Recognizing long strings as a single slot

What technique would make Snips accurate at reading long strings?

If I had several training statements that looked like:

The [reader:name](boy) read "[title:book_title](A Connecticut Yankee in King Arthur's Court)".
The [reader](girl) read "[title]The Scarlet Letter".

A chatbot that heard:
The man read “There and Back Again: A Hobbit’s Tale”

would likely return three “title” slots, containing “there”, “and Back Again”, “Hobbit’s Tale”.
Note what I did with the capitalization and dropping a few pieces, because this is what I’m actually seeing. Snips will split the book’s name between multiple slots, do random things to capitalization, and even drop random pieces.

Is there a technique or way to tag the training data so that Snips doesn’t get “creative”, and just returns the whole string in the same way it was passed in?

This issue is discussed here --> https://github.com/snipsco/snips-nlu/issues/810