Questõesde UECE sobre Análise sintática | Syntax Parsing

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Foram encontradas 105 questões
fc57585f-b7
UECE 2012 - Inglês - Análise sintática | Syntax Parsing

In questions, sentences from the text may have been modified/adapted to fit certain grammatical structures.


The sentences “We have had several male couples and lesbian couples come to our program from our competitors’ program because they didn’t feel comfortable there,” and “what you’ve become a master in will not keep you valuable throughout the whole of your career” contain, respectively, a/an

TEXT


The need to constantly adapt is the new reality for many workers, well beyond the information technology business. Car mechanics, librarians, doctors, Hollywood special effects designers — virtually everyone whose job is touched by computing — are being forced to find new, more efficient ways to learn as retooling becomes increasingly important not just to change careers, but simply to stay competitive on their chosen path.

Going back to school for months or years is not realistic for many workers, who are often left to figure out for themselves what new skills will make them more valuable, or just keep them from obsolescence. In their quest to occupy a useful niche, they are turning to bite-size instructional videos, peer-to-peer forums and virtual college courses.

Lynda Gratton, a professor of management practice at the London Business School, has coined a term for this necessity: “serial mastery.”

“You can’t expect that what you’ve become a master in will keep you valuable throughout the whole of your career, and you want to add to that the fact that most people are now going to be working into their 70s,” she said, adding that workers must try to choose specialties that cannot be outsourced or automated. “Being a generalist is, in my view, very unwise. Your major competitor is Wikipedia or Google.”

Businesses have responded by pouring more money into training, even in the current economic doldrums, according to several measures. They have experimented by paying employees to share their expertise in internal social networks, creating video games that teach and, human resources consultants say, enticing employees with tuition help even if they leave the company.

Individuals have also shouldered a lot of responsibility for their own upgrades. Lynda.com, which charges $25 a month for access to training videos on topics like the latest version of Photoshop, says its base of individual customers has been growing 42 percent a year since 2008. Online universities like Udacity and Coursera are on pace to double in size in a year, according to Josh Bersin of Bersin & Associates, a consulting firm that specializes in learning and talent management. The number of doctors participating in continuing education programs has more than doubled in the last decade, with the vast majority of the growth stemming from the increased popularity of Internet-based activities, according to the Accreditation Council for Continuing Medical Education in Chicago.

The struggle is not just to keep up, but to anticipate a future of rapid change. When the AshevilleBuncombe Technical Community College in North Carolina wanted to start a program for developing smartphone and tablet apps, the faculty had to consider the name carefully. “We had this title Mobile Applications, and then we realized that it may not be apps in two years, it may be something else,” said Pamela Silvers, the chairwoman of the business computer technologies department. “So we changed it to Mobile Development.”

As the metadata and digital archivist at Emory University, Elizabeth Russey Roke, 35, has had to keep up with evolving standards that help different databases share information, learn how to archive “born digital” materials, and use computers to bring literary and social connections among different collections to life. The bulk of her learning has been on the job, supplemented by the occasional course or videos on Lynda.com.

“For me, it’s easier to learn something in the classroom than it is on my own,” she said. “But I can’t exactly afford another three years of library school.”

Rapid change is a challenge for traditional universities; textbooks and even journals often lag too far behind the curve to be of help, said Kunal Mehta, a Ph.D. student in bioengineering at Stanford University. His field is so new, and changing so rapidly, he said, that there is little consensus on established practices or necessary skills. “It’s more difficult to know what we should learn,” he said. “We have advisers that we work with, but a lot of times they don’t know any better than us what’s going to happen in the future.” 

Instead, Mr. Mehta, 26, spends a lot of time comparing notes with others in his field, just as many professionals turn to their peers to help them stay current. The International Automotive Technicians Network, where mechanics pay $15 a month to trade tips on repairs, has more than 75,000 active users today, up from 48,000 in 2006, said Scott Brown, the president. 

In an economy where new, specialized knowledge is worth so much, it may seem anticompetitive to share expertise. But many professionals say they don’t see it that way. 

“We’re scattered all over the country, Australia, New Zealand, the U.K., so it never really bothered us that we were sharing the secrets of what we do,” said Bill Moss, whose repair shop in Warrenton, Va., specializes in European cars, and who is a frequent user of peer-to-peer forums. 

Mr. Moss, 55, said technological advances and proprietary diagnostic tools had forced many garages to specialize. Ten years ago, if his business had hit a slow patch, he said, he would have been quicker to broaden his repertory. “I might have looked at other brands and said, ‘These cars aren’t so bad.’ That’s much harder to do now, based on technology and equipment requirements.” His training budget is about $4,000 a year for each repair technician. 

Learning curves are not always driven by technology. Managers have to deal with different cultures, different time zones and different generations as well as changing attitudes. As medical director of the Reproductive Science Center of New England, Dr. Samuel C. Pang has used patient focus groups and sensitivity training to help the staff adjust to treating lesbian couples, gay male couples, and transgendered couples who want to have children. This has given the clinic a competitive advantage. 

“We have had several male couples and lesbian couples come to our program from our competitors’ program because they said they didn’t feel comfortable there,” Dr. Pang said. 

On top of that, he has to master constantly evolving technology. “The amount of information that I learned in medical school is minuscule,” he said, “compared to what is out there now.” 

 http://www.nytimes.com/2012/09/22

A
adverb clause and adverb clause.
B
noun clause and adverb clause.
C
adjective clause and a noun clause.
D
adverb clause and a noun clause.
fc506226-b7
UECE 2012 - Inglês - Análise sintática | Syntax Parsing

In questions, sentences from the text may have been modified/adapted to fit certain grammatical structures.


In the sentences “…it never really bothered us that we were sharing the secrets of our profession.” and “…a lot of times they don’t know any better than us what’s going to happen in the future”, one finds, respectively, a/an



TEXT


The need to constantly adapt is the new reality for many workers, well beyond the information technology business. Car mechanics, librarians, doctors, Hollywood special effects designers — virtually everyone whose job is touched by computing — are being forced to find new, more efficient ways to learn as retooling becomes increasingly important not just to change careers, but simply to stay competitive on their chosen path.

Going back to school for months or years is not realistic for many workers, who are often left to figure out for themselves what new skills will make them more valuable, or just keep them from obsolescence. In their quest to occupy a useful niche, they are turning to bite-size instructional videos, peer-to-peer forums and virtual college courses.

Lynda Gratton, a professor of management practice at the London Business School, has coined a term for this necessity: “serial mastery.”

“You can’t expect that what you’ve become a master in will keep you valuable throughout the whole of your career, and you want to add to that the fact that most people are now going to be working into their 70s,” she said, adding that workers must try to choose specialties that cannot be outsourced or automated. “Being a generalist is, in my view, very unwise. Your major competitor is Wikipedia or Google.”

Businesses have responded by pouring more money into training, even in the current economic doldrums, according to several measures. They have experimented by paying employees to share their expertise in internal social networks, creating video games that teach and, human resources consultants say, enticing employees with tuition help even if they leave the company.

Individuals have also shouldered a lot of responsibility for their own upgrades. Lynda.com, which charges $25 a month for access to training videos on topics like the latest version of Photoshop, says its base of individual customers has been growing 42 percent a year since 2008. Online universities like Udacity and Coursera are on pace to double in size in a year, according to Josh Bersin of Bersin & Associates, a consulting firm that specializes in learning and talent management. The number of doctors participating in continuing education programs has more than doubled in the last decade, with the vast majority of the growth stemming from the increased popularity of Internet-based activities, according to the Accreditation Council for Continuing Medical Education in Chicago.

The struggle is not just to keep up, but to anticipate a future of rapid change. When the AshevilleBuncombe Technical Community College in North Carolina wanted to start a program for developing smartphone and tablet apps, the faculty had to consider the name carefully. “We had this title Mobile Applications, and then we realized that it may not be apps in two years, it may be something else,” said Pamela Silvers, the chairwoman of the business computer technologies department. “So we changed it to Mobile Development.”

As the metadata and digital archivist at Emory University, Elizabeth Russey Roke, 35, has had to keep up with evolving standards that help different databases share information, learn how to archive “born digital” materials, and use computers to bring literary and social connections among different collections to life. The bulk of her learning has been on the job, supplemented by the occasional course or videos on Lynda.com.

“For me, it’s easier to learn something in the classroom than it is on my own,” she said. “But I can’t exactly afford another three years of library school.”

Rapid change is a challenge for traditional universities; textbooks and even journals often lag too far behind the curve to be of help, said Kunal Mehta, a Ph.D. student in bioengineering at Stanford University. His field is so new, and changing so rapidly, he said, that there is little consensus on established practices or necessary skills. “It’s more difficult to know what we should learn,” he said. “We have advisers that we work with, but a lot of times they don’t know any better than us what’s going to happen in the future.” 

Instead, Mr. Mehta, 26, spends a lot of time comparing notes with others in his field, just as many professionals turn to their peers to help them stay current. The International Automotive Technicians Network, where mechanics pay $15 a month to trade tips on repairs, has more than 75,000 active users today, up from 48,000 in 2006, said Scott Brown, the president. 

In an economy where new, specialized knowledge is worth so much, it may seem anticompetitive to share expertise. But many professionals say they don’t see it that way. 

“We’re scattered all over the country, Australia, New Zealand, the U.K., so it never really bothered us that we were sharing the secrets of what we do,” said Bill Moss, whose repair shop in Warrenton, Va., specializes in European cars, and who is a frequent user of peer-to-peer forums. 

Mr. Moss, 55, said technological advances and proprietary diagnostic tools had forced many garages to specialize. Ten years ago, if his business had hit a slow patch, he said, he would have been quicker to broaden his repertory. “I might have looked at other brands and said, ‘These cars aren’t so bad.’ That’s much harder to do now, based on technology and equipment requirements.” His training budget is about $4,000 a year for each repair technician. 

Learning curves are not always driven by technology. Managers have to deal with different cultures, different time zones and different generations as well as changing attitudes. As medical director of the Reproductive Science Center of New England, Dr. Samuel C. Pang has used patient focus groups and sensitivity training to help the staff adjust to treating lesbian couples, gay male couples, and transgendered couples who want to have children. This has given the clinic a competitive advantage. 

“We have had several male couples and lesbian couples come to our program from our competitors’ program because they said they didn’t feel comfortable there,” Dr. Pang said. 

On top of that, he has to master constantly evolving technology. “The amount of information that I learned in medical school is minuscule,” he said, “compared to what is out there now.” 

 http://www.nytimes.com/2012/09/22

A
adjective clause and a noun clause.
B
noun clause and a noun clause.
C
adverb clause and an adjective clause.
D
noun clause and an adjective clause.
325f6268-b6
UECE 2010 - Inglês - Análise sintática | Syntax Parsing

In the sentences “In a chaotic world, which many see to be on a disaster course, through the cracks, „the faults in reality‟, we and our writers catch other vertiginous glimpses of „chaos and old night‟”, “The satiety which Macbeth claimed to have experienced (… ) was representative of it.” and “…people have tried to come to terms with and find adequate descriptions and symbols for deeply rooted, primitive and powerful forces, energies and fears which are related to death, afterlife, punishment, darkness, evil, violence and destruction.” one finds relative clauses classified respectively as


A
defining, non-defining, defining.
B
non-defining, defining, non-defining.
C
defining, non-defining, defining.
D
non-defining, defining, defining.
326431c6-b6
UECE 2010 - Inglês - Análise sintática | Syntax Parsing

The sentences “Fear created horrors enough and the eschatological order was never far from people‟s minds.”, “…artists depicted the spectre of death in paint, through sculpture and by means of woodcut.” and “we and our writers catch other vertiginous glimpses of „chaos and old night‟ ” contain respectively a/an


A
direct object, an indirect object, an indirect object.
B
indirect object, an indirect object, a direct object.
C
indirect object, a direct object, a direct object.
D
direct object, a direct object, a direct object.
324c3f29-b6
UECE 2010 - Inglês - Análise sintática | Syntax Parsing

The sentences “He depicts extremes of fear and insanity and, through the operations of evil, gives us glimpses of hell.” “Fear created horrors enough and the eschatological order was never far from people‟s minds.” and “From late in the 18th c. until the present day – in short, for some two hundred years – the horror story in its many and various forms has been a diachronic feature of British and American literature…” should be classified respectively as


A
complex, complex, compound.
B
simple, compound, complex.
C
compound, compound, simple.
D
compound, compound, complex.
32493520-b6
UECE 2010 - Inglês - Análise sintática | Syntax Parsing

In the sentence “Gothic influence traveled to America and affected writers such as Edgar Allan Poe, whose tales are short, intense, sensational and have the power to inspire horror and terror.” one may find at least one


A
noun clause.
B
adjective clause.
C
time clause.
D
contrast clause.
4e6a702c-af
UECE 2013 - Inglês - Análise sintática | Syntax Parsing

In the following question, some sentences from the text may have been modified to fit certain grammatical structures.


The sentences “…they know it will make them employable.” and “…Amazon tells them what books they should read” contain, respectively, a/an

TEXT
   
   HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
   The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
     In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
      Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
      Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
     Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
     “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
  Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
      Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
    With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
     Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
     Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
       Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

From: www.nytimes.com
A
subject noun clause and an object noun clause.
B
object noun clause and a subject noun clause.
C
subject noun clause and a subject noun clause.
D
object noun clause and an object noun clause.
4e675b3a-af
UECE 2013 - Inglês - Análise sintática | Syntax Parsing

In the following question, some sentences from the text may have been modified to fit certain grammatical structures.

The sentences “Ethics classes address these questions.” and “The United States will need a great number of graduates with skills handling large amounts of data.” contain, respectively, a/an

TEXT
   
   HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
   The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
     In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
      Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
      Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
     Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
     “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
  Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
      Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
    With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
     Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
     Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
       Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

From: www.nytimes.com
A
restrictive clause and a noun clause.
B
direct object and a direct object.
C
adverbial clause and a direct object.
D
indirect objet and an indirect object.
4e5eef0d-af
UECE 2013 - Inglês - Análise sintática | Syntax Parsing

In the sentences “We’re building these models that have impact on human life.” and “She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service.” one finds, respectively, a/an

TEXT
   
   HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
   The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
     In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
      Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
      Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
     Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
     “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
  Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
      Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
    With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
     Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
     Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
       Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

From: www.nytimes.com
A
adjective clause and an adverb clause.
B
adverb clause and a relative clause.
C
adverb clause and a noun clause.
D
noun clause and an adjective clause.
4e5b79d7-af
UECE 2013 - Inglês - Análise sintática | Syntax Parsing

The sentence “She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings.” contains

TEXT
   
   HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
   The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
     In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
      Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
      Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
     Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
     “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
  Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
      Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
    With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
     Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
     Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
       Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

From: www.nytimes.com
A
a conditional clause. 
B
an adjective clause.
C
two noun clauses. 
D
an adverbial place clause. 
4e585fd8-af
UECE 2013 - Inglês - Análise sintática | Syntax Parsing, Aspectos linguísticos | Linguistic aspects

The sentences “In the fall, Columbia will offer new master’s and certificate programs heavy on data.” and “Data scientists are the magicians of the Big Data era.” contain, respectively, at least one

TEXT
   
   HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
   The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
     In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
      Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
      Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
     Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
     “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
  Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
      Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
    With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
     Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
     Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
       Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

From: www.nytimes.com
A
direct object and subject complement.
B
object complement and direct object.
C
subject complement and direct object.
D
indirect object and object complement.
4e49edb9-af
UECE 2013 - Inglês - Análise sintática | Syntax Parsing

