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 Q]: The dataset consists of more than $0.3$ million records and has been made available for future research.
Question: What is the size of the dataset?
[EX A]: $0.3$ million records

[EX Q]: Our training data consists of 2.09M sentence pairs extracted from LDC corpus. To test different approaches on Chinese-to-English translation task, we use NIST 2003(MT03) dataset as the validation set, and NIST 2004(MT04), NIST 2005(MT05), NIST 2006(MT06) datasets as our test sets. For English-to-Chinese translation task, we also use NIST 2003(MT03) dataset as the validation set, and NIST 2008(MT08) will be used as test set.
Question: What dataset did they use?
[EX A]: LDC corpus NIST 2003(MT03) NIST 2004(MT04), NIST 2005(MT05), NIST 2006(MT06) NIST 2008(MT08)

[EX Q]: Although humor is a universal construct, there is a wide variety between what each individual may find humorous. We attempt to focus on a subset of the population where we can quantitatively measure reactions: the popular Reddit r/Jokes thread. This forum is highly popular - with tens of thousands of jokes being posted monthly and over 16 million members. Although larger joke datasets exist, the r/Jokes thread is unparalleled in the amount of rated jokes it contains. To the best of our knowledge there is no comparable source of rated jokes in any other language. These Reddit posts consist of the body of the joke, the punchline, and the number of reactions or upvotes. Although this type of humor may only be most enjoyable to a subset of the population, it is an effective way to measure responses to jokes in a large group setting.
Question: What kind of humor they have evaluated?
[EX A]:
a subset of the population where we can quantitatively measure reactions: the popular Reddit r/Jokes thread These Reddit posts consist of the body of the joke, the punchline, and the number of reactions or upvotes.