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:
The Y-axis in the figure is the success rate of the agent (measured in terms of number of dialogs that resulted in launching a skill divided by total number of dialogs), and the X-axis is the number of learning steps.  
 Question: How did they measure effectiveness?

Ex Output:
number of dialogs that resulted in launching a skill divided by total number of dialogs


Ex Input:
To capture this interesting property, we propose a new tagging scheme consisting of three tags, namely { INLINEFORM0 }.

INLINEFORM0 tag indicates that the current word appears before the pun in the given context.

INLINEFORM0 tag highlights the current word is a pun.

INLINEFORM0 tag indicates that the current word appears after the pun. 
 Question: What is the tagging scheme employed?

Ex Output:
A new tagging scheme that tags the words before and after the pun as well as the pun words.


Ex Input:
For training, three types of Recurrent Neural Network (RNN) layers are used – an encoder layer, a decoder layer and an output layer. These layers together form a LSTM model. LSTM is typically used in seq2seq translation. 
 Question: What is the architecture of the system?

Ex Output:

seq2seq translation