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: We use Waseem and Hovy BIBREF5, Davidson et al. BIBREF9, and Waseem et al. BIBREF10 as baselines and compare the results with our different fine-tuning strategies using pre-trained BERTbase model.  
 Question: What baseline is used?
Example Output: Waseem and Hovy BIBREF5 Davidson et al. BIBREF9 Waseem et al. BIBREF10

Example Input: These workers completed 1001 tasks: 496 tasks in the control and 505 in the AUI.  
 Question: How many responses did they obtain?
Example Output: 1001

Example Input: We sampled all papers published in the Computer Science subcategories of Artificial Intelligence (cs.AI), Machine Learning (cs.LG), Social and Information Networks (cs.SI), Computational Linguistics (cs.CL), Computers and Society (cs.CY), Information Retrieval (cs.IR), and Computer Vision (CS.CV), the Statistics subcategory of Machine Learning (stat.ML), and Social Physics (physics.soc-ph). We filtered for papers in which the title or abstract included at least one of the words “machine learning”, “classif*”, or “supervi*” (case insensitive). We then filtered to papers in which the title or abstract included at least “twitter” or “tweet” (case insensitive), which resulted in 494 papers. We used the same query on Elsevier's Scopus database of peer-reviewed articles, selecting 30 randomly sampled articles, which mostly selected from conference proceedings. One paper from the Scopus sample was corrupted, so only 29 papers were examined. 
 Question: How were the machine learning papers from ArXiv sampled?
Example Output:
sampled all papers published in the Computer Science subcategories of Artificial Intelligence (cs.AI), Machine Learning (cs.LG), Social and Information Networks (cs.SI), Computational Linguistics (cs.CL), Computers and Society (cs.CY), Information Retrieval (cs.IR), and Computer Vision (CS.CV), the Statistics subcategory of Machine Learning (stat.ML), and Social Physics (physics.soc-ph) filtered for papers in which the title or abstract included at least one of the words “machine learning”, “classif*”, or “supervi*” (case insensitive) filtered to papers in which the title or abstract included at least “twitter” or “tweet” (case insensitive)