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 focus primarily on the smaller data set of 645 hand-labeled articles provided to task participants, both for training and for validation.  We pre-trained BERT-base on the 600,000 articles without labels by using the same Cloze task BIBREF5 that BERT had originally used for pre-training. 

Output: How long is the dataset?


Input: Consider Input: Participants who were shown the definition were more likely to suggest to ban the tweet. In fact, participants in group one very rarely gave different answers to questions one and two (18 of 500 instances or 3.6%). This suggests that participants in that group aligned their own opinion with the definition.

Output: How did the authors demonstrate that showing a hate speech definition caused annotators to partially align their own opinion with the definition?


Input: Consider Input: The Siamese neural network has two parallel convolutional networks, INLINEFORM0 , that share the same set of weights, INLINEFORM1 , as shown in Figure FIGREF5 (a).


Output: What is the architecture of the siamese neural network?