niryuu/sni-each-converted huggingface dataset:
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: Robin had a busy day storing XML. At 5 AM, he stored 220 Gigabytes to the database. At 6 AM, he stored 330 Gigabytes to the database. At 7 AM, he stored 440 Gigabytes to the database. At 8 AM, he got breakfast. At 9 AM, he stored 550 Gigabytes to the database. At 10 AM, he stored 660 Gigabytes to the database. At 11 AM, she went to sleep to finish storing XML later that day.
Output: What time did storage costs go up:  6 AM or 11 AM?
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: Robin had a busy day storing XML. At 5 AM, he stored 220 Gigabytes to the database. At 6 AM, he stored 330 Gigabytes to the database. At 7 AM, he stored 440 Gigabytes to the database. At 8 AM, he got breakfast. At 9 AM, he stored 550 Gigabytes to the database. At 10 AM, he stored 660 Gigabytes to the database. At 11 AM, she went to sleep to finish storing XML later that day.
Output: What time did storage costs go up:  6 AM or 8 AM?
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: Robin had a busy day storing XML. At 5 AM, he stored 220 Gigabytes to the database. At 6 AM, he stored 330 Gigabytes to the database. At 7 AM, he stored 440 Gigabytes to the database. At 8 AM, he got breakfast. At 9 AM, he stored 550 Gigabytes to the database. At 10 AM, he stored 660 Gigabytes to the database. At 11 AM, she went to sleep to finish storing XML later that day.
Output: What time did storage costs go up:  7 AM or 11 AM?
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: Robin had a busy day storing XML. At 5 AM, he stored 220 Gigabytes to the database. At 6 AM, he stored 330 Gigabytes to the database. At 7 AM, he stored 440 Gigabytes to the database. At 8 AM, he got breakfast. At 9 AM, he stored 550 Gigabytes to the database. At 10 AM, he stored 660 Gigabytes to the database. At 11 AM, she went to sleep to finish storing XML later that day.
Output: What time did storage costs go up:  7 AM or 8 AM?
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: Robin had a busy day storing XML. At 5 AM, he stored 220 Gigabytes to the database. At 6 AM, he stored 330 Gigabytes to the database. At 7 AM, he stored 440 Gigabytes to the database. At 8 AM, he got breakfast. At 9 AM, he stored 550 Gigabytes to the database. At 10 AM, he stored 660 Gigabytes to the database. At 11 AM, she went to sleep to finish storing XML later that day.
Output: What time did storage costs go up:  9 AM or 11 AM?
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: Robin had a busy day storing XML. At 5 AM, he stored 220 Gigabytes to the database. At 6 AM, he stored 330 Gigabytes to the database. At 7 AM, he stored 440 Gigabytes to the database. At 8 AM, he got breakfast. At 9 AM, he stored 550 Gigabytes to the database. At 10 AM, he stored 660 Gigabytes to the database. At 11 AM, she went to sleep to finish storing XML later that day.
Output: What time did storage costs go up:  9 AM or 8 AM?
Background Paragraph: Chemical reactions follow the laws of thermodynamics. The First Law of Thermodynamics states that energy can be changed from one form to another, but it cannot be created or destroyed. This law is also known as the Law of Conservation of Energy. The Second Law of Thermodynamics states the energy available after a chemical reaction is always less than that at the beginning of a reaction. This is also commonly referred to as entropy. Entropy can be described as the degree of disorder in a system . That is, as energy is transferred from one form to another, some of the energy is lost as heat, and the amount of available energy decreases. As the energy decreases, the disorder in the system increases, and, by definition, the entropy increases. Ice melting provides an example in which entropy increases. Entropy essentially is a measure of the tendency of a process, such as a chemical reaction, to proceed in a particular direction. 
Story: Marcus is in a lab working on an experiment. He combines two chemicals to see if they react and the solution starts to boil. He notices that the air above the chemicals reacting has greatly increased in heat.
Output: Given the heat rising off of the solution, has the disorder of the system increased or decreased?
