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.
--------
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: We evaluate the performance of our proposed method using two criteria: i) rank-correlation BIBREF25 to evaluate visual grounding and ii) accuracy to evaluate question answering. Intuitively, rank-correlation measures the similarity between human and model attention maps under a rank-based metric. A high rank-correlation means that the model is `looking at' image areas that agree to the visual information used by a human to answer the same question. In terms of accuracy of a predicted answer INLINEFORM0 is evaluated by: DISPLAYFORM0



Answer: How do they measure the correlation between manual groundings and model generated ones?


Question: The corpus consists of 53 documents, which contain an average number of 156.1 sentences per document, each with 19.55 tokens on average.

Answer:
How many documents are in the new corpus?