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.

Ex Input:
To simplify the task, we set up a binary classification: candidates who have been liked or shortlisted are considered part of the hirable class and others part of the not hirable class. 
 Question: How is "hirability" defined?

Ex Output:
candidates who have been liked or shortlisted are considered part of the hirable class


Ex Input:
As a first corpus, we compiled INLINEFORM0 that represents a collection of 80 excerpts from scientific works including papers, dissertations, book chapters and technical reports, which we have chosen from the well-known Digital Bibliography & Library Project (DBLP) platform. As a second corpus, we compiled INLINEFORM0 , which represents a collection of 1,645 chat conversations of 550 sex offenders crawled from the Perverted-Justice portal. As a third corpus, we compiled INLINEFORM0 , which is a collection of 200 aggregated postings crawled from the Reddit platform. 
 Question: What size are the corpora?

Ex Output:
80 excerpts from scientific works collection of 1,645 chat conversations collection of 200 aggregated postings


Ex Input:
We calculate the probability of a sentence with a long-short term memory (LSTM, hochreiter1997long) LM, i.e., a special type of RNN LM, which has been trained on a large corpus. We train our LSTM LMs on the English Gigaword corpus BIBREF15 , which consists of news data. 
 Question: what language models do they use?

Ex Output:

LSTM LMs