We aim to construct an efficient emulator to derive a generalized solution operator for related scenarios. To that end, we use the learned labels (emergent coordinates) to model a neural operator. The DeepONet model is constructed on the emergent space, time, and parameter embeddings such that we learn the solution operator, Ψ, defined as: