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.

Input: Consider Input: We evaluate performance of our models on the SQUAD BIBREF16 dataset (denoted $\mathcal {S}$ ). We use the same split as that of BIBREF4 , where a random subset of 70,484 instances from $\mathcal {S}\ $ are used for training ( ${\mathcal {S}}^{tr}$ ), 10,570 instances for validation ( ${\mathcal {S}}^{val}$ ), and 11,877 instances for testing ( ${\mathcal {S}}^{te}$ ).

Output: Which datasets are used to train this model?

Input: Consider Input: Figure FIGREF23 shows the proposed ontology, which, in our evaluation procedure, was populated with 3121 events entries from 51 documents.

Output: How is the effectiveness of this pipeline approach evaluated?

Input: Consider Input: This baseline has an F1 of 41.59% and accuracy of 71.22%.
Output: what are their evaluation metrics?