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.

Recurrent Neural Network (RNN) Language Models
are trained to output the probability distribution of the upcoming word given a context, without explicitly representing the structure of the context BIBREF9, BIBREF10. ActionLSTM
models the linearized bracketed tree structure of a sentence by learning to predict the next action required to construct a phrase-structure parse BIBREF16. Generative Recurrent Neural Network Grammars (RNNG)
jointly model the word sequence as well as the underlying syntactic structure BIBREF18.
Question: What are the baseline models?
Recurrent Neural Network (RNN) ActionLSTM Generative Recurrent Neural Network Grammars (RNNG)

We used dataset, HEOT obtained from one of the past studies done by Mathur et al. where they annotated a set of cleaned tweets obtained from twitter for the conversations happening in Indian subcontinent. A labelled dataset for a corresponding english tweets were also obtained from a study conducted by Davidson et al.
Question: How is the dataset collected?
A labelled dataset for a corresponding english tweets were also obtained from a study conducted by Davidson et al HEOT obtained from one of the past studies done by Mathur et al

Table TABREF14 presents the distribution of the tweets by country before and after the filtering process. A large portion of the samples is from India because the MeToo movement has peaked towards the end of 2018 in India. There are very few samples from Russia likely because of content moderation and regulations on social media usage in the country.
Question: Do the tweets come from a specific region?
No