Background Paragraph: Chemical reactions follow the laws of thermodynamics. The First Law of Thermodynamics states that energy can be changed from one form to another, but it cannot be created or destroyed. This law is also known as the Law of Conservation of Energy. The Second Law of Thermodynamics states the energy available after a chemical reaction is always less than that at the beginning of a reaction. This is also commonly referred to as entropy. Entropy can be described as the degree of disorder in a system . That is, as energy is transferred from one form to another, some of the energy is lost as heat, and the amount of available energy decreases. As the energy decreases, the disorder in the system increases, and, by definition, the entropy increases. Ice melting provides an example in which entropy increases. Entropy essentially is a measure of the tendency of a process, such as a chemical reaction, to proceed in a particular direction. 
Story: Marcus is in a lab working on an experiment. He combines two chemicals to see if they react and the solution starts to boil. He notices that the air above the chemicals reacting has greatly increased in heat.
Output: Will the boiling solution Marcus made have more or less energy when it finishes reacting?
Background Paragraph: Chemical reactions follow the laws of thermodynamics. The First Law of Thermodynamics states that energy can be changed from one form to another, but it cannot be created or destroyed. This law is also known as the Law of Conservation of Energy. The Second Law of Thermodynamics states the energy available after a chemical reaction is always less than that at the beginning of a reaction. This is also commonly referred to as entropy. Entropy can be described as the degree of disorder in a system . That is, as energy is transferred from one form to another, some of the energy is lost as heat, and the amount of available energy decreases. As the energy decreases, the disorder in the system increases, and, by definition, the entropy increases. Ice melting provides an example in which entropy increases. Entropy essentially is a measure of the tendency of a process, such as a chemical reaction, to proceed in a particular direction. 
Story: Marcus is in a lab working on an experiment. He combines two chemicals to see if they react and the solution starts to boil. He notices that the air above the chemicals reacting has greatly increased in heat.
Output: Will the disorder of a system increase or decrease as entropy increases?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Friday or Monday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Friday or Sunday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Saturday or Monday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Sunday or Monday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Thursday or Monday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Thursday or Sunday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Tuesday or Monday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Tuesday or Sunday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Wednesday or Monday?
Background Paragraph: Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases. 
Story: There were a lot of motorcycles on Interstate 10 last week. On Tuesday, there were 3500 motorcyclists. On Wednesday, there were 4500 motorcyclists. On Thursday, there were 5500 motorcyclists. On Friday, there were 6500 motorcyclists. On Saturday, there were 7500 motorcyclists. On Sunday, there were 8500 motorcyclists. On Monday, there were 9500 motorcyclists.
Output: What day had a lower crash rate per cyclist: Wednesday or Sunday?
Background Paragraph: Enzymes increase the rate of chemical reactions by reducing the amount of activation energy needed for reactants to start reacting. One way this can happen is modeled in the Figure below . Enzymes aren’t changed or used up in the reactions they catalyze, so they can be used to speed up the same reaction over and over again. Each enzyme is highly specific for the particular reaction is catalyzes, so enzymes are very effective. A reaction that would take many years to occur without its enzyme might occur in a split second with the enzyme. Enzymes are also very efficient, so waste products rarely form. 
Story: Two scientists, Cathy and Mark, are working on a  new project. They want to make a new polymer using two chemicals. Mark mixes the two chemicals together on the first day and after a week of waiting he has managed to create a new polymer. While he is happy about the result he feels a week is way to long. Cathy has an idea. She decides to try adding an enzyme to the chemical mixture, The mixture only takes seconds to form the new polymer and the enzyme she used is in tact floating on top of the now completed polymer. She decides to test even further and uses the left over enzyme on another batch of chemicals. The reaction occurs in seconds again and the same amount of enzyme is left floating on top of the polymer for her to use again in the next batch.
Output: Will using the enzyme in the chemical mixture increase or decrease the speed of the reaction?
Background Paragraph: Flywheel energy storage (FES) works by accelerating a rotor (flywheel) to a very high speed, holding energy as rotational energy. When energy is extracted, the flywheel's rotational speed declines as a consequence of conservation of energy; adding energy correspondingly results in an increase in the speed of the flywheel.

