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.

[EX Q]: According the distribution of the sentiment score, the sentiment on Tesla is slightly skewed towards positive during the testing period.
[EX A]: Do the authors give any examples of major events which draw the public's attention and the impact they have on stock price?

[EX 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.
[EX A]: What were the traditional linguistic feature-based models?

[EX Q]: Experiments ::: Baselines
To comprehensively evaluate our AGDT, we compare the AGDT with several competitive models.
[EX A]:
Is the model evaluated against other Aspect-Based models?