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.

Input: Consider Input: For testing, we also applied the TongueNet on the UBC database BIBREF14 without any training to see the generalization ability of the model.

Output: What previously annotated databases are available?


Input: Consider Input: Given the fact that the research on offensive language detection has to a large extent been focused on the English language, we set out to explore the design of models that can successfully be used for both English and Danish.

Output: What is the challenge for other language except English


Input: Consider Input: Another problem we face is that the BERT model released by Google is trained only on Arabic Wikipedia, which is almost exclusively Modern Standard Arabic (MSA). The shared task dataset contains 5,030 tweets related to different political issues and events in the Middle East taking place between 2011 and 2018. Tweets involve both MSA as well as dialects at various degrees of granularity such as Egyptian, Gulf, and Levantine.


Output: What dialect is used in the Google BERT model and what is used in the task data?