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Knowledge Graph
Knowledge graphs model connected concepts so AI systems can reason across entities and relationships, not only isolated text snippets.
Definition
A structured representation of entities and their relationships used by AI systems to organise and connect information.
How It Works
Knowledge Graph helps teams build predictable AI and translation workflows by setting clear expectations for quality, consistency, and decision-making.
In production environments, this concept is applied with process controls such as human review, terminology alignment, and repeatable quality checks across multilingual content.
They are widely used in semantic search, question answering, and retrieval-augmented generation to improve contextual understanding.
Key Concepts
- core principle of knowledge graph
- workflow-level implementation
- terminology and quality consistency
- human validation before publication
Where It Is Used
- localisation workflows
- AI translation pipelines
- multilingual content production
- cross-referencing related concepts such as Keyphrase Extraction