In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

[Q]: We downloaded 76 videos from a tutorial website about an image editing program . 
[A]: What is the source of the triples?


[Q]: The first type of classifier we evaluate in this work are feedforward neural networks (DNNs) consisting of 3 hidden layers, each with 512 rectified linear units (ReLUs) with a softmax activation function. As a second classifier to evaluate, we use convolutional neural networks (CNNs) with 2 convolutional and max pooling layers, followed by 2 fully-connected ReLU layers with 512 nodes.
[A]: What type of models are used for classification?


[Q]: Intuitively, under-translated input words should contribute little to the NMT outputs, yielding much smaller word importance.  By exploiting the word importance calculated by Attribution method, we can identify the under-translation errors automatically without the involvement of human interpreters. 
[A]:
How do they measure which words are under-translated by NMT models?