Tips on structured data translation

Hello -

I am trying to build a translator to translate between one set of structured data to another set of structured data. By structured data I mean data that is formatted using specific standards or rules.

For example, structured data input could be latin alphanumerics, in JSON format, using predefined syntax and ruled. The structured data output could be something similar, but perhaps XML.

Do I treat this as if I were building a model to translate between, say, German and English? Or should I be thinking about it another way?

Generating models that translate / produce logical content is one thing…but what about when the syntax / structure of the data also communicates information?

For example, please consider the made-up JSON below - how would I train a model to understand that the key : value pair structure means just that, a key value pair? Or training a model to understand that the menuitem field equivocates to a data structure containing three elements?

Please dont take those questions as literal, I’m trying to understand how to approach training a model where the structure of the data itself communicates information.

Thank you

{“menu”: {
“id”: “file”,
“value”: “File”,
“popup”: {
“menuitem”: [
{“value”: “New”, “onclick”: “CreateNewDoc()”},
{“value”: “Open”, “onclick”: “OpenDoc()”},
{“value”: “Close”, “onclick”: “CloseDoc()”}