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.

[Q]: Our main contributions are (1) the publication of Turkish corpus for coarse-grained and fine-grained NER, and TC research, (2) six different versions of corpus according to noise reduction methodology and entity types, (3) an analysis of the corpus and (4) benchmark comparisons for NER and TC tasks against human annotators. 
[A]: Did they experiment with the dataset on some tasks?


[Q]: To tackle this issue we applying a back-translation method BIBREF13, where we translate indirect and physical harassment tweets of the train set from english to german, french and greek. After that, we translate them back to english in order to achieve data augmentation.
[A]: What language(s) is/are represented in the dataset?


[Q]: Detection: In hypernymy detection, the task is to classify whether pairs of words are in a hypernymy relation. Direction: In direction prediction, the task is to identify which term is broader in a given pair of words. Graded Entailment: In graded entailment, the task is to quantify the degree to which a hypernymy relation holds.
[A]:
What hypernymy tasks do they study?