Lexical Relations Builder
Map the synonyms, broader and narrower terms, parts, related entities and predicates around a topic, and turn them into a page outline.
How to use the lexical relations builder
- Name the entity the page is about and pick its type. Be specific: “Shopify SEO” rather than “SEO”.
- Fill in the relations you know. Synonyms are alternative names; hypernyms are the broader category it belongs to; hyponyms are narrower types; meronyms are its parts; related entities are things that appear alongside it; predicates are what it does, has, needs or costs.
- Watch the map and the suggested structure update as you type. The outline is generated from your relations: hyponyms become sub-sections, predicates become “how it” sections, related entities become a comparison or context section.
- Copy the map as text for a brief, or as JSON if you keep topical maps in a spreadsheet or database.
Why relations matter more than keywords
Search engines model topics as entities and the relationships between them. When Google evaluates a page about “Shopify SEO”, it expects to find the things that belong to that topic: collections and product pages (parts), e-commerce SEO (the broader category), canonical tags and duplicate URLs (attributes), Google Search Console and apps (related entities). A page that names those things in sensible sentences is understood as a thorough treatment of the topic. A page that repeats “Shopify SEO” twenty times but never mentions collections is not.
Mapping the relations before writing also settles two structural questions: which hub the page belongs under (its hypernym) and which supporting pages it should link out to (its hyponyms and related entities). That is the basis of a topical map, and it is why this tool pairs with the topical map builder and the content brief generator.
Worked example
Entity: Google Business Profile (tool or software). Synonyms: GBP, Google My Business, GMB. Hypernym: local SEO. Hyponyms: service-area profile, storefront profile. Meronyms: categories, attributes, posts, photos, reviews, Q&A. Related entities: Google Maps, local pack, NAP citations. Predicates: drives map pack rankings, requires verification, shows reviews, supports posts.
From those relations the tool proposes: an H1 naming the entity, an H2 on what it is and where it sits in local SEO, H3s for the profile types, an H2 on the parts (categories, reviews, photos), H2s on how it drives map rankings and how verification works, and a section on Google Maps and the local pack. That is close to what a strong page on the topic actually contains.
Frequently asked questions
Where do I find the relations for a topic I do not know well?
Look at the top-ranking pages, Wikipedia’s article and its section headings, Google’s “People also ask” and related searches, and the categories and attributes used by the products or tools involved. The relations are usually visible once you look for them.
How many relations is enough?
Enough to write every section with something specific to say. For a supporting page, eight to twelve relations is typical. For a hub page, you may map thirty and then split them across several pages.
Is this the same as LSI keywords?
No. “LSI keywords” is a marketing term for loosely related words. Lexical relations are specific, named relationships between entities, and they translate directly into page structure and internal links.
Related tools
Background reading: how entity coverage fits into a topical map, in the content SEO strategy guide.