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:
Three datasets annotated with emotions are commonly used for the development and evaluation of emotion detection systems, namely the Affective Text dataset, the Fairy Tales dataset, and the ISEAR dataset. A summary is provided in Table TABREF8 , which also shows, in the bottom row, what role each dataset has in our experiments: apart from the development portion of the Affective Text, which we used to develop our models (Section SECREF4 ), all three have been used as benchmarks for our evaluation. 
 Question: Which existing benchmarks did they compare to?

Ex Output:
Affective Text Fairy Tales ISEAR


Ex Input:
The ratio of correct `translations' (matches) was used as an evaluation measure. 
 Question: What evaluation metric do they use?

Ex Output:
Accuracy


Ex Input:
We compare the results of our model to a baseline multi-task architecture inspired by yang2016multi. In our baseline model there are no explicit connections between tasks - the only shared parameters are in the hidden layer. 
 Question: What is the baseline?

Ex Output:

The baseline is a multi-task architecture inspired by another paper.