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:
We evaluate our newly proposed models and related baselines in several low-resource settings across different languages with real, distantly supervised data with non-synthetic noise. The advanced modeling of the noisy labels substantially improves the performance up to 36% over methods without noise-handling and up to 9% over all other noise-handling baselines. 
 Question: Did they evaluate against baseline?

Ex Output:
Yes


Ex Input:
In this work, we use pretraining on the unlabeled data of each task and show that it can increase the performance of classification systems. 
 Question: Where is MVCNN pertained?

Ex Output:
on the unlabeled data of each task


Ex Input:
 In this work, we consider words that can indicate the characteristics of the neighbor words as contextual keywords and develop an approach to generate features from the automatically extracted contextual keywords. 
 Question: What contextual features are used?

Ex Output:

The words that can indicate the characteristics of the neighbor words as contextual keywords and generate it from the automatically extracted contextual keywords.