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.

[EX Q]: The second algorithm incorporates recent ideas of data selection in machine translation BIBREF7 . We develop a novel re-weighting method to resolve these problems, using ideas inspired by data selection in machine translation BIBREF26 , BIBREF7 .
Question: What is the data selection paper in machine translation
[EX A]: BIBREF7 BIBREF26

[EX Q]: E2E NLG challenge Dataset: The training set of the E2E challenge dataset which consists of 42K samples was partitioned into a 10K paired and 32K unpaired datasets by a random process. The Wikipedia Company Dataset: The Wikipedia company dataset presented in Section SECREF18 was filtered to contain only companies having abstracts of at least 7 words and at most 105 words. The dataset was then divided into: a training set (35K), a development set (4.3K) and a test set (4.3K). The training set was also partitioned in order to obtain the paired and unpaired datasets.
Question: What non-annotated datasets are considered?
[EX A]: E2E NLG challenge Dataset The Wikipedia Company Dataset

[EX Q]: As neural classification model, we use a convolutional neural network (CNN) BIBREF29, which has previously shown good results for tweet classification BIBREF30, BIBREF27.
Question: What neural classifiers are used?
[EX A]:
convolutional neural network (CNN) BIBREF29