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.

Input: Consider Input: In the experiments, we consider four data sets, two of them newly created and the remaining two already public: CNN, TIME, 20 Newsgroups, and Reuters-21578. The code and the two new data sets are available at github.com/baiyangwang/emgan. For the pre-processing of all the documents, we transformed all characters to lower case, stemmed the documents, and ran the word2vec model on each corpora to obtain word embeddings with a size of 300. In all subsequent models, we only consider the most frequent INLINEFORM0 words across all corpora in a data set. 
 Question: Which corpora do they use?

Output: CNN, TIME, 20 Newsgroups, and Reuters-21578


Input: Consider Input: The datasets used for training, validation and testing contain sentences extracted from the Europarl corpus BIBREF1 and SoNaR corpus BIBREF2. The Europarl corpus is an open-source parallel corpus containing proceedings of the European Parliament. The Dutch section consists of 2,333,816 sentences and 53,487,257 words. The SoNaR corpus comprises two corpora: SONAR500 and SONAR1. The SONAR500 corpus consists of more than 500 million words obtained from different domains. 
 Question: What are the sizes of both datasets?

Output: The Dutch section consists of 2,333,816 sentences and 53,487,257 words. The SONAR500 corpus consists of more than 500 million words obtained from different domains.


Input: Consider Input: The approaches we use and what we mean by `success' are thus guided by our research questions.

Domain experts and fellow researchers can provide feedback on questions and help with dynamically revising them. Sometimes we also hope to connect to multiple disciplines. Questions about potential “dual use” may also arise. 
 Question: What approaches do they use towards text analysis?


Output: Domain experts and fellow researchers can provide feedback on questions and help with dynamically revising them. connect to multiple disciplines dual use