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.

[Q]: 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?
[A]: CNN, TIME, 20 Newsgroups, and Reuters-21578

[Q]: The UNGA speeches dataset, compiled by Baturo et al. UNGAspeeches, contains the text from 7,507 speeches given between 1970-2015 inclusive.
Question: how many speeches are in the dataset?
[A]: 7,507

[Q]: replacing this single GRU with two different components first component is a sentence reader second component is the input fusion layer
Question: What changes they did on input module?
[A]:
For the DMN+, we propose replacing this single GRU with two different components. The first component is a sentence reader The second component is the input fusion layer