niryuu/sni-each-converted huggingface dataset:
Background Paragraph: Matter, dark matter, and dark energy are distributed homogeneously throughout the Universe over length scales longer than 300 million light-years or so. However, over shorter length-scales, matter tends to clump hierarchically; many atoms are condensed into stars, most stars into galaxies, most galaxies into clusters, superclusters and, finally, large-scale galactic filaments. The observable Universe contains approximately 300 sextillion (3×1023) stars and more than 100 billion (1011) galaxies. Typical galaxies range from dwarfs with as few as ten million (107) stars up to giants with one trillion (1012) stars. Between the larger structures are voids, which are typically 10–150 Mpc (33 million–490 million ly) in diameter. The Milky Way is in the Local Group of galaxies, which in turn is in the Laniakea Supercluster. This supercluster spans over 500 million light-years, while the Local Group spans over 10 million light-years. The Universe also has vast regions of relative emptiness; the largest known void measures 1.8 billion ly (550 Mpc) across. 
Story: Rob is an amateur astronomer. He was looking at the sky with his telescope. First he took a longer length observation. He noted his observation as case A. Then he took a shorter length observation. He noted that observation as case B. He found that it's beneficial to take both observations to get a fuller view of the observable universe.
Output: In which observation matter would clump more hierarchically, case A or case B?
Background Paragraph: Matter, dark matter, and dark energy are distributed homogeneously throughout the Universe over length scales longer than 300 million light-years or so. However, over shorter length-scales, matter tends to clump hierarchically; many atoms are condensed into stars, most stars into galaxies, most galaxies into clusters, superclusters and, finally, large-scale galactic filaments. The observable Universe contains approximately 300 sextillion (3×1023) stars and more than 100 billion (1011) galaxies. Typical galaxies range from dwarfs with as few as ten million (107) stars up to giants with one trillion (1012) stars. Between the larger structures are voids, which are typically 10–150 Mpc (33 million–490 million ly) in diameter. The Milky Way is in the Local Group of galaxies, which in turn is in the Laniakea Supercluster. This supercluster spans over 500 million light-years, while the Local Group spans over 10 million light-years. The Universe also has vast regions of relative emptiness; the largest known void measures 1.8 billion ly (550 Mpc) across. 
Story: Rob is an amateur astronomer. He was looking at the sky with his telescope. First he took a longer length observation. He noted his observation as case A. Then he took a shorter length observation. He noted that observation as case B. He found that it's beneficial to take both observations to get a fuller view of the observable universe.
Output: Which observation would detect stars and galaxies well, case A or case B?
Background Paragraph: Matter, dark matter, and dark energy are distributed homogeneously throughout the Universe over length scales longer than 300 million light-years or so. However, over shorter length-scales, matter tends to clump hierarchically; many atoms are condensed into stars, most stars into galaxies, most galaxies into clusters, superclusters and, finally, large-scale galactic filaments. The observable Universe contains approximately 300 sextillion (3×1023) stars and more than 100 billion (1011) galaxies. Typical galaxies range from dwarfs with as few as ten million (107) stars up to giants with one trillion (1012) stars. Between the larger structures are voids, which are typically 10–150 Mpc (33 million–490 million ly) in diameter. The Milky Way is in the Local Group of galaxies, which in turn is in the Laniakea Supercluster. This supercluster spans over 500 million light-years, while the Local Group spans over 10 million light-years. The Universe also has vast regions of relative emptiness; the largest known void measures 1.8 billion ly (550 Mpc) across. 
Story: Rob is an amateur astronomer. He was looking at the sky with his telescope. First he took a longer length observation. He noted his observation as case A. Then he took a shorter length observation. He noted that observation as case B. He found that it's beneficial to take both observations to get a fuller view of the observable universe.
