Term extraction is the process of scanning source content to identify candidate terms, product names, recurring phrases, and domain-specific expressions for potential inclusion in a termbase and for consistent use during translation. It usually takes place early in localization workflows, using automated tools or manual review to produce a candidate list for terminologists or subject-matter experts to validate before entries are approved.
Term extraction is used in localization preparation, often in CAT tools or terminology management systems, before translation begins. The output is a candidate list that terminologists review, with source context, frequency information, and existing termbase matches; approved items then become termbase entries for translators and QA. This helps standardize terminology before large-scale localization starts.
One common error is treating every high-frequency phrase as a term, which floods the termbase with noise and locks translators into unnecessary matches. Another is adding terms without context or domain validation, so the same string receives a single sense when it has multiple meanings in different product areas or departments.
For creative and consumer content the failure mode is flatness, not inaccuracy — and flatness passes an accuracy check. Terms here also carry technical constraints (reading speed, character budgets) that are part of the brief.
Angel Translation locks terms like this into a project terminology base before expert review begins, so the same source term resolves to the same target term across every document in a submission — and stays consistent in the next revision. See the 8-step AI + expert workflow.
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