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.

Following previous work BIBREF13, BIBREF12, BIBREF10, BIBREF17, BIBREF9, BIBREF7, we choose SemCor3.0 as training corpus, which is the largest corpus manually annotated with WordNet sense for WSD.
Is SemCor3.0 reflective of English language data in general?

SIGHAN Bakeoff defines two types of evaluation settings, closed test limits all the data for learning should not be beyond the given training set, while open test does not take this limitation BIBREF21.
What is meant by closed test setting?

As introduced above, the `One Million Post' corpus provides annotation labels for more than 11,000 user comments. Although there is no directly comparable category capturing `offensive language' as defined in the shared task, there are two closely related categories. From the resource, we extract all those comments in which a majority of the annotators agree that they contain either `inappropriate' or `discriminating' content, or none of the aforementioned. We treat the first two cases as examples of `offense' and the latter case as examples of `other'.

What are the near-offensive language categories?