For integer/dates values annotated, does the model learn the range of values as well?

I have a prodigy session set up to annotate certain numeric values in a document for age (ranges from 0 to 100). I am only annotating the number. My question is, suppose there is a corrupt value which crept in (age being 1000 or 22.7), will the model understand that even though it is close to the age text in the document, it should not be picked up?

In other words, can it learn the range of integer values, and if it does, will that work for date format as well?
For instance a date in the format dd/mm/yyyy which is DOB (all the annotated ones are < 01/01/2000) and there is a date 31/12/2020, will that get picked up as well since all the annotated dates are nowhere close to this range?

Thank you

The model will regard a numeric token as just a token, and while it might learn some ordering of numbers, you shouldn't rely on that. You're much better off doing that sort of logic explicitly, it's not where the machine learning model will be best utilised.

It's possible the model could start to rely on particular substring characters of dates, but I think those probably wouldn't be decisive. You might want to normalize the date texts if this is likely to be a problem that will inhibit generalization.