Query Entities Discovery and Keyword Research

How to Discover Query Entities that Expand Keyword Research

Updated 8.17.2023

While still keyword-based, Google SERPs are changing to entity clustering, query entities discovery, and using content scoring to surface the best content.

Google’s comprehension of entities is updating everything from indexation, what ranks, and what visually displays on the SERP! It has made query entities’ discovery and keyword research to build semantically rich content more important than ever. Today search engines consider searchers’ intent and the contextual meaning behind words in structured content in addition to the “words” themselves.

Paid search marketing is no longer just about buying the right keyword nor is SEO constrained by keyword research and matching. Organic search result pages (SERPs) are increasingly filled with rich-featured displays and Knowledge Graphs. Today, researchers need a way to identify more relevant search phrases with related meanings that expand on a main topic. This is accomplished by a SERP analysis and research for conversational opportunities.

Semantic matches and keyword clustering bring about content clarity and depth. It is more about content writing based on the natural language that your audience uses and relates to. Researching entities removes confusion.

If your site visitors have a great experience with your content, they’re much more likely to trust you, implement the solutions you offer, convert, and be a return customer. By consistently showing up in web searches and helping them get their questions answered – your business can grow. Your publications may inspire people to learn new ways to think about their situation. They will thank you.

Table of Contents

How is Keyword Research Changing?

Keyword Research is transitioning to Entity Oriented Search, which involves the discovery of semantic search phrases.

The key focus of each article still centers on words around a topic entity. Think of keywords as one way of describing an entity. Or, that an entity that is a search phrase. By linking named entities to your Google Knowledge Graph, your content is “hosted” on Google and more easily discoverable.

All facets of an entity-oriented search may represent a summary of information across the web that provides a coherent and comprehensive overview of a topic. It surpasses keyword-based research by going further to understand query context and search intent. This approach helps your new content to both support your business pillars and care about how your audience behaves when conducting a search.

Many people complain of searching online only to get frustrated with massive, fluffy article options that provide no real information that meets their search intent. Avoid creating content filled with hyperbolic and pretentious language that is too complex. The real value of your content piece should be clear.

Your audience wants to understand what they can expect before they click on a link to your page. Then, what you say should be clear in your readers’ minds after reading it. Keyword stuffed content has little value and is frustrating to read.

How are entities different from keywords?

Entities relate to concepts or ideas that have unique attributes and clear characteristics which can share relational nodes. Even though each entity has an independent aspect, it has both direct and indirect shared connections with other entities based on common qualities.

Entities are part of knowledge graphs. They aren’t restrained by the use of a specific language.

Entities assist how search engines categorize information topics in order to help them:

  • Decipher user queries.
  • Match and answer these questions.

In general, semantic search intends to match documents that correspond to the meaning and intent of the query, not just its words. That is a key difference between keyword research and what is needed today – aligning with search intent. An entity organized facts in statements known as triples that are extracted in the form of subject, predicate, and object.

Understanding how Google’s algorithm is changing because of entity search gives you an advantage within the SERPs. It’s about focusing your efforts on creating valuable content for users rather than just for search engines. It remains important to target their results effectively with relevant keywords, but including relevant entities must now happen alongside keyword research.

What is a search entity?

Google describes an entity as “A thing or concept that is singular, unique, well-defined and distinguishable.”

Entity is a live or real thing providing a distinction between a thing’s existence and its qualities. Related search query entities are identified whenever a query is entered into Google Search. Search Query Entity Identification involves the classification of the search query, meaning that the entity present in the query is identified. A search entity is basically a better method for bots to decipher user intent while mapping additional verified sources to answer a search query.

After Google successfully classifies the category and entity name of the search query, it seeks additional resources for a deeper understanding of related queries. Similar to a keyword, a search query entity may refer to an individual, enterprise, partnership, association, board, smell, flavor, or legal cooperative that has a unique, identifiable existence. An entity can be considered a type of keyword since it references a specific person, place, concept, or thing.

You are an entity. Where you live, your ethnicity, your address is an entity. The shape of your eyes, music genre, or your favorite type of food is an entity. We have moved from keyword-focused SEO to discovering how entities with similar attributes are grouped together.

