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.
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Question: To find a large amount of hate speech on the refugee crisis, we used 10 hashtags that can be used in an insulting or offensive way.

Answer: How were potentially hateful messages identified?


Question: Yet, it is possible that the precise interpretability scores that are measured here are biased by the dataset used. However, it should be noted that the change in the interpretability scores for different word coverages might be effected by non-ideal subsampling of category words. Although our word sampling method, based on words' distances to category centers, is expected to generate categories that are represented better compared to random sampling of category words, category representations might be suboptimal compared to human designed categories.

Answer: What are the weaknesses of their proposed interpretability quantification method?


Question: We map each relation type $R(x,y)$ to at least one parametrized natural-language question $q_x$ whose answer is $y$ .

Answer:
How is the input triple translated to a slot-filling task?