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.

Input: Consider 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?

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


Input: Consider Input: We then show the tweet text and image and we ask them to classify it in one of 6 categories: No attacks to any community, racist, sexist, homophobic, religion based attacks or attacks to other communities. 
 Question: What annotations are available in the dataset - tweat used hate speach or not?

Output: No attacks to any community  racist sexist homophobic religion based attacks attacks to other communities


Input: Consider Input: Given that words from texts of the same class belong to the same context, it is possible to model word vectors of each class as word subspaces and efficiently compare them in terms of similarity by using canonical angles between the word subspaces.  
 Question: What can word subspace represent?


Output: Word vectors, usually in the context of others within the same class