One way to think of it is that an entity is a keyword on steroids. Entity Search is the term that references searches where Google returns results for a topic instead of returning results that match the actual search query itself. An entity in computer science might reference a number of different concepts, depending on the context. Within programming, entities can either refer to an HTML entity or an on-page or internal entity relationship. When conducting your audience research, you care about which entities your ideal customer uses most often.

How are search queries matched to web pages?

Search engines process and catalog information they find in an index, a huge database of all the content they harvest and decide is good enough to serve up. Often words used in a search query leave ambiguity. Google seeks to narrow user choices by providing search filter options.

Search engines have struggled with new search entries and vague search intent. This need is pushing the Semantic Web and Linked Data forward. It is useful as a means to improve search engines’ content comprehension, cataloging, and matching abilities to return better SERPs. By embracing this new approach, your content ideation processes will be more effective.

“To give you the most useful information, search algorithms look at many factors, including the words of your query, relevance, and usability of pages, the expertise of sources, and your location and settings. The weight applied to each factor varies depending on the nature of your query—for example, the freshness of the content plays a bigger role in answering queries about current news topics than it does about dictionary definitions.” – Google [1]


Content ideation in the marketing industry is the process of identifying topics to be used in future marketing content. It helps when trying to provide your audience with “the most useful information”. The topics are meant to be relevant to your company’s goals and support your content marketing strategy. To understand how search query terms get indexed and boost content, we need a basic grasp of Phrase-Based Indexing.

How Phrase-Based Indexing Creates Document Descriptions of Query Phrases?

Phrase-Based Indexing can help many pages increase their relevance for specific query terms when using co-occurring phrases. This includes wording related to those queries and anchor text pointed to that page using related phrases.

Google Patent US7536408B2 Phrase-based indexing in an information retrieval system explains how Google may identify phrases in a query and use them later to retrieve and rank documents.

“Phrase information may also be used in an information retrieval system to create a description of a document, for example the documents included in a set of search results. Given a search query, the system identifies the phrases present in the query, along with their related phrases, and their phrase extensions. For a given document, each sentence of the document has a count of how many of the query phrases, related phrases, and phrase extensions are present in the sentence. The sentences of document can be ranked by these counts.

The phrase identification operation of the indexing system 110 identifies “good” and “bad” phrases in the document collection that are useful to indexing and searching documents. In one aspect, good phrases are phrases that tend to occur in more than certain percentage of documents in the document collection, and/or are indicated as having a distinguished appearance in such documents, such as delimited by markup tags…”

Websites, pieces of content, and content authors are “scored” so that a search engine can provide the best result. They are looking for relevant, unique, trusted, expert-written, value-added content.

Across the Web of Semantic Data, an entity is the “thing” described in a document. This entity recognition helps search engines identify the most useful, value-added content.

Identify Value-added Topics for your Writing Team

Content ideation begins with proper market research that goes beyond traditional keyword research tools.

Your research can also find link-worthy topics with search volume where you can provide value-added content. Every business wants the build best-in-class content for a keyword that will quickly generate 40+ inbound links and obtain page ranking #1. It is possible; it also requires smart research and/or a lot of work. While it may not be the fastest business growth model if revenue needs are immediate, publishing unique, value-added content is typically the best long-term strategy. We find that when topics are covered in-depth, it is easier to rank.

Exceptional content creation not only requires learning what’s changed but also figuring out how these changes impact your current content marketing strategies. Great SEOs and content managers fundamentally understand a business as a whole from top to bottom and its holistic marketing strategy. It means more than creating content that satisfies your audience by answering questions via the queries they use.

If you are embarking on initial projects requiring website ideation efforts, the remainder of this article is for you.