The sentences “They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it…” and “In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data...” should be classified respectively as

TEXT
   
   HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
   The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
     In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
      Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
      Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
     Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
     “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
  Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
      Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
    With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
     Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
     Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
       Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

From: www.nytimes.com
A
simple and compound.
B
complex and compound.
C
compound and simple.
D
compound-complex and simple
4e4f465a-af
UECE 2013 - Inglês - Análise sintática | Syntax Parsing, Aspectos linguísticos | Linguistic aspects, Orações condicionais | Conditional Clauses

The sentences “Many use data sets provided by businesses or government, and pass back their results.” and “Because data science is so new, universities are scrambling to define it…” contain, respectively, a

TEXT
   
   HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
   The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
     In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
      Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
      Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
     Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
     “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
  Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
      Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
    With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
     Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
     Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
       Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

From: www.nytimes.com
A
subordinate clause and a coordinate clause.
B
subordinate clause and a subordinate clause.
C
coordinate clause and a coordinate clause.
D
coordinate clause and a subordinate clause.
a224ca13-a5
UECE 2011 - Inglês - Análise sintática | Syntax Parsing

The sentences “I recorded all my children over the years in some shape or form.”/ “It's a more sophisticated kind of communicative medium.” and “You get semantic threads running through it.” have syntactic elements that may be classified respectively as

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A
subject complement, direct object, direct object.
B
indirect object, subject complement, indirect object.
C
direct object, subject complement, direct object.
D
direct object, direct object, subject complement.
984e532a-a5
UECE 2011 - Inglês - Análise sintática | Syntax Parsing

In the sentences “We are rearing a generation of kids who are more equitable and more understanding about the existence of language variety...” and “… some are academic but many are for the general inquisitive reader, including By Hook or by Crook: A Journey in Search of English and Shakespeare's Words, which was co-authored by his son, Ben.” one finds relative clauses that should be classified respectively as

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A
defining and defining.
B
non-defining and defining.
C
defining and non-defining.
D
non-defining and non-defining.
9dead020-a5
UECE 2011 - Inglês - Análise sintática | Syntax Parsing

The sentence “All these different genres – instant messaging, blogging, chatrooms, virtual worlds – have evolved different sets of communicative strategies.” is an example of a

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A
complex sentence.
B
simple sentence.
C
compound sentence.
D
compound-complex sentence.
9b294132-a5
UECE 2011 - Inglês - Análise sintática | Syntax Parsing, Aspectos linguísticos | Linguistic aspects

In the sentence “When it gradually came back in, we didn't want to go back to what we did in the 1950s.” one may spot in its sequence a/an

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A
noun clause and an adjective clause.
B
adverb clause and a noun clause.
C
adjective clause and an adverbial clause.
D
noun clause and a noun clause.
99ba8fc8-a5
UECE 2011 - Inglês - Análise sintática | Syntax Parsing

The sentences “In the jaunty early chapters of A Little Book of Language, Crystal notes how, when his four children were young, he would study them.”, and “You don't talk to a linguist without having what you say taken down and used in evidence against you at some point in time.” contain, respectively, at least one

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A
adjective clause and adjective clause.
B
adverb clause and noun clause.
C
adjective clause and adverb clause.
D
adverb clause and adjective clause.
96c737b0-a5
UECE 2011 - Inglês - Análise sintática | Syntax Parsing

The sentences “This all sounds very innocent, but books for children can be a contentious issue.” and “Language, as much as history, is part of a national identity and cannot escape contemporary debates.” should be classified respectively as

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A
simple and compound.
B
compound and simple.
C
complex and complex.
D
compound and compound.
0dbcc600-91
UECE 2015 - Inglês - Análise sintática | Syntax Parsing, Aspectos linguísticos | Linguistic aspects

In the sentence “In New York, demand for story time has surged across the city’s three library systems — the New York Public Library, the Brooklyn Public Library, and the Queens Library — and has posed logistical challenges for some branches…” the link between the two clauses is established by a/an

TEXT

    A library tradition is being refashioned to emphasize early literacy and better prepare young children for school, and drawing many new fans in the process.

