Understanding Structured Data in InLinks: Wiki vs Google

Amman Masood

10d ago (edited) in 🔨 Tools

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.

3. Structured Data Generation Algorithms

Purpose: Automatically generate JSON-LD structured data (macro and micro) for search engines.How it Works: Algorithms extract identified entities and map them into schema formats, enabling search engines to understand the content better.

4. Knowledge Graph Mapping Algorithms

Purpose: Link entities to external knowledge graphs like Wikipedia and Google Knowledge Graph.How it Works: The algorithm compares the extracted entities to known entities in databases (Wikipedia, Google), then bridges them for better semantic understanding.

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