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: Based on annotated corpora and token-based features, studies used machine learning approaches to build word segmentation systems with accuracy about 94%-97%. 
 Question: How successful are the approaches used to solve word segmentation in Vietnamese?
Example Output: Their accuracy in word segmentation is about 94%-97%.

Example Input: The De7 database used for this study was designed by Marc Schroeder as one of the first attempts of creating diphone databases for expressive speech synthesis BIBREF2. The database contains three voice qualities (modal, soft and loud) uttered by a German female speaker, with about 50 minutes of speech available for each voice quality. 
 Question: What large corpus is used for experiments?
Example Output:
The De7 database