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: 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?
Example Output: the dataset consists of pathology reports including sentences and questions and answers about tumor size and resection margins so it does include additional sentences

Example Input: A "coding scheme" is defined, which is a set of labels, annotations, or codes that items in the corpus may have. Schemes include formal definitions or procedures, and often include examples, particularly for borderline cases. Next, coders are trained with the coding scheme, which typically involves interactive feedback. Training sometimes results in changes to the coding scheme, in which the first round becomes a pilot test. Then, annotators independently review at least a portion of the same items throughout the entire process, with a calculation of "inter-annotator agreement" or "inter-rater reliability." Finally, there is a process of "reconciliation" for disagreements, which is sometimes by majority vote without discussion and other times discussion-based.
Question: What are the core best practices of structured content analysis?
Example Output: "coding scheme" is defined coders are trained with the coding scheme Training sometimes results in changes to the coding scheme calculation of "inter-annotator agreement" or "inter-rater reliability." there is a process of "reconciliation" for disagreements

Example Input: To adapt the FactorCell BIBREF4 for our purposes, we replace user embeddings with a low-dimensional image representation. Thus, we are able to modify each query completion to be personalized to a specific image representation.
Question: How they complete a user query prefix conditioned upon an image?
Example Output:
we replace user embeddings with a low-dimensional image representation