But I'm not sure this is the right way to do it.
Given that most of the information on Wikipedia is "narrative", and doesn't consist of facts contained in Wikidata (e.g. a history article recounting a battle, or a movie article explaining the plot), this scope for this will be extremely limited. The creators are attempting to address this by actually containing every single aspect of a movie's plot as a fact, and that sentences are functions that express those facts... but this seems entirely unwieldy and just too much work.
What I've wished for instead, for years, is actually an underlying "metalanguage" that expresses the vocabulary and grammatical concepts in all languages. Very loosely, think of an "intermediate" linguistic representation layer in Google Translate.
Obviously nobody can write in that directly in a user-friendly way. But what you could do is take English (or any language) text, do an automated translation into that intermediate representation, then ask the author or volunteers to identify all ambiguous language cases" -- e.g. it would ask if "he signed" means made his signature, or communicated in sign language. It would also ask for things that would need clarification perhaps not in your own language but in other languages -- e.g. what noun does "it" refer to, so another language will know to use the masculine or feminine version. All of this can be done within your own language to produce an accurate language-agnostic "text".
Then, out of this intermediate canonical interpretation, every article on Wikipedia would be generated back out of it, in all languages, and perfectly accurately, because the output program isn't even ML, it's just a straight-up rule engine.
Interestingly, an English-language original might be output just a little bit different but in ways that don't change the meaning. Almost like a language "linter".
Anyways -- I think it would actually be doable. The key part is a "Google Translate"-type tool that does 99% of the work. It would need manual curation of the intermediate layer with a professional linguist from each language, as well as manually curated output rules (although those could be generated by ML as a first pass).
But something like that could fundamentally change communication. Imagine if any article you wanted to make available perfectly translated to anyone, you could do, just with the extra work of resolving all the ambiguities a translating program finds.