sentence and paragraph prediction for hotpotqa

Hi

In the page 14 of the paper,
> For evidence extraction we apply 2 layer feedforward networks on top of the representations corresponding to sentence and paragraph tokens to get the corresponding evidence prediction scores and use binary cross entropy loss to train the model.

Is the 2 layer feedforward networks something likes
```
torch.nn.Sequential(
torch.nn.Linear(self.model.config.hidden_size, self.model.config.hidden_size)
torch.nn.ReLU(),
torch.nn.Linear(self.model.config.hidden_size, 1), # score for 'yes', while 0 for 'no'
)
```

Besides, do you predict sentence and paragraphs separately or nested? The reason I ask is that gold sentences are always inside of gold paragraphs. When predict and compute the support f1, does a sentence considered as predicted positive has to be within a paragraph predicted positive? Do you use a hard threshold for both sentence and paragraph prediction?

Thank you