Example D (Passage from Wikipedia)
Passage	For 4,000 years China has been a nation of farmers. By the time the People's Republic of China was established in 1949, virtually all arable land was under cultivation; irrigation and drainage systems constructed centuries earlier and intensive farming practices already produced relatively high yields. But little prime virgin land was available to support population growth and economic development. However, after a decline in production as a result of the Great Leap Forward (1958-60), agricultural reforms implemented in the 1980s increased yields and promised even greater future production from existing cultivated land.
Dialogue	[Teacher bot]: China has been a nation of farmers for 4,000 years! [Student bot]:Wow, that's a long time. What do they grow? [Teacher bot]: They grow a variety of crops, including chicken, fish, fruits, and vegetables. [Student bot]: That sounds like a lot of food. What else can you tell me about China? [Teacher bot]: Well, by the time the People's Republic of China was established in 1949, virtually all arable land was under cultivation.
Example E (Passage from CNN-DailyMail)
Passage	Everywhere you look there are two-wheeled drivers waiting ominously for passengers to hop on board. They're the backbone of public transport in Uganda and the fastest way to get around the capital city, Kampala. The boda boda motorbike taxi is a staple used by all sectors of society. Traditionally, the usual way of catching a ride was to venture into any street corner packed with tens of boda bodes or simply waiting for one to pass by. But now, a new local startup are bringing this classic mode of transport into the technological age by providing the ability to hail a boda boda at the click of a smartphone. "Bodas are the main thing getting people from A to B," says Alastair Sussock, co-founder of SafeBoda ...
Dialogue	[Teacher bot]: Ugandan start-up SafeBoda are bringing this classic mode of transport into the technological age by providing the ability to hail a boda boda at the click of a smartphone. [Student bot]: I've never heard of them. What are they? [Teacher bot]: They are the backbone of public transport in Uganda and the fastest way to get around the capital city, Kampala. [Student bot]: That's really cool. How long have they been around? [Teacher bot]: Well they have been around for a long time. Traditionally, the usual way of catching a ride was to venture into any street corner packed with tens of boda bodes or simply waiting for one to pass by.
Example F (Passage from Paper Abstracts)
Passage	Existing open-domain question answering (QA) models are not suitable for real-time usage because they need to process several long documents on-demand for every input query, which is computationally prohibitive. In this paper, we introduce query-agnostic indexable representations of document phrases that can drastically speed up open-domain QA. In particular, our dense-sparse phrase encoding effectively captures syntactic, semantic, and lexical information of the phrases and eliminates the pipeline filtering of context documents. Leveraging strategies for optimizing training and inference time, our model can be trained and deployed even in a single 4-GPU server. Moreover, by representing phrases as pointers to their start and end tokens, our model indexes phrases in the entire English Wikipedia (up to 60 billion phrases) using under 2TB. Our experiments on SQuAD-Open show that our model is on par with or more accurate than previous models with 6000x reduced computational cost, which translates into at least 68x faster end-to-end inference benchmark on CPUs ...
Dialogue	[Teacher bot]: We introduce query-agnostic indexable representations of document phrases that can drastically speed up open-domain QA. [Student bot]: What is QA? [Teacher bot]: It is a process where our dense-sparse phrase encoding effectively captures syntactic, semantic, and lexical information of the phrases and eliminates the pipeline filtering of context documents. [Student bot]: What are the basic concepts of QA? [Teacher bot]: Well the basic concepts are that we represent phrases as pointers to their start and end tokens, our model indexes phrases in the entire English Wikipedia (up to 60 billion phrases) using under 2TB.