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.

We acquired the data in two rounds of annotation. In the first one, we were looking for original and uncommon sentence change suggestions.
How do they introduce language variation?

Previous attempts to annotate QA-SRL initially involved trained annotators BIBREF4 but later resorted to crowdsourcing BIBREF5 to achieve scalability.
How was the corpus obtained?

Three baseline classification methods: Support Vector Machines (SVM), Adaboost, and Random Forests are adopted to evaluate our extracted features. On each dataset, the employed classifiers are trained with individual feature first, and then with the combination of the two features.

LDA is an unsupervised method; is this paper introducing an unsupervised approach to spam detection?