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Parallel Corpus
A collection of texts and their translations in two or more languages used to train machine translation systems.
Definition
A collection of texts and their translations in two or more languages used to train machine translation systems.
How It Works
Parallel Corpus 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 parallel corpus
- 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 Post-Editing (MTPE)