you work in healthcare, finance, education, legal, or another vertical, what would an EntityMap profile for your sector look like?<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The specification is available at entitymap.org\/spec\/v1.0. A validator is live at entitymap.org\/validate. The community forum and GitHub repository are at github.com\/entitymap.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Participants are invited to review the specification, test implementation, raise issues, suggest improvements, and contribute to the discussion before 30 June 2026.<\/p> <h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">Important Context: This Is Genuinely Open<\/h2> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">This is a standards proposal from within the search and AI community. R.V. Guha, one of the founders of schema.org, has reviewed the project and given it his endorsement.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The consultation is genuinely open. The first phase focuses on technical review and early implementation. Wider adoption, sector-specific applications and research into the standard\u2019s broader impact will follow after the consultation closes.<\/p> <h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">Why This Moment Matters<\/h2> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">If you have spent the last few years watching AI systems misrepresent your work, your clients\u2019 work, or your organization\u2019s expertise, this is your moment to shape how that changes.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The bar for entry is low. You need to review the specification, test it against a real problem you care about, and tell the project what you found. That feedback will inform the standard before it becomes finalized.<\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The consultation runs for 33 days. After that, the adoption phase begins.<\/p> <p><em><strong>Disclosure:<\/strong> I am the CEO of InLinks and Waikay, which both support the EntityMap standards proposal.<\/em><\/p> <p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>More Resources:<\/strong><\/p> <hr\/> <p><em>Featured Image: optimarc\/Shutterstock<\/em><\/p> <\/div> <p>Generative AI,SEO#EntityMap #Open #Standard #Systems #Structured #View #Business #sejournal #Dixon_Jones1780321285<\/p> ","protected":false},"excerpt":{"rendered":"<p>AI systems are now answering questions about your business. The problem is that they are often getting it wrong. Consider the typical situation. A brand\u2019s products, services, expertise, locations, leadership, and relationships are distributed across dozens of pages. An AI model retrieves fragments from those pages, stitches them together probabilistically, and generates an answer. The [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":9117,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[261,23964,35302,2465,80,28053,6607,347,3932],"class_list":["post-9116","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-accessibility","tag-business","tag-dixon_jones","tag-entitymap","tag-open","tag-sejournal","tag-standard","tag-structured","tag-systems","tag-view"],"acf":[],"_links":{"self":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/9116","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=9116"}],"version-history":[{"count":0,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/9116\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/media\/9117"}],"wp:attachment":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=9116"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=9116"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=9116"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}