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.

Example Input: The neural machine translation was trained using Nematus. For the NMT system as well as for the PreMT system, we used the default configuration.
Example Output: Which NMT architecture do they use?

Example Input: Due to the high cost of pre-training BERT language model, we directly adopt parameters pre-trained by Google in Chinese general corpus. The named entity recognition is applied on both pathology report texts and query texts.
Example Output: What data is the language model pretrained on?

Example Input: However, no prior work has explored the target of the offensive language, which is important in many scenarios, e.g., when studying hate speech with respect to a specific target.
Example Output:
What are the differences between this dataset and pre-existing ones?