How to do Keyword Research That also Finds Query Entities for Value-Added Content Ideas

Add to your keyword research by following these 8 steps to find the best entity query terms for content creation:

1. Study your niche and know which entities your audience cares about.

2. Map how business goals can be supported by content.

3. Conduct a user sentiment analysis.

4. Use good keyword research tools.

5. Create a list of important and seed entity phrases.

6. Study your audiences’ search intent for entity-first-indexing.

7. Use schema markup to help search engines understand your content.

8. Conduct a competitive gap analysis to find topic authority entities.

1. Study your niche and know which entities your audience cares about.

Gain a data-based view of topics your customers care about. Formerly, this focused on keyword research and search volume. Today, it includes identifying the best search phrases, semantic search, and an understanding of topic node relationships. For example, if marketing is your main topic, then internet marketing, marketing strategy, paid marketing, and social media marketing are all google subtopic entities.

If you miss your audience, your content has failed.

When speaking during a presentation directly in front of your audience, you know whether or not what you’re saying resonates. Attendees start drifting, silently texting, whispering with others, or looking bored. With web content, your search marketing reports will reveal your content marketing success status and which search queries work. You don’t need to lose your audience. People’s appetite for informational and educational content has never been higher.

Support your readers’ objectives. You cannot expect consumers to purchase from you if you’re not there during the awareness stage. Identify the purpose of each content piece and how it supports your readers’ decision-making process at each stage of their purchase journey.

Despite a significant body of research in optimizing keywords, your content may be still falling short unless you further optimize it semantically for search intent, market it, and update it when freshness is needed.

Over time, that represents a lot of work. Meaning that only value-added content is worth the effort.

Gain a combined understanding of keyword research, user intent and entities.

Identify which topic entities are interesting, and what relevant information will be of the most value to your audience. The end goal of this research is to select the best entities and keywords from a list of content ideas that will provide the most value. In the long run, value-added content is considerably less expensive than banner advertising, Google AdWords, Facebook Ads, and other priorities that may soak up your time and budgets.

What exactly is value-added content?

Value-added website content refers to fresh, unique, needed or exclusive content or information that your audience searches for and cannot find sufficient answers to. Examples of this added value content include video content, case studies, research studies, white papers, promotional offers, video tutorials, and in-depth informational articles and blog posts.

From the business owners’ perspective, it’s about “Content and Conversions”. Multiple studies and surveys in Q1 of 2022 affirm that content is going to be the dominant marketing practice being deployed by marketing professionals. A huge disconnect remains with how to publish value-added content efficiently and effectively while gaining more conversions.

Research and discovery of query recommendation typically entails the analysis of query logs, which contain a variety of information about previous keyword search activities. Find new entities useful for query recommendation that will help shape value-added content. Crafting original content becomes harder in the midst of the sea of content that’s already published; Google is committed to discovering the most valuable query answers and remains the most complete map of that sea.

2. Map how business goals can be supported by content marketing.

Entity SEO and an entity-based search approach give a competitive edge – as long as you are on track with your business goals. You can only write effective content to support your products or services when you keep your goal post in view. Although entities are often conversations between SEOs, keywords still have a major role to help find and connect your content to entities. This applies whether on your Google Knowledge Graph or your internal content mapping to your business goals.

Smart marketing research offers better insights than accumulating tons of data and A/B testing. Measuring every keyword and usage is extremely time-consuming. Entity phrase understanding gives you a fuller impact on how your content writing can help you meet your business goals. To make your content rich, value-added entities may be video content, case studies, research studies, white papers, promotional offers, tutorials, infographics, charts, tables, and blog posts.

You will be more successful when you focus on creating the best content that makes your readers more successful.

If you use Oracle, the Java Persistence query language (JPQL) is a simple, string-based language similar to SQL used to query entities and their relationships. Criteria queries allow you to define the query in the business tier of the application

3. Conduct a Sentiment Analysis

Sentiment analysis helps identify the tone of text data, positive, negative, neutral, or dead. Capturing the right sentiment can help your content better resonate with the Voice of Customer (VOC) and even direct product development to improve functionality. Frequently, sentiment analysis is lexicon and rule-based, meaning it performs a lookup on words tagged by humans as positive, negative, or neutral. Advanced search models such as BERT and MUM take us past the traditional lexicon-based approach and apply deep learning models to surface the best content.

