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.

[EX Q]: 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?
[EX A]: tutorial videos for a photo-editing software

[EX Q]: As a starting point, we used the DIP corpus BIBREF37 , a collection of 49 clusters of 100 web pages on educational topics (e.g. bullying, homeschooling, drugs) with a short description of each topic. 
 Question: Which collections of web documents are included in the corpus?
[EX A]: DIP corpus BIBREF37

[EX Q]:  We use standard Precision, Recall and F1 at mention level (Micro) and at the document level (Macro) as measurements. We can see the average linking precision (Micro) of WW is lower than that of TAC2010, and NCEL outperforms all baseline methods in both easy and hard cases. 
 Question: How do they verify generalization ability?
[EX A]:
By calculating Macro F1 metric at the document level.