如何将RNN应用于序列到序列的NLP任务？

I'm quite confused about sequence-to-sequence RNN on NLP tasks. Previously, I have implemented some neural models of classification tasks. In those tasks, the models take word embeddings as input and use a softmax layer at the end of the networks to do classification. But how do neural models do seq2seq tasks? If the input is word embedding, then what is the output of the neural model? Examles of these tasks include question answering, dialogue systems and machine translation.I'm quite confused about sequence-to-sequence R