A trigger word (or power word) is an emotionally-packed word or expression used to trigger a psychological reaction in readers. By identifying your consumer’s language and emotions along the buyer journey, you can create content that is easy for them to read and “feel”. If you speak over their heads they may hit the back button. Additionally, use language that resonates with their emotional triggers and effectively shows that you understand and anticipate their needs.

Remember that emotions are entities that build consumer relationships that drive sales. So a good way to help Google understand your content is to add relevant entities to support main entities, the same way you would add secondary topics to help support your topic hubs.

4. Use good keyword research tools.

Deep topic research and analysis tools can take you a long way in writing unbeatable SEO content. We use them to research and find topic Hub and Spoke suggestions. It makes it easier to identify content ideas that will provide additional value to readers. One research tactic alone will never give you the best end ROI.

Keyword tools may struggle to keep up with entity search terms, but they are still useful for content ideation and identifying subtopics. They are great to support your hunches. Here are few:

  • Google Trends: This Google tool helps to identify trending search topics in your industry as the tech giant sees them. It tracks global or localized search trends and provides a wealth of data. Recently it was incorporated into Google Search.
  • Google Search Console: More reports are added that offer key insights as to what content is working well and can identify where you may have many impressions but few clicks. This offers content suggestions for both improving existing content and new content ideas. Using Google’s Custom Search API you can record keywords, pages, and top queries that are most effective. You can also retrieve a lot of data insights from Google SERPs, glean semantic queries and leverage data science for better content creation. On January 31, 2022, the Google Search Console URL Inspection API [2] is launched, a new way for developers and SEOs to debug and optimize their pages.
  • Knowledge Graph Search API: This lets you find entities in the Google Knowledge Graph that help identify content types it’s interested in. Google also provides a tool developers.google.com/apis-explorer/#p/kgsearch/v1/kgsearch.entities.search to allow you to interrogate their knowledge base.
  • Ontotext Text Mining Plugin: Enrich documents with mentions of known entities with an output of text mining APIs as SPARQL binding variables. It can generate semantic annotations by linking fragments from texts to knowledge graph entities (entity linking).
  • Wordlift I have firsthand experienced how Wordlift.io’s entity vocabulary definitions help connect content to Google’s understanding of a web page. Wordlift entities help organize content. When annotating an article with an entity, this tool creates a relationship between the article and entity in such a way that a computer can understand it. These relationships are stored in the website’s graph and provide meaningful recommendations to your readers.
  • Streamlit Keyword Clustering App: Semantic matches are now possible in the new version of the app using state-of-the-art text embeddings and the Sentence Transformers library. You can report a bug or an issue in Github. Gain search volume from Keyword Surfer or Semrush API (an API is required and you will spend 10 credits per keyword).
  • Semrush Topic Tool: all you need to do is think of the topic or keyword of interest that you want your website to cover and type it into the Topic Research search bar.
  • Ahrefs Keyword Tool: Under “Search Suggestions”, check out “terms” and “parent topics”.
  • CCG’s Content Topic Optimization Tool It’s meant to help you gain an objective, data-based view of topics your customers care about.
  • Contrack: A large scale human-human conversation corpus for context tracking with people and location annotations. It’s a unified approach to Entity-Centric Context Tracking in Social Conversationsby five Google authors. [4]
  • NER: A process assisting the systems or algorithms to identify, classify, and connect entities in the text with entities in other knowledge bases.
  • Google Workspace Entity Research Tool: This SEO Content Optimization Tool lets you enter the entity your article is targeting, and its AI analyzes the top-performing content in Google Search. It will show exactly what your audience expects to read about and show you what your content is missing.

Formerly many content marketers passed up on content ideas if their keyword tools didn’t show a sufficient search volume. But that’s not how this entity-based search works. Today you get to higher search volume and keyword rankings by creating topical authority. Entity relevance matters more than search volume.

5. Create a list of seed keyword phrases.

Your list of keyword suggestions and query expressions is foundational to content mapping.

Seed keywords are the beginning of the keyword research process. They help your business know what defines your niche. The Google Keyword Planner and the Moz’s Keyword Explorer are helpful places to start discovering the top entities to discuss and questions to answer in your content. They can help to forecast your keywords; you can overview them in a graph as well as more detailed forecasts in table format.

