In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

Input: Consider Input: Using our methodology, we tagged 10,000 Arabic tweet dataset for offensiveness, where offensive tweets account for roughly 19% of the tweets. Further, we labeled tweets as vulgar or hate speech.
Question: How many tweets are in the dataset?

Output: 10,000 Arabic tweet dataset

Input: Consider Input: To collect a diverse training dataset, we have randomly sampled 1000 posts each from the subreddits politics, business, science, and AskReddit, and 1000 additional posts from the Reddit frontpage.
Question: what are the topics pulled from Reddit?

Output: politics, business, science, and AskReddit, and 1000 additional posts from the Reddit frontpage.

Input: Consider Input: Thus, SIM has many fewer parameters than existing dialogue state tracking models. To compensate for the exclusion of slot-specific parameters, we incorporate better feature representation of user utterance and dialogue states using syntactic information and convolutional neural networks (CNN).
Question: How do they prevent the model complexity increasing with the increased number of slots?
Output: They exclude slot-specific parameters and incorporate better feature representation of user utterance and dialogue states using syntactic information and convolutional neural networks (CNN).