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.

We defined the reward as being 1 for successfully completing the task, and 0 otherwise. A discount of $0.95$ was used to incentivize the system to complete dialogs faster rather than slower, yielding return 0 for failed dialogs, and $G = 0.95^{T-1}$ for successful dialogs, where $T$ is the number of system turns in the dialog.   0.95^{T-1} reward  0.95^{T-1}  
 Question: What is the reward model for the reinforcement learning appraoch?
reward 1 for successfully completing the task, with a discount by the number of turns, and reward 0 when fail

This paper used the real-time method to randomly collect 10% of publicly available English tweets using several pre-defined DDEO-related queries (Table TABREF6 ) within a specific time frame.  
 Question: Do they evaluate only on English data?
Yes

Across all 26 datasets, RCRN outperforms not only standard BiLSTMs but also 3L-BiLSTMs which have approximately equal parameterization. 
 Question: Does their model have more parameters than other models?

approximately equal parameterization