Keras data structure for LSTM-networks
Your target y can be whatever you need. 

If you want to do sequence to sequence for example, y will have the same number of time steps than the inputs (you predict something for each timestep).

But you can also define an output with one timestep only, for text classification for example.
Your input data has 10 timesteps, but the output is only a prediction at the last timestep.

It depends on the problem you’re trying to solve.