Best strategy for extracting specific structured data from unstructured sentences
The task is a specific case of  NER (technically NER is a sequence labeling task, a special case of classification).
I think you would have two main options:

Apply a pre-trained NER model: most deal with time entities but not always very accurately, and it wouldn't be specifically adapted to your data so you wouldn't obtain the distinction between the three types of values. Advantage: no need for training data.
Train your own NER model: that's the ideal scenario in terms of performance, assuming you have (or can have) a good amount of annotated data for training.