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: They can answer each question with either `yes', `rather yes', `rather no', or `no'. They can supplement each answer with a comment of at most 500 characters. 
 Question: What annotations are present in dataset?
Example Output: answer each question with either `yes', `rather yes', `rather no', or `no'. can supplement each answer with a comment of at most 500 characters

Example Input: Although no perfect matches exist, we decided upon the Quora duplicate question dataset BIBREF22 as the best match. To study the embeddings, we computed the euclidean distance between the two questions using various embeddings, to study the distance between semantically similar and dissimilar questions. 
 Question: What existing corpus is used for comparison in these experiments?
Example Output: Quora duplicate question dataset BIBREF22

Example Input: We first evaluate our converted embedding models on multi-language lexical similarity and relatedness tasks, as a sanity check, to make sure the word sense induction process did not hurt the general performance of the embeddings. Then, we test the sense embeddings on WSD task. 
 Question: Was any extrinsic evaluation carried out?
Example Output:
Yes