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.

When evaluating classifiers it is common to use accuracy, precision and recall as well as Hamming loss.  It has been shown that when calculating precision and recall on multi-label classifiers, it can be advantageous to use micro averaged precision and recall BIBREF6 . The formulas for micro averaged precision are expressed as DISPLAYFORM0 DISPLAYFORM1
what evaluation metrics are discussed?

However, we see that IR methods perform better than the best neural models. We do not find enough evidence to reject the null hypothesis regarding what context from the cited document should be used.
Which baseline performs best?

The annotator carried out all annotation.

How many annotators tagged each tweet?