In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

The dataset includes about 6,000 triples, comprised of videos, questions, and answer spans manually collected from screencast tutorial videos with spoken narratives for a photo-editing software.  
 Question: What kind of instructional videos are in the dataset?
tutorial videos for a photo-editing software

We recruited 100 crowdworkers on Amazon Mechanical Turk (AMT) and measured completion times and accuracies for typing randomly sampled sentences from the Yelp corpus.  
 Question: What user variations have been tested?
completion times and accuracies 

Our encoder-decoder framework employs separate encoding for different speakers in the dialog. User utterances $x_t^{usr}$ and system utterances $x_t^{sys}$ are fed into a user encoder and a system encoder separately to obtain encoder hidden states $h_{i}^{usr}$ and $h_{i}^{sys}$ . We integrate semantic slot scaffold by performing delexicalization on original dialogs. Delexicalization is a common pre-processing step in dialog modeling. We integrate dialog domain scaffold through a multi-task framework. Dialog domain indicates different conversation task content, for example, booking hotel, restaurant and taxi in MultiWOZ dataset. 
 Question: How does SPNet utilize additional speaker role, semantic slot and dialog domain annotations?

Our encoder-decoder framework employs separate encoding for different speakers in the dialog. We integrate semantic slot scaffold by performing delexicalization on original dialogs. We integrate dialog domain scaffold through a multi-task framework.