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.

[EX Q]: The third person plural pronoun 'they' has no gender in English and most other languages (unlike the third person singular pronouns 'he', 'she', and 'it'). If these sentences are translated into French, then 'they' in the first sentence should be translated 'elles', as referring to Jane and Susan, and 'they' in the second sentence should be translated 'ils', as referring to Fred and George. A couple of examples: The word 'sie' in German serves as both the formal second person prounoun (always capitalized), the third person feminine singular, and the third person plural.
Question: What language do they explore?
[EX A]: English French German

[EX Q]: In particular, we aggregate documents from the CommonCrawl dataset that has the most overlapping n-grams with the questions. We name this dataset STORIES since most of the constituent documents take the form of a story with long chain of coherent events. Figure 5 -left and middle show that STORIES always yield the highest accuracy for both types of input processing.
Question: Which of their training domains improves performance the most?
[EX A]: documents from the CommonCrawl dataset that has the most overlapping n-grams with the question

[EX Q]: For a fair comparison, we trained each model on the same corpus of 10 million sentences gathered from Wikipedia.
Question: On which dataset(s) do they compute their word embeddings?
[EX A]:
10 million sentences gathered from Wikipedia