In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

[EX Q]: We address this issue by We address this issue by examining and reviewing publicly available datasets for abusive content detection, which we provide access to on a new dedicated website, hatespeechdata.com. We address this issue by examining and reviewing publicly available datasets for abusive content detection, which we provide access to on a new dedicated website, hatespeechdata.com.
Question: What is open website for cataloguing abusive language data?
[EX A]: hatespeechdata.com

[EX Q]: In particular, we aggregate documents from the CommonCrawl dataset that has the most overlapping n-grams with the questions. We name this dataset STORIES since most of the constituent documents take the form of a story with long chain of coherent events. Figure 5 -left and middle show that STORIES always yield the highest accuracy for both types of input processing.
Question: Which of their training domains improves performance the most?
[EX A]: documents from the CommonCrawl dataset that has the most overlapping n-grams with the question

[EX Q]: For the English version, we performed both a thorough manual analysis and automatic evaluation across three commonly used TS datasets from two different domains For the English version, we performed both a thorough manual analysis and automatic evaluation across three commonly used TS datasets from two different domains The evaluation of the German version is in progress.
Question: What are the corpora used for the task?
[EX A]:
For the English version, we performed both a thorough manual analysis and automatic evaluation across three commonly used TS datasets from two different domains The evaluation of the German version is in progress.