You will be given a definition of a task first, then some input of the task.
In this task, you will be presented with a context from an academic paper and a question based on the context. You have to classify the questions into "Extractive", "Abstractive", or "Yes-no" questions. Extractive questions can be answered by concatenating extracts taken from a context into a summary while answering abstractive questions involves paraphrasing the context using novel sentences. Yes-no question is a question whose expected answer is one of two choices, one that affirms the question and one that denies the question. Typically, the choices are either yes or no.

We also observe that the best combination seems to consist in training our model on the original out-of-context dataset and testing it on the in-context pairs. In this configuration we reach an F-score (0.72) only slightly lower than the one reported in BIBREF3 (0.74), and we record the highest Pearson correlation, 0.3 (which is still not strong, compared to BIBREF3 's best run, 0.75).
Question: What were the results of the first experiment?
Output:
Abstractive