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 Input:
We used the relation classification dataset of the SemEval 2010 task 8 BIBREF8 . It consists of sentences which have been manually labeled with 19 relations (9 directed relations and one artificial class Other). 8,000 sentences have been distributed as training set and 2,717 sentences served as test set.

Ex Output:
Which dataset do they train their models on?


Ex Input:
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 Output:
How do they obtain the new context represetation?


Ex Input:
In this work, we develop a technique to rapidly transfer an existing pre-trained model from English to other languages in an energy efficient way BIBREF8. 

Ex Output:

How much training data from the non-English language is used by the system?


