Assume that we have a continuous uniform random number generator on $(0, 1)$.
It is well-known that rejection-acceptance sampling can be used to generate standard normal random variable $Z$ by comparing standard normal density function with exponential density function, where the latter can be generated through inverse sampling transform (the inverse CDF of exponential distribution has a closed form).
However, suppose that we impose certain condition on $Z$, say $Z>-1$. How can one generate random samples that fulfill this condition?