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: Last, we evaluate our approaches in 9 commonly used text classification datasets. We evaluate our methods on several commonly used datasets whose themes range from sentiment, web-page, science to medical and healthcare.
Question: What NLP tasks do they consider?
Example Output: text classification for themes including sentiment, web-page, science, medical and healthcare

Example Input: Then we define the similarity between INLINEFORM7 and INLINEFORM8 by, DISPLAYFORM0 We note that the similarity metric defined above for sentences is equally applicable for n-gram retrieval.
Question: Which similarity measure do they use in their n-gram retrieval approach?
Example Output: we define the similarity between INLINEFORM7 and INLINEFORM8 by, DISPLAYFORM0

Example Input: We use Gaussian Processes as this probabilistic kernelised framework avoids the need for expensive cross-validation for hyperparameter selection
Question: Why is a Gaussian process an especially appropriate method for this classification problem?
Example Output:
avoids the need for expensive cross-validation for hyperparameter selection