Research online documents containing similar words that are semantically related to help create a list of your priority and seed keyword phrases. Find words frequently co-occurring that are also considered close entity relationships. People searching may want to solve cases where statistical semantics queries will be highly valuable.

After you’ve obtained sample results, download the data and pull it into a spreadsheet. We like to use Google Sheets as a database for keyword research and prioritizing query entities. A good keyword analysis model can detect the most relevant keywords from a piece of text with no manual work.

A seed keyword is a short-tail search term, usually consisting of one or two words. Seed keywords are useful to sprout other queries for which you can optimize your website. After identifying a few relevant seed keywords, build them up with modifiers to generate long-tail keywords. The contextual meaning of these words assists in aligning content to searchers’ intent.

We learn from another US Patent No. US 2015/0331866 that four factors are involved in the ranking of entities:

  • Relatedness.
  • Notability.
  • Contribution.
  • Prize.

Ask yourself, are people’s needs getting met by your content? Can people relate to your seed keyword phrases? Are you publishing notable and helpful content? Are you leveraging AI and Knowledge Graphs to maximize your content?

6. Study your audiences’ search intent for entity-first-indexing.

Identify your audience’s search intent when searching for products or services that you offer. What they are saying or typing in a search box may be the best way they know to communicate but only vaguely represent what they hope to gain by conducting a search.

What type of information are they seeking that will help them make purchase decisions? Here are some top things to consider

  • Product comparison charts – may include what your competition offers.
  • Product size charts – great for remarketing in paid search.
  • A list of pain points and solutions in table format.

If your audience wants to get answers on mobile, perfect the mobile version of your content. Optimization for your website on mobile devices matters more than ever. If your audience is there, then your content needs to match their search intent well on mobile devices.

Cindy Krum wrote about how Google mobile-first indexing explores best practices designed to improve user experiences in Google Search and how it relates to entities. She believes: “Google’s change to Mobile-First Indexing is much more about an entity classification and translation than it is about a different user-agent and viewport size for the bot. I believe this so much that I have started calling Mobile-First Indexing ‘Entity-First Indexing’. It is much more accurate and descriptive of the challenges and changes that SEO’s are about to face with Mobile-First/Entity-First Indexing.”

“New strategies will include adding audio versions of text-only content, adding video and voice-interactive versions of content, and getting all these assets indexed and associated correctly with the main entity. In addition to being evaluated for the content and potentially for mobile rendering, domains are evaluated for entity understanding using on-page text, metadata, Schema and other signals,” Krum adds.

7. Use schema markup to help search engines understand your content.

Structured data helps provide the context of a web page’s topical relevance. You need to discover certain schema entities that provide value in a content piece. Schema markup helps your content to be featured directly on Google SERPs; which may generate links directly to your site.

Schema markup powers the creation of rich snippets, which may feature your content. Consumers are clicking right on the SERP. And according to Semrush, “70% of all answers returned from voice searches occupied a SERP feature with 60% of those returning a Featured Snippet result”. [3] Implementing schema markup directly into voice-to-text is a key technical SEO strategy. Today using semantic technologies and schema.org is fundamental to rank and reach your target audience.

When you effectively combine structured data markup with this kind of knowledge, you are building a strong entity roadmap that demonstrates that you are a subject expert. Structured data informs Google of the data needed to display your page’s entities. The featured snippets you may gain are a great way to drive clicks to your web pages.

Google’s Entity Understanding

Also, by implementing structured data in your content, you may contribute to entities on search engine knowledge graphs and win a rich snippet. It’s of high value to answer questions commonly asked to gain a PAA rich snippet. Optimize for People Also Ask inclusion as that gives you related entities to cover in your content. The schema.org vocabulary is continually evolving to represent and boost any kind of content.

You can use the Schema.org sameAs property to reference related web pages’ URLs. This informs search engines “this is the same thing as what you’ll find at this address” and helps to connect entities. It offers context, and context allows Google to disambiguate multiple versions of a single entity, Currently, we know of only 10,000 to 50,000 domains that use this property. Meaning, it’s your opportunity to make a difference with a smarter SEO strategy.

