TASK DEFINITION: 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.
PROBLEM: 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?

SOLUTION: Yes

PROBLEM: After removing 135 questions during the validation, the final dataset comprises 13,939 questions, 3,827 of which require commonsense knowledge (i.e. 27.4%).  
 Question: what is the size of their dataset?

SOLUTION: 13,939

PROBLEM: Our VG training set consists of 85% of the data: 16k images and 740k corresponding region descriptions. 
 Question: How big is data provided by this research?

SOLUTION:
16k images and 740k corresponding region descriptions