Most FES systems use electricity to accelerate and decelerate the flywheel, but devices that directly use mechanical energy are under consideration. 
Story: Ben works with a flywheel, and has been instructed at various times to change the speeds based on certain conditions. He operates a device that gives or limits the flywheels energy by turning a crank left to give more energy, or right to decrease energy.
Output: Which way should Ben turn the crank to decrease the flywheel speed?
Background Paragraph: Flywheel energy storage (FES) works by accelerating a rotor (flywheel) to a very high speed, holding energy as rotational energy. When energy is extracted, the flywheel's rotational speed declines as a consequence of conservation of energy; adding energy correspondingly results in an increase in the speed of the flywheel.

Most FES systems use electricity to accelerate and decelerate the flywheel, but devices that directly use mechanical energy are under consideration. 
Story: Ben works with a flywheel, and has been instructed at various times to change the speeds based on certain conditions. He operates a device that gives or limits the flywheels energy by turning a crank left to give more energy, or right to decrease energy.
Output: Which way should Ben turn the crank to increase the flywheel speed?
Background Paragraph: Flywheel energy storage (FES) works by accelerating a rotor (flywheel) to a very high speed, holding energy as rotational energy. When energy is extracted, the flywheel's rotational speed declines as a consequence of conservation of energy; adding energy correspondingly results in an increase in the speed of the flywheel.

Most FES systems use electricity to accelerate and decelerate the flywheel, but devices that directly use mechanical energy are under consideration. 
Story: Ben works with a flywheel, and has been instructed at various times to change the speeds based on certain conditions. He operates a device that gives or limits the flywheels energy by turning a crank left to give more energy, or right to decrease energy.
Output: Will the flywheel go faster or slower if the crank is turned to the left?
Background Paragraph: Flywheel energy storage (FES) works by accelerating a rotor (flywheel) to a very high speed, holding energy as rotational energy. When energy is extracted, the flywheel's rotational speed declines as a consequence of conservation of energy; adding energy correspondingly results in an increase in the speed of the flywheel.

Most FES systems use electricity to accelerate and decelerate the flywheel, but devices that directly use mechanical energy are under consideration. 
Story: Ben works with a flywheel, and has been instructed at various times to change the speeds based on certain conditions. He operates a device that gives or limits the flywheels energy by turning a crank left to give more energy, or right to decrease energy.
Output: Will the flywheel go faster or slower if the crank is turned to the right?
Background Paragraph: Wind causes the generation of sound. The movement of air causes movements of parts of natural objects, such as leaves or grass. These objects will produce sound if they touch each other. Even a soft wind will cause a low level of environmental noise. If the wind is blowing harder, it may produce howling sounds of varying frequencies. This may be caused by the wind blowing over cavities, or by vortices created in the air downstream of an object. Especially on high buildings, many structural parts may be a cause of annoying noise at certain wind conditions. Examples of these parts are balconies, ventilation openings, roof openings or cables. 
Story: George lives in a rural area and has a sort of barren forest behind his house. Sometimes, especially when it is storming spooky sounds can be heard that scare George and he has no idea what they are.
Output: Given George can hear a lot of noise one night, has the strength of the wind likely increased or decreased?
Background Paragraph: Wind causes the generation of sound. The movement of air causes movements of parts of natural objects, such as leaves or grass. These objects will produce sound if they touch each other. Even a soft wind will cause a low level of environmental noise. If the wind is blowing harder, it may produce howling sounds of varying frequencies. This may be caused by the wind blowing over cavities, or by vortices created in the air downstream of an object. Especially on high buildings, many structural parts may be a cause of annoying noise at certain wind conditions. Examples of these parts are balconies, ventilation openings, roof openings or cables. 
Story: George lives in a rural area and has a sort of barren forest behind his house. Sometimes, especially when it is storming spooky sounds can be heard that scare George and he has no idea what they are.
Output: When it is storming, is George more or less likely to hear howling noises?