In addition to explicitly expressing the page’s content, structured data markup can also define the content’s relationship in the web of data, like the Knowledge Graph.

8. Conduct a Competitive Gap Analysis to find topical authority entities.

A competitive gap analysis can identify what content is missing on your site. Research your market niche to discover what more in-depth content your audience wants. By conducting this additional research, you can be clued in missed opportunities to provide answers and solutions.

Perhaps you haven’t thought of a certain topic angle that has high search volume and opportunity. You can enrich and demonstrate your topic expertise by adding meaningful content that meets your audience’s needs and says more than what they currently find elsewhere. This often means writing specific pages for long-tail keywords.

You can assess the search terms used by your competitors, write better content around them, and win that web traffic.

Additional Tip for Query Entities Discovery: Use Facts

Factual content builds trust: It is best to provide context around some of the site’s statements and advice. Include facts from authoritative sources to avoid misinformation and support your opinions. Use Fact Check Markup for Search to build trust.

Google policies have something to say about incorrect information. “Information that is demonstrably false or outdated, as evidenced by, but not limited to legal documents, expert consensus, or other reputable primary sources. We may decline to act on facts that are reasonably disputed or lack demonstrative evidence.”

Adding the Power of Multidimensional Entities

To gain the power of multidimensional entities, craft these relationships and to organize the customer journey accordingly means:

  1. A deep understanding of customer journeys.
  2. Keeping business goals in view.
  3. The skills to craft them together effectively.

With an entity approach to SEO, the semantic meanings that Google associates to the targeted keyword phrase or topic in view to achieve multidimensional entities. Understand the most used keyword phrases that Google associates to your target entity. Let this guide your content writing. This will help you publish comprehensive articles with answers that Google and its users are looking for.

Because optimizing only for a keyword often leads to keyword stuffing and doesn’t deliver enough value. Also, I have noticed that the content often leads to fewer indexed keywords if you only optimize for the keyword rather than for semantic and entities

Statistics support factual content:

  • Content marketing costs 62% less than promotional, push-based outbound marketing while generating more than three times as many leads. [5]
  • 61% of consumers’ buying decisions are influenced by custom content. [6] Create your custom content in a way that adds it to Google’s Knowledge Graph.

“It’s a system that understands facts and information about entities from materials shared across the web, as well as from open source and licensed databases. It has amassed over 500 billion facts about five billion entities.” – Sources of information for the Google Knowledge Graph [7]


If you are not convinced yet as to the value of surfacing the right query entities, let’s answer a few more questions.

Does quality, well-researched content ideation really matter?

Yes. Given the proliferation of content today, your new pages may simply be lost without starting from a base of well-researched content ideation. While quality content matters to every website, healthcare content marketing requires more initial research and effort. Keyword research alone may leave your publications weak or thin in today’s market.

For example, see Connolly’s conclusion about WebMD’s depression treatment informational page. He writes that it is not totally unreliable but is sloppy and incomplete. You don’t want the same said about your content marketing publications!

“It looks mainly like something someone dashed off in an hour. And it could easily give patients a skewed view of their treatment options. It’s somewhat superficial, and they don’t really get into evidence-based discussions or much about current treatment guidelines”. – Danielle Correia of dragon360[7]


“The best way to get other sites to create high-quality, relevant links to yours is to create unique, relevant content that can naturally gain popularity in the Internet community. Creating good content pays off: Links are usually editorial votes given by choice, and the more useful content you have, the greater the chances someone else will find that content valuable to their readers and link to it.” – Google


It takes a good writer, and excellent page optimization to avoid someone (or Google) judging your content as “poor-quality”. Quality content is more important than the quantity of content you publish.

Has entity-based research replaced keyword research?

Keyword research isn’t dead, but entities provide better insights to search engines about the relationship between words in a search. Entity-based research can complement your keyword research. While not meant to replace it, this approach should definitely not be skipped.

Entity-based search phrases from the semantic point of view have largely replaced keyword-based search. Entity-based search is a better method for search engines to understand search intent and match relevant content. Google is able to catalog and map your well-defined entities across verified sources that feed Google’s Knowledge Graph question answering feature.

