How do we know the true value of a parameter, in order to check estimator properties? For example, we say that an estimator is unbiased if the expected value of the estimator is the true value of the parameter we're trying to estimate. However, if we already know the true value of the parameter, why are we trying to estimate it? I know there's something I'm missing here, like some theoretical true value that we can find, otherwise I don't see how we can check for unbiasedness, consistency etc.

In practice we don't know the true value of the parameter. However, if we are to use the estimator, we have to know its properties - to be sure that it is a good one (or at least suitable/acceptable under the circumstances.)
What we do usually assume to know is the underlying statistical distribution or, at least, some kind of a model structure (in case of non-parametric estimators.)
