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.

Ex Input:
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?

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


Ex Input:
A meta-research study found only 1 in 9 qualitative papers in Human-Computer Interaction reported inter-rater reliability metrics BIBREF31. Another related area are meta-research and methods papers focused on identifying or preventing low-effort responses from crowdworkers — sometimes called “spam” or “random” responses, or alternatively ”fraudsters” or ”cheaters.” Rates of “self-agreement” are often used, determining if the same person labels the same item differently at a later stage. 
 Question: What are the key issues around whether the gold standard data produced in such an annotation is reliable? 

Ex Output:
 only 1 in 9 qualitative papers in Human-Computer Interaction reported inter-rater reliability metrics low-effort responses from crowdworkers


Ex Input:
As shown in Table TABREF12, the T-T model significantly outperforms the LSTM-based RNN-T baseline. 
 Question: What was previous state of the art model?

Ex Output:

LSTM-based RNN-T