In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

[EX Q]: We use two datasets in this work: the training is done on the Fisher Corpus English Part 1 (LDC2004S13) BIBREF15 and testing on the Suicide Risk Assessment corpus BIBREF16 , along with Fisher.
[EX A]: Which dataset do they use to learn embeddings?

[EX Q]: We propose extended middle context, a new context representation for CNNs for relation classification. The contexts are split into three disjoint regions based on the two relation arguments: the left context, the middle context and the right context. Hence, we propose to use two contexts: (1) a combination of the left context, the left entity and the middle context; and (2) a combination of the middle context, the right entity and the right context. The two contexts are processed by two independent convolutional and max-pooling layers. After pooling, the results are concatenated to form the sentence representation.
[EX A]: How do they obtain the new context represetation?

[EX Q]: The dataset from Twitter that we are using in our work, consists of a train set, a validation set and a test set. It was published for the "First workshop on categorizing different types of online harassment languages in social media". The whole dataset is divided into two categories, which are harassment and non-harassment tweets. Moreover, considering the type of the harassment, the tweets are divided into three sub-categories which are indirect harassment, sexual and physical harassment.
[EX A]:
What types of online harassment are studied?