How InLinks generates macro and micro structured data in JSON-LD format. Inlinks currently uses two types of SEO APIs: The Search Engine Understanding and Natural Language Processing API The Content Audit API Supported languages are English, French, German, Polish, Portuguese, Italian, Dutch and Spanish. 1. Search Engine Understanding and NLP API This API lets you send a URL to get: The list of entities detected.The entities detected by Google.The category or type of each entity.The Search Engine Understanding score.A Semantic Schema markup you can add to a webpage to ensure Google correctly understands the entities you’re talking about. 2. Content Audit API This API lets you get a white-label SEO content audit, similar to the InLinks Content Audit tool. When you are using an API to request data or perform an action, you need to provide specific pieces of information, called parameters, for the API to process your request correctly. The keyword or phrase to auditThe selected language/market (see list below)The selected Search EngineAn existing URL to audit (optional)Your Customer ID and associated API keyThe output of this API is a web page, not XML. If the call is successful, the API returns the URL of the Content Audit. InLinks' system maps entities to both Wikipedia and Google's Knowledge Graph. While Wikipedia entities are publicly accessible, Google's Knowledge Graph entities are proprietary. This process does not rely on a specific API that directly maps Wikipedia entities to Google entities. Here’s a breakdown of what such algorithms might include: 1. Entity Recognition Algorithms Purpose: Identify entities (e.g., people, places, things, or concepts) within the content.How it Works: Algorithms analyze text, breaking it down into components (words, phrases) to detect and classify entities. 2. Semantic Analysis Algorithms Purpose: Understand the meaning and context of entities within content.How it Works: The algorithm determines the relationships between entities to identify what the content is about.

I improved the knowledge retrieval of this app. I also switched the model to the new GPT o1 with advanced reasoning and tweaked the prompts. It's now providing even better ideas for planning your topical maps. I also just published a detailed walkthrough video explaining how to use it and best practices. Check it out: https://www.skool.com/ai-seo/classroom/09b951ef?md=bec382640bb9430092d035ca17ef0303

Hi Jonathan– Hope you’re doing well! I have a couple of questions about topical maps that have been mentioned in steps tab of Google Sheet: 1. Do you have any specific prompt you use to expand a list of ideas? And how do you base these ideas? Do you refer to them as entities, roots, attributes, or is it best to simply ask ChatGPT for a “list of 30 additional source contexts for [niche]"? 2. How do you go about finding better root/nodes? How do you determine if something could be restructured into something more meaningful? Would appreciate any insights on this! Thanks again,

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