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.

Example Input: For example, it can be used to extract features for usage with other machine learning tools, or to evaluate given features with the existing classifiers or regressors. Figure FIGREF19 demonstrates a simple feature extractor that retrieves the sentence length. 
 Question: Do they show an example of usage for INFODENS?
Example Output: Yes

Example Input: In this paper, we introduce automatic `drunk-texting prediction' as a computational task. Given a tweet, the goal is to automatically identify if it was written by a drunk user.  
 Question: Do the authors equate drunk tweeting with drunk texting? 
Example Output: Yes

Example Input: Results and Analysis 
 Question: what quantitative analysis is done?
Example Output:
Answer with content missing: (Evaluation section) Given that in CLIR the primary goal is to get a better ranked list of documents against a translated query, we only report Mean Average Precision (MAP).

