When I first learned about the OmegaWiki project (called WiktionaryZ then, I think), I was thrilled. It tried to represent lexical (Wiktionary) definitions and other language concepts using data. For each sense of each word, a so called DefinedMeaning was created. In the same sense, Wikidata has its entities. But soon, I learned about a problematic aspect of OmegaWiki’s concept, and the same thing appears on Wikidata: You represent some set of concepts in a single language, then another language comes and needs to split some concepts in two, because your language uses one word for both, but the other differentiates between them. Then, a third language comes and it maps its concepts to your existing set still a bit differently, so you might get four entities for just three languages. Etc.
On Wikidata, more focus is, I guess, on “concrete” entities: people, places, etc., where this does not appear that often. But it contains the abstract entities as well, and the problem appears there all the time. You might try to “fix” the problematic entities by splitting them to more elementary, linked using “subclass of” etc.; in some cases it might work quite fine (but losing the interwiki links in the process, which is unfortunate, given those were the original use case of Wikidata), in others, it is basically impossible without a degree in philosophy and deep understanding of ten languages, to be able to correctly distinguish and represent their relations. And imagine somebody trying to _use_ those entities. Like “I would like to say this person was a writer”, but there are seventeen entities with the English label of “writer”, distinguished by some obscure difference used by a group of Sino-Tibetan languages.
And… Wikidata entities represent basically just nouns.
So… I am a bit sceptical.
(I blame viewing it on mobile.)
Not all languages have "X is Y" constructs, but all known human languages have some structure to declare that object X has property Y. Capture the idea "Object X has property Y" in your semantic language, and a grammar engine can wire that down to your target language.
The largest risk is that the resulting text will be dry as hell, not that it's an impossible task.
I'd also be worried about ambiguity; humans can (sometimes) detect when they may be parsed the wrong way in context. I wonder if there will be a way to flag results that don't properly convey the data. How would that be integrated into the generator? (There's probably an answer in the literature.)
Lots of fun questions to explore.
What is hard in that the conjucts do not have unique identifiers in the example. That is an essential thing to have. As there is plenty of synonyms and meaning might change. Same applies to center.