You are given a background paragraph that describes one or more causal or qualitative relationships such as a relationship in economics or a scientific law and a story that makes use of the concepts or the relationship described in the provided paragraph. You are also given a question about the story that requires an understanding of the relationship described in the background paragraph and the story. You need to come up with an answer to the given question; the answer will be a span from either the question or the story. In order to correctly answer the given question, you need to understand the relationship mentioned in the background paragraph and should be able to use it to understand that in the story. Your answer can not consist of any word that is not mentioned in any of these: the background paragraph, the story, or the question. You can directly copy and paste a span from the story or the question while answering the given question.

Example Input: Background Paragraph: Fish mortality is a parameter used in fisheries population dynamics to account for the loss of fish in a fish stock through death. The mortality can be divided into two types:

Natural mortality: the removal of fish from the stock due to causes not associated with fishing. Such causes can include disease, competition, cannibalism, old age, predation, pollution or any other natural factor that causes the death of fish. In fisheries models natural mortality is denoted by (M).[1]
Fishing mortality: the removal of fish from the stock due to fishing activities using any fishing gear.[1] It is denoted by (F) in fisheries models. 
Story: Bob works as a scientist for a large fishing company in Norway. Norway's government has strict regulations on fishing to protect its fish stock. Part of Bob's job is to provide the government with fish mortality data. Today, he has two samples of fish to investigate, sample A and sample B. Bob concluded sample A had natural mortality, but sample B had fishing mortality. 
Question: Would pollution be a casue of death or not a cause of death for sample B?
Example Output: not a cause of death.

Example Input: Background Paragraph: Bernoulli’s law explains how the wings of both airplanes and birds create lift that allows flight (see Figure below ). The shape of the wings causes air to flow more quickly — and air pressure to be lower — above the wings than below them. This allows the wings to lift the plane or bird above the ground against the pull of gravity. A spoiler on a race car, like the one in Figure below , works in the opposite way. Its shape causes air to flow more slowly — and air pressure to be greater — above the spoiler than below it. As a result, air pressure pushes the car downward, giving its wheels better traction on the track. 
Story: Rob is experimenting with how air pressure works. To that end, he has designed two tests. In the first test the air flow works as it would in an airplane wing. He labels it as case A. In the second test the air flow works as it would in a race car spoiler. He labels it as case B. He is surprised to see that air flow behaves differently in different situations. 
Question: Would case A have higher or lower air pressure above it than case B?
Example Output: lower.

Example Input: Background Paragraph: Storing large volumes of data – When storing XML to either file or database, the volume of data a system produces can often exceed reasonable limits, with a number of detriments: the access times go up as more data is read, CPU load goes up as XML data takes more power to process, and storage costs go up. By storing XML data in Fast Infoset format, data volume may be reduced by as much as 80 percent. 
Story: Brett had a busy day storing XML. At 3 PM, he stored 100 Gigabytes to the database. At 4 PM, he stored 200 Gigabytes to the database. At 5 PM, he stored 300 Gigabytes to the database. At 6 PM, he got dinner. At 7 PM, he stored 400 Gigabytes to the database. At 8 PM, he stored 500 Gigabytes to the database. At 9 PM, he went to sleep to finish storing XML in the morning. 
Question: What time did CPU load go up: 4 PM or 6 PM?
Example Output:
4 PM.