Configure settings for duplicated strings to achieve the highest efficiency of the localization process and to save costs.
In Crowdin Enterprise, the localization process is based on translating the source strings to the defined target languages. Source strings are uploaded to the system in localization files. Each unique source string that was first uploaded or added (for CSV files) in Crowdin Enterprise is considered to be the master string. All other strings that are identical to the master string but were uploaded or created later are considered duplicated strings.
There are 4 main options to work with duplicated strings in Crowdin Enterprise:
When this option is chosen, all the duplicated strings will be visible for translators. Each duplicate will require separate translation.
Use case: works perfectly for the projects where the same words might have various meanings depending on the context.
When this option is chosen, all the duplicated strings will be shown and automatically translated. When the master string is translated, its translation is automatically shared between all the duplicates. This allows translators to check and re-translate duplicated strings if necessary.
Use case: works great if you want to save time, but need the automatic translations to be reviewed.
When this option is chosen, only the master strings that were originally uploaded to the system will be available for translations. All duplicated strings will automatically gain the translations from the original strings and will be hidden in all version branches.
Couple of things to keep in mind:
Use case: works perfectly for continuous projects with various version branches. Allows translators to work with unique strings in separate branches.
When this option is chosen, the system spots the duplicated strings in all files. Only the master strings that were originally uploaded are visible and should be translated. The hidden duplicated strings will automatically share the translations from the corresponding master strings.
Use case: works great for the projects with narrow scopes where all duplicates share the same context.