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.

Q: We also applied our model to MCTest dataset which requires machines to answer multiple-choice reading comprehension questions about fictional stories.  
 Question: Do they experiment with their proposed model on any other dataset other than MovieQA?

A: Yes
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Q: (2) Different from LEM and DPEMM, AEM uses a generator network to capture the event-related patterns and is able to mine events from different text sources (short and long). Moreover, unlike traditional inference procedure, such as Gibbs sampling used in LEM and DPEMM, AEM could extract the events more efficiently due to the CUDA acceleration; 
 Question: What alternative to Gibbs sampling is used?

A: generator network to capture the event-related patterns
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Q: Table 1 shows an example of difficult and easy examples according to our definition of difficulty. The underlined text demarcates the (consensus) reference label provided by domain experts. In the difficult examples, crowd workers marked text distinct from these reference annotations; whereas in the easy cases they reproduced them with reasonable fidelity. The difficult sentences usually exhibit complicated structure and feature jargon. 
 Question: Is an instance a sentence or an IE tuple?

A:
sentence
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