TASK DEFINITION: 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.
PROBLEM: Our dataset is annotated based on Chinese pathology reports provided by the Department of Gastrointestinal Surgery, Ruijin Hospital. It contains 17,833 sentences, 826,987 characters and 2,714 question-answer pairs.  
 Question: How big is QA-CTS task dataset?

SOLUTION: 17,833 sentences, 826,987 characters and 2,714 question-answer pairs

PROBLEM: Because our approach is specifically intended to yield sentences that are grammatical, we additionally consider the following log ratio (i.e., the grammatical phrase over the ungrammatical phrase): 
 Question: How do they measure grammaticality?

SOLUTION: by calculating log ratio of grammatical phrase over ungrammatical phrase

PROBLEM: We further explore the effect of INLINEFORM0 -gram length in our model (i.e., the filter size for the covolutional layers used by the attention parsing module). In Figure FIGREF39 we plot the AUC scores for link prediction on the Cora dataset against varying INLINEFORM1 -gram length.  
 Question: Do they measure how well they perform on longer sequences specifically?

SOLUTION:
Yes