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.

Input: Consider Input: Table TABREF20 shows that, on WoZ and DSTC2 datasets, SIM model has the same number of parameters, which is only 23% and 19% of that in GLAD model. 
 Question: How do they measure model size?

Output: By the number of parameters.


Input: Consider Input: For all tasks, we use a TensorFlow implementation. AraNet predicts age, dialect, gender, emotion, irony, and sentiment from social media posts. It delivers state-of-the-art and competitive performance on these tasks and has the advantage of using a unified, simple framework based on the recently-developed BERT model.  
 Question: Did they experiment on all the tasks?

Output: Yes


Input: Consider Input: Using this annotation model, we create a new large publicly available dataset of English tweets. 
 Question: In what language are the tweets?


Output: English