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Semantic Similarity
A measure used in natural language processing to determine how similar two texts are in meaning.
Definition
A measure used in natural language processing to determine how similar two texts are in meaning.
How It Works
Semantic Similarity 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.
Key Concepts
- core principle of semantic similarity
- 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 Segment-based Translation