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.

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. All question-answer pairs are annotated and reviewed by four clinicians with three types of questions, namely tumor size, proximal resection margin and distal resection margin.  
 Question: Is all text in this dataset a question, or are there unrelated sentences in between questions?
the dataset consists of pathology reports including sentences and questions and answers about tumor size and resection margins so it does include additional sentences 

Our model contains five independent decoders, one for each image in the sequence. This allows each decoder to learn a specific language model for each position of the sequence. 
 Question: Do the decoder LSTMs all have the same weights?
No

The average classification accuracy results are summarised in Table TABREF9. 
 Question: What evaluation metric is used?

average classification accuracy