Output: Which observation would not detect stars and galaxies well, case A or case B?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: If Ken doen't like any yeast around him, which yeast  he should not worry about, yeas A or yeast B?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: If Ken doesn't like any yeast around him, which yeast should he be careful about, yeas A or yeast B?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: If Ken wants a dough sample to expand, which yeast should he use, yeast A or yeast B?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: If Ken wants to ferment alcohol, which yeast should he use, yeast A or yeast B?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: Which yeast sample is not a good match as a leavening  agent, yeast A or yeast B?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: Which yeast sample would be used as a leavening agent,  yeast A or yeast B?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: Would yeast A be used as a leavening agent or not be used as a leavening agent?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: Would yeast A more likely to present or absent on human body?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: Would yeast B be used as a leavening agent or not be used as a leavening agent?
Background Paragraph: Baker's yeast is the common name for the strains of yeast commonly used in baking bread and bakery products, serving as a leavening agent which causes the bread to rise (expand and become lighter and softer) by converting the fermentable sugars present in the dough into carbon dioxide and ethanol. Baker's yeast is of the species Saccharomyces cerevisiae,[1] and is the same species (but a different strain) as the kind commonly used in alcoholic fermentation, which is called brewer's yeast.[2] Baker's yeast is also a single-cell microorganism found on and around the human body. 
Story: Ken is a microbiologist. He got two samples of yeasts, yeast A and yeast B, from two different businesses. Yeast A is used in a bakery, and yeast B is used in a brewery. He has to decide the characteristics of each 
yeast sample for further study.
Interestingly, despite all his curiosity, Ken doesn't like any yeast to be around him.
Output: Would yeast B more likely to present or absent on human body?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Which country would attract businesses requiring higher labor supply, Germany or France?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Which country would have higher labor supply in response to their taxation?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Which country would have lower labor supply in response to their taxation?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Which country would not attract businesses requiring higher labor supply, Germany or France?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Which country would see declining government revenue, Germany or France?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Which country would see increasing government revenue, Germany or France?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Would France have lower or higher labor supply?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Would France's government revenue increase or decrease as a result of their tax policy?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Would Germany have lower or higher labor supply?
Background Paragraph: The Laffer curve depicts the amount of government revenue as a function of the rate of taxation. It shows that for a tax rate above a certain critical rate, government revenue starts decreasing as the tax rate rises, as a consequence of a decline in labour supply. This theory supports that, if the tax rate is above that critical point, a decrease in the tax rate should imply a rise in labour supply that in turn would lead to an increase in government revenue. 
Story: After the second world war Germany and France took two different policies in respect to taxation. After the war Germany, then West Germany, has mostly elected pro-capitalist governments. As a consequence, Germany implemented tax rate below the critical rate. But France took the other way. Their mostly pro-socialist governments implemented tax rate above the critical rate. As a result, businesses had to make informed decisions while doing business in these countries.
Output: Would Germany's government revenue increase or decrease as a result of their tax policy?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Friday or Saturday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Monday or Friday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Monday or Saturday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Sunday or Friday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Sunday or Saturday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Thursday or Friday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Thursday or Saturday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Tuesday or Friday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Tuesday or Saturday?
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 16 last week. On Sunday, there were 1255 motorcyclists. On Monday, there were 2255 motorcyclists. On Tuesday, there were 3251 motorcyclists. On Wednesday, there were 4251 motorcyclists. On Thursday, there were 5251 motorcyclists. On Friday, there were 6251 motorcyclists. On Saturday, there were 7251 motorcyclists.
Output: What day had a lower crash rate per cyclist: Wednesday or Saturday?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country had a higher productivity?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country had a higher satisfaction rate?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country had a lower productivity?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country had a lower satisfaction rate?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country had higher taxes?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country had less money to invest?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country had lower taxes?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country had more money to invest?
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 lands applied different economical measures over the last decade. Greenland increased productivity so they became wealthy and prosperous. Iceland chose to increase taxation and expand its government, they had little money to invest.
Output: Which country was less optimistic?