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.

[Q]: This section introduces our probabilistic model that infers keyword expectation and trains the target model simultaneously.
Question: What type of classifiers are used?
[A]: probabilistic model

[Q]: Despite the focus on sharing datasets and source codes on popular software development platforms such as GitHub (github.com) or Zenodo (zenodo.org), it is still a challenge to use data or code from other groups.
Question: Are datasets publicly available?
[A]: Yes

[Q]: 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?
[A]:
the dataset consists of pathology reports including sentences and questions and answers about tumor size and resection margins so it does include additional sentences