Background Paragraph: Wind causes the generation of sound. The movement of air causes movements of parts of natural objects, such as leaves or grass. These objects will produce sound if they touch each other. Even a soft wind will cause a low level of environmental noise. If the wind is blowing harder, it may produce howling sounds of varying frequencies. This may be caused by the wind blowing over cavities, or by vortices created in the air downstream of an object. Especially on high buildings, many structural parts may be a cause of annoying noise at certain wind conditions. Examples of these parts are balconies, ventilation openings, roof openings or cables. 
Story: George lives in a rural area and has a sort of barren forest behind his house. Sometimes, especially when it is storming spooky sounds can be heard that scare George and he has no idea what they are.
Output: Will a soft wind likely cause rustling noises or howling noises?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country experienced financial dissatisfaction after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country experienced financial satisfaction after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country experienced less stagflation after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country experienced more stagflation after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country had a higher life satisfaction index after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country had a lower life satisfaction index after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country had greater optimism after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country had lesser optimism after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country was less happy after 10 years?
Background Paragraph: Using longitudinal data from over 100 countries, Diener and his colleagues showed that rich countries are in general happier than poor countries (Diener, Tay, & Oishi, 2013).[17] Also, life satisfaction for most countries goes up as they become wealthier over time. Diener identified three factors that influence the relationship between income and SWB. Namely, rising income most likely results in higher SWB when it leads to greater optimism, financial satisfaction and household material prosperity among citizens. Furthermore, Diener and his colleagues investigated the relationship between income and different elements of SWB. They illustrated that income has stronger influence on people’s evaluation of their lives than the positive or negative emotions they experience over time (Diener, Kahneman, Tov, & Arora, 2010).[18] The study points to the necessity to evaluate different elements of SWB separately instead of treating happiness as a single entity. 
Story: Two neighboring countries implemented different sets of economic reforms. The reforms took over a decade to implement, but the effects were not similar at all. Redvania was more prosperous and it became much richer, while Blueland stagflated and the inhabitants were not pleased with the outcome.
Output: Which country was much happier after 10 years?
Background Paragraph: Type 2 diabetes is much more common than type 1 diabetes. Type 2 diabetes occurs when body cells no longer respond normally to insulin. The pancreas still makes insulin, but the cells of the body can’t use it. Being overweight and having high blood pressure increase the chances of developing type 2 diabetes. This type of diabetes usually develops in adulthood. However, it is becoming more common in teens and children because more young people are overweight now than ever before. 
Story: Mark and his sister Elaine recently had a visit with their doctors to see how their health was doing. Mark has not been able to manage his weight for the last several years, and the doctor told him he now officially has type 2 diabetes. Elaine has paid close attention to her health, and the doctor told her she does not have type 2 diabetes and her health is normal.
Output: Whose body cells no longer respond normally to insulin?
Background Paragraph: Type 2 diabetes is much more common than type 1 diabetes. Type 2 diabetes occurs when body cells no longer respond normally to insulin. The pancreas still makes insulin, but the cells of the body can’t use it. Being overweight and having high blood pressure increase the chances of developing type 2 diabetes. This type of diabetes usually develops in adulthood. However, it is becoming more common in teens and children because more young people are overweight now than ever before. 
Story: Mark and his sister Elaine recently had a visit with their doctors to see how their health was doing. Mark has not been able to manage his weight for the last several years, and the doctor told him he now officially has type 2 diabetes. Elaine has paid close attention to her health, and the doctor told her she does not have type 2 diabetes and her health is normal.
Output: Whose body cells still respond normally to insulin?
Background Paragraph: The Figure below shows decibel levels of several different sounds. As decibel levels get higher, sound waves have greater intensity and sounds are louder. For every 10-decibel increase in the intensity of sound, loudness is 10 times greater. Therefore, a 30-decibel “quiet” room is 10 times louder than a 20-decibel whisper, and a 40-decibel light rainfall is 100 times louder than the whisper. High-decibel sounds are dangerous. They can damage the ears and cause loss of hearing. 
