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: 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.

A: Is SemCor3.0 reflective of English language data in general?
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Q: As we mention in the Section 2, CAEVO is the current state-of-the-art system for feature-based temporal event relation extraction BIBREF10 . It's widely used as the baseline for evaluating TB-Dense data. We adopt it as our baseline for evaluating CaTeRS and RED datasets.

A: What were the traditional linguistic feature-based models?
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Q: We validate our approach on the Wikipedia toxic comments dataset BIBREF18 .

A:
Which datasets do they use?
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