MTL enables learning many tasks jointly, encapsulating them in a single model and leveraging their shared representation (Caruana, 1997;Ruder, 2017).
we will use a hard-sharing architecture: the sentence is first processed by stacked BILSTMs shared across all tasks, with a task-dependent feed-forward network on the top of it, to compute each task's outputs.