instruction:
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 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.
answer:
What language(s) is/are represented in the dataset?


question:
The model consists of one layer of LSTM followed by three dense layers. The LSTM layer uses a dropout value of 0.2. 
answer:
Do they use dropout?


question:
This work analyzes the understanding of pretrained language models of factual and commonsense knowledge stored in negated statements. To this end, we introduce the negated LAMA dataset. We construct it by simply inserting negation elements (e.g., “not”) in LAMA cloze statement (e.g., “The theory of relativity was not developed by [MASK].”).
answer:

How did they extend LAMA evaluation framework to focus on negation?