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 perform a direct comparison of expert and crowd contributors, for 1000 term groups based on the number of total annotations(200 term groups with 2 total annotations, 200 term groups with 3 total annotations, and so on up to term groups with 6 total annotations).  Evaluators were given a summary of the annotations received for the term group in the form of:The term group "inequality inequity" received annotations as 50.0% sadness, 33.33% disgust, 16.67% anger. Then, they were asked to evaluate on a scale from 1 to 5, how valid these annotations were considered. 
 Question: How do they compare lexicons?
Human evaluators were asked to evaluate on a scale from 1 to 5 the validity of the lexicon annotations made by the experts and crowd contributors.

Twitter data: We used the Twitter API to scrap tweets with hashtags. All non-English tweets were filtered out by the API. 
 Question: Do they evaluate only on English datasets?
Yes

To make the annotated data publicly available, we selected 70 news articles from Arabic WikiNews site. These articles cover recent news from year 2013 to year 2015 in multiple genres (politics, economics, health, science and technology, sports, arts, and culture.) Articles contain 18,300 words, and they are evenly distributed among these 7 genres with 10 articles per each. 
 Question: What is the size of the dataset?

Articles contain 18,300 words, and they are evenly distributed among these 7 genres with 10 articles per each