This article goes over several strategies for project managers to leverage Lilt Memories to optimize localization workflows.
TMX file sizes
TM files can be uploaded directly to Lilt if they are 200MB or smaller. For files larger than 200MB, you can zip the TMX file and upload it with the extension “.tmx.zip”. Note that Lilt currently only supports zipped “.tmx” files.
For a list of supported file types, see the Supported File Formats article.
TB CSV file format
Before uploading, you’ll want to check the Memory Settings.
- If you want the entries you import to be visible to translators immediately, set the Default TB Entry Status to Reviewed.
- If you want the imported entries to be reviewed by a linguist before becoming available for use in the Lilt Editor Terminology Pane, set the Default TB Entry Status to Unreviewed or Draft.
When uploading CSV files, the columns should be structured with the first two columns being source text and target text. If a row is missing either of these, the row will not be imported. Termbase CSV files can optionally include a header row as the first row.
Termbase example in a spreadsheet application:
Termbase example in a text editor:
CSV with header rows can be imported by using the Termbase (TB With Header) option when importing, as described in the Uploading Memory Files article.
Termbase CSV files can have as many metadata columns as you would like, and the CSV can contain rows without certain metadata columns. Each metadata field needs to be separated by a comma. In the example screenshots above, the metadata columns are “status”, “created date”, and “updated data”.
Before uploading, make sure there are not any undesired spaces in the CSV file, as all spaces are included in the imported data, even spaces directly after commas.
TMX content clean-up
To save time from having to clean up TM entries in Lilt after uploading TMX files, it is best to clean up the files beforehand. Having polluted TMX files can lead to issues with inconsistency and reduce productivity.
Things you can look out for when cleaning your TMX files:
- Sort through the older TM entries and remove entries that are outdated. This can be as easy as removing all entries that were last utilized before a given date.
- Remove duplicate TM entries that have the same source text but different target text.
TMX file naming convention
TMX files evolve over time, so to better keep track of your TMX files, it is helpful to name them with informative labels such as the date, type of content, and name of the product or project. Whatever format you choose, maintaining a consistent naming convention will help project managers stay organized and be able to easily identify which projects are associated with which Memories.
Example naming convention:
- [DATE]-[CONTENT TYPE]-[NAME]
In this example, [NAME] could be the product or the project.
Examples using this naming convention:
TM repetition management
Every time a TM is used in translation, an entry for that TM is added to the associated Memory. If the same TM is used multiple times, there will be duplicates in the Memory. In the Editor’s Segment Context pane, duplicate entries are stacked to avoid confusion. In the example below, this stacking is displayed as “+1 identical result”.
It is up to project managers to determine how often they want to remove duplicates or whether they want to remove duplicates at all. On the Manage Memory page of the Memories tab, entries are sorted by the date they were last updated, so if you want to find duplicates for a specific entry, use the search bar to filter the results.
Archiving projects to preserve TMs
If you want to remove a project from the Kanban Board, you can either archive the project or delete the project.
Archiving a project will retain that project’s TMs within the associated Memory. If you plan to reuse segments, archiving a project is generally a better option than deleting the project.
Deleting a project will also delete that project’s TMs from within the associated Memory. If you want to delete a project, consider first downloading the Memory data using the Export Memory As TMX option in case you want to utilize the project’s TMs in the future by importing the data into a Lilt Memory.