It’s the connection between you and the people who want to purchase your products and services. It helps you show up in Google Shopping Results when your audience needs you versus on the second, thrid, or a later page in search results.

According to Impact Plus’s Only April 1, 2011 31 SEO statistics for 2021 and what they tell us article by Jen Barrell, “only 0.78% of Google searchers click on results from the 2nd page”. This indicates why prioritizing SEO increaases your changes for your business to appear first during those Google’s 1.2 trillion+ searches annually.

Google Patent for Methods, Systems, and Media for Interpreting Queries

Google was granted US Patent: 11,210,289 on December 28, 2021 – it is all about how the tech giant may interpret queries. This may indicate the growing use of entity extraction, node relationships, entity scoring, and wherein the entity name is derived from metadata associated with the search domain.

“Mechanisms for interpreting queries are provided. In some implementations, a method for interpreting queries is provided, comprising: receiving a search query in a search domain; determining search terms based on the search query; determining, for each of the search terms, whether a search term corresponds to an entity name, wherein the entity name is derived from metadata associated with the search domain; in response to determining that entity names correspond to a portion of the search terms, determining an entity type and an entity score associated with each of the corresponding entity names; determining a remaining portion of the entity names by removing at least one of the matching entity names based on the entity score and contextual information in the search query; and performing a search in the search domain with the remaining portion of entity names, wherein each entity name in the remaining portion of entity names is searched corresponding to the associated entity type.” – Methods, systems, and media for interpreting queries [9]

Are Entities used by Google as a Ranking Factor?

No, they are not used in that sense as a factor that deciphers ranking. The traditional sense of how pages are ranked is more clearly a secret sauce than ever. Listening to what Gary Illyes and John Mueller have stated on numerous occasions indicates that content and links are factors that heavily influence the entity graph.

Co-occurrence is an aspect of how Google forms relationships between different entities. Co-occurrence refers to how frequently two different entities are linked together somehow, such as how often two different names are mentioned in a connected manner. For example, Google may ‘learn’ about the relationship between a business owner and CEO by how frequently their names are mentioned together. However, this is different from a ranking factor.

“You can freely use Google’s Entity Extraction tool in their API documentation, to see the entities they report in a page of text. However, this may not include all the entities they see as that API tends to be biased towards places, brands and things that start with canpital letters. Other free entity extraction tools include IBM Watson and Inlinks. A free to use tool buried on the home page of Inlinks.net compares the entities returned by Google’s API and compares them to the entities found by teh more aggressive InLinks api. This lets you see gaps in Google’s potential understanding of a page of content.


Whilst Google’s own Knowledge Graph uses identifiers like ‘kgmid=/g/11f0vfyswk’ to refer to an entity in it’s own graph, these IDs can change, which makes it hard for a third party to consistently reference them. So InLinks (which has its own knowledge graph) references Wikipedia URLs instead. The logioc is that Google understands these and should be able to transpose these URLs readily into their own Knowledge Graph.” Dixon Jones of Inlinks.net

Conclusion about Google’s Entity Extraction and Keyword Research

Improve and streamline your content planning process with good research. Enrich your content with entity vocabulary building and leap your content engagement and existence. As an authoritative content writer, editor, or publisher, you can identify the entities that best describe the essential meaning of your content between those words. Simply put, authoritative content is unique content that aligns with readers’ query intent, demonstrates subject expertise, and provides the right level of researched answers.

Call 651-206-2410 to Conduct a schema audit that discovers opportunities.


[1] google.com/search/howsearchworks/algorithms/

[2] developers.google.com/search/blog/2022/01/url-inspection-api

[3] semrush.com/blog/voice-search-study

[4] rxiv.org/abs/2201.12409

[5] lyfemarketing.com/blog/benefits-content-marketing

[6] vox.com/2016/4/5/11358268/webmd-accuracy-trustworthy

[7] blog.google/products/search/about-knowledge-graph-and-knowledge-panels/

[8] dragon360.com/blog/digital-content-marketing-strategy

[9] https://patft.uspto.gov/netacgi/nph-Parser

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