Story: James is attending a concert. When he first walks in the concert hall there aren't that many people there and it is relatively quiet. As the room fills up it starts to get a bit louder. And when the concert starts its so loud that it is almost painful for him as he is sitting near the speakers.
Output: Given that during the concert the decibel levels were high enough to be painful to James, will further increasing them make them safer or harmful?
Background Paragraph: The Figure below shows decibel levels of several different sounds. As decibel levels get higher, sound waves have greater intensity and sounds are louder. For every 10-decibel increase in the intensity of sound, loudness is 10 times greater. Therefore, a 30-decibel “quiet” room is 10 times louder than a 20-decibel whisper, and a 40-decibel light rainfall is 100 times louder than the whisper. High-decibel sounds are dangerous. They can damage the ears and cause loss of hearing. 
Story: James is attending a concert. When he first walks in the concert hall there aren't that many people there and it is relatively quiet. As the room fills up it starts to get a bit louder. And when the concert starts its so loud that it is almost painful for him as he is sitting near the speakers.
Output: Given the concert is now over and everyone is leaving, will the decibel levels increase or decrease?
Background Paragraph: The Figure below shows decibel levels of several different sounds. As decibel levels get higher, sound waves have greater intensity and sounds are louder. For every 10-decibel increase in the intensity of sound, loudness is 10 times greater. Therefore, a 30-decibel “quiet” room is 10 times louder than a 20-decibel whisper, and a 40-decibel light rainfall is 100 times louder than the whisper. High-decibel sounds are dangerous. They can damage the ears and cause loss of hearing. 
Story: James is attending a concert. When he first walks in the concert hall there aren't that many people there and it is relatively quiet. As the room fills up it starts to get a bit louder. And when the concert starts its so loud that it is almost painful for him as he is sitting near the speakers.
Output: Will the decibel levels have increased or decreased in the time since James arrived at the concert to when the show started?
Background Paragraph: Figure B above shows an important relationship between the wavelength and frequency of a wave. The top wave clearly has a shorter wavelength than the second wave. However, if you picture yourself at a stationary point watching these waves pass by, more waves of the first kind would pass by in a given amount of time. Thus the frequency of the first waves is greater than that of the second waves. Wavelength and frequency are therefore inversely related. As the wavelength of a wave increases, its frequency decreases. The equation that relates the two is. 
Story: Jenna is studying waves and their related characteristics. Today, is she analyzing two different waves, wave D and wave M. Wave D has a very long wavelength, and wave M has a short wavelength. Jenna is making note of this so she can perhaps use this information in future studies.
Output: Which wave has a greater frequency?
Background Paragraph: Figure B above shows an important relationship between the wavelength and frequency of a wave. The top wave clearly has a shorter wavelength than the second wave. However, if you picture yourself at a stationary point watching these waves pass by, more waves of the first kind would pass by in a given amount of time. Thus the frequency of the first waves is greater than that of the second waves. Wavelength and frequency are therefore inversely related. As the wavelength of a wave increases, its frequency decreases. The equation that relates the two is. 
Story: Jenna is studying waves and their related characteristics. Today, is she analyzing two different waves, wave D and wave M. Wave D has a very long wavelength, and wave M has a short wavelength. Jenna is making note of this so she can perhaps use this information in future studies.
Output: Which wave has a lesser frequency?
Background Paragraph: Shown in the Figure below is a cylinder of gas on the left that is at room temperature (300 K). On the right, the cylinder has been heated until the Kelvin temperature has doubled to 600 K. The kinetic energy of the gas molecules increases, so collisions with the walls of the container are now more forceful than they were before. As a result, the pressure of the gas doubles. Decreasing the temperature would have the opposite effect, and the pressure of an enclosed gas would decrease. 
Story: In a laboratory, Marcus is working with two identical containers of the same amount of gas inside them. For his next experiment, he needs these containers to be different temperatures. He takes container X and puts it in the refrigerator, and he leaves container Y out on the table. One hour later, he comes back and takes container X out of the refrigerator so he can now begin his experiment.
Output: Is the pressure in container X higher or lower than container Y?