How to make a Neural network understand that multiple inputs are related to the same entity? Neural networks can have multiple inputs.
But some times two or more of these inputs can often be related to a single entity.

E.g : Height and weight of a person to predict the probability of disease or price and Volume of a stock to predict it's value.

How can we make a neural network understand that two inputs are related to the same entity?
Is there any efficient (or inefficient) way of 'tagging' them together?
It is not necessary to indicate this to the neural network (and not possible).  This is not part of how neural networks are typically used -- or part of how other machine learning algorithms are used, either.

I confess I'm not clear on why you think it would make a difference, but it doesn't matter: there's no way (that I know of) to do that, and it's not something people normally do.