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: As one of our aims is to compare coreference chain properties in automatic translation with those of the source texts and human reference, we derive data from ParCorFull, an English-German corpus annotated with full coreference chains BIBREF46. 
 Question: What languages are seen in the news and TED datasets?
Example Output: English German

Example Input: Compared with 2015, our QA-SRL gold yielded 1593 annotations, with 989 core and 604 adjuncts, while theirs yielded 1315 annotations, 979 core and 336 adjuncts.  
 Question: How much more coverage is in the new dataset?
Example Output: 278 more annotations

Example Input: We evaluate our method on two widely-studied datasets provided by Waseem and Hovey BIBREF5 and Davidson et al. BIBREF9. 
 Question: Which publicly available datasets are used?
Example Output:
Waseem-dataset Davidson-dataset,