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.

Example Input: The English online magazine of ISIS was named Dabiq and first appeared on the dark web on July 2014 and continued publishing for 15 issues. This publication was followed by Rumiyah which produced 13 English language issues through September 2017. Looking through both Dabiq and Rumiyah, many issues of the magazines contain articles specifically addressing women, usually with " to our sisters " incorporated into the title.
Question: Do they report results only on English data?
Example Output: Yes

Example Input: More generally, we know little about the types of development issues that different countries prioritise, or whether country-specific factors such as wealth or democracy make countries more likely to push for specific development issues to be put on the global political agenda. We find that discussion of Topic 2 is not significantly impacted by country-specific factors, such as wealth, population, democracy, levels of ODA, and conflict (although there are regional effects).
Question: What are the country-specific drivers of international development rhetoric?
Example Output: wealth democracy population levels of ODA conflict

Example Input: We extract 5 Surface and Lexical features, namely sequence length in number of tokens, average word length, type-token ratio, and lexical to tokens ratio (ratio of adjectives, verbs, nouns, and adverbs to tokens). We extracted two features that use a learned representation: Firstly, we get a sentence embedding feature that is built by averaging the word embeddings of an input sentence. Secondly, we extract a fastText representation using the fastText library with the same parameters as reported in Joulin et al. joulin2016bag.
Question: Do they differentiate insights where they are dealing with learned or engineered representations?
Example Output:
Yes