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: Pre-trained English NER model We construct the English NER system following BIBREF7 . This system uses a bidirectional LSTM as a character-level language model to take context information for word embedding generation.  For pre-trained English NER system, we use the default NER model of Flair. 
 Question: Which pre-trained English NER model do they use?
Example Output: Bidirectional LSTM based NER model of Flair

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 acquired the data in two rounds of annotation. In the first one, we were looking for original and uncommon sentence change suggestions. 
 Question: How do they introduce language variation?
Example Output:
 we were looking for original and uncommon sentence change suggestions

