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.

Input: Consider Input: Our work is further connected to the topic of interpretability and transparency of machine learning models BIBREF11, BIBREF35, BIBREF12, for which humans are increasingly involved, for instance for post-hoc evaluations of the model's interpretability. 

Output: How are the interpretability merits of the approach demonstrated?


Input: Consider 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.

Output: Which dataset do they train their models on?


Input: Consider Input: In this paper, we have shown that both human and machine translation can alter superficial patterns in data, which requires reconsidering previous findings in cross-lingual transfer learning.


Output: Does the professional translation or the machine translation introduce the artifacts?