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: However, no prior work has explored the target of the offensive language, which is important in many scenarios, e.g., when studying hate speech with respect to a specific target. 
 Question: What are the differences between this dataset and pre-existing ones?
Example Output: no prior work has explored the target of the offensive language

Example Input: We combine 13k questions gathered from this pipeline with an additional 3k questions with yes/no answers from the NQ training set to reach a total of 16k questions.  
 Question: what is the size of BoolQ dataset?
Example Output:  16k questions

Example Input: Just as introduced in sec:introduction, it is intractable to compute similarity exactly, as involving INLINEFORM0 computation. Hence, we consider the monte-carlo approximation: DISPLAYFORM0

where INLINEFORM0 is a list of entity pairs sampled from INLINEFORM1 . We use sequential sampling to gain INLINEFORM6 , which means we first sample INLINEFORM7 given INLINEFORM8 from INLINEFORM9 , and then sample INLINEFORM10 given INLINEFORM11 and INLINEFORM12 from INLINEFORM13 . 
 Question: Which sampling method do they use to approximate similarity between the conditional probability distributions over entity pairs?
Example Output:
monte-carlo sequential sampling