This will help make machine translation more reliable, ensuring that objective data does not get transformed along with the language presenting that data. It will also make it easier to test and validate the machine translators.

Any automated translations would still need to reviewed. I don't think we will (or should) see totally automated translations in the near future, but I do think the machine translators could be a very useful tool for editors.

Language models are impressive, but they are not efficient data retrieval systems. Denny Vrandecic, the founder of Wikidata, has a couple insightful videos about this topic.

This one talks about knowledge graphs in general, from 2020: https://www.youtube.com/watch?v=Oips1aW738Q

This one is from last year and is specifically about how you could integrate LLMs with the knowledge graph to greatly increase their accuracy, utility, and efficiency: https://www.youtube.com/watch?v=WqYBx2gB6vA

I highly recommend that second video. He does a great job laying out what LLMs are efficient for, what more conventional methods are efficient for, and how you can integrate them to get the best of both worlds.