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: 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?

SOLUTION: English French German 

PROBLEM: To learn better graph representation of multi-party dialogues, we adopt the dialogues with 8-15 utterances and 3-7 speakers. To simplify the task, we filter the dialogues with long sentences (more than 20 words). Finally, we obtain 52,053 dialogues and 460,358 utterances. 
 Question: How large is the proposed dataset?

SOLUTION: we obtain 52,053 dialogues and 460,358 utterances

PROBLEM: To evaluate the usefulness of our corpus for SMT purposes, we used it to train an automatic translator with Moses BIBREF8 . 
 Question: What SMT models did they look at?

SOLUTION:
automatic translator with Moses