    Among parents of the under-5 set, spots for story time have become as coveted as seats for a hot Broadway show like “Hamilton.” Lines stretch down the block at some branches, with tickets given out on a first-come-first-served basis because there is not enough room to accommodate all of the children who show up.

    Workers at the 67th Street Library on the Upper East Side of Manhattan turn away at least 10 people from every reading. They have been so overwhelmed by the rush at story time — held in the branch’s largest room, on the third floor — that once the space is full, they close the door and shut down the elevator. “It is so crowded and so popular, it’s insane,” Jacqueline Schector, a librarian, said.

    Story time is drawing capacity crowds at public libraries across New York and across the country at a time when, more than ever, educators are emphasizing the importance of early literacy in preparing children for school and for developing critical thinking skills. The demand crosses economic lines, with parents at all income levels vying to get in.

    Many libraries have refashioned the traditional readings to include enrichment activities such as counting numbers and naming colors, as well as music and dance. And many parents have made story time a fixture in their family routines alongside school pickups and playground outings — and, for those who employ nannies, a nonnegotiable requirement of the job.

    In New York, demand for story time has surged across the city’s three library systems — the New York Public Library, the Brooklyn Public Library, and the Queens Library — and has posed logistical challenges for some branches, particularly those in small or cramped buildings. Citywide, story time attendance rose to 510,367 people in fiscal year 2015, up nearly 28 percent from 399,751 in fiscal 2013.

    “The secret’s out,” said Lucy Yates, 44, an opera coach with two sons who goes to story time at the Fort Washington Library every week.

    Stroller-pushing parents and nannies begin to line up for story time outside some branches an hour before doors open. To prevent overcrowding, tickets are given out at the New Amsterdam and Webster branches, both in Manhattan, the Parkchester branch in the Bronx, and a half-dozen branches in Brooklyn, including in Park Slope, Kensington and Bay Ridge.

    The 67th Street branch keeps adding story times — there are now six a week — and holds sessions outdoors in the summer, when crowds can swell to 200 people.

    In Queens, 41 library branches are scheduled to add weekend hours this month, and many will undoubtedly include weekend story times. As Joanne King, a spokeswoman for the library explained, parents have been begging for them and “every story time is full, every time we have one.”

    Long a library staple, story time has typically been an informal reading to a small group of boys and girls sitting in a circle. Today’s story times involve carefully planned lessons by specially trained librarians that emphasize education as much as entertainment, and often include suggestions for parents and caregivers about how to reinforce what children have learned, library officials said.

    Libraries around the country have expanded story time and other children’s programs in recent years, attracting a new generation of patrons in an age when online offerings sometimes make trips to the book stacks unnecessary. Sari Feldman, president of the American Library Association, said such early-literacy efforts are part of a larger transformation libraries are undergoing to become active learning centers for their communities by offering services like classes in English as a second language, computer skills and career counseling.

    Ms. Feldman said the increased demand for story time was a product, in part, of more than a decade of work by the library association and others to encourage libraries to play a larger role in preparing young children for school. In 2004, as part of that effort, the association developed a curriculum, “Every Child Ready to Read,” that she said is now used by thousands of libraries.

    The New York Public Library is adding 45 children’s librarians to support story time and other programs, some of which are run in partnership with the city government. It has also designated 20 of its 88 neighborhood branches, including the Fort Washington Library, as “enhanced literary sites.” As such, they will double their story time sessions, to an average of four a week, and distribute 15,000 “family literacy kits” that include a book and a schedule of story times.

    “It is clear that reading and being exposed to books early in life are critical factors in student success,” Anthony W. Marx, president of the New York Public Library, said. “The library is playing an increasingly important role in strengthening early literacy in this city, expanding efforts to bring reading to children and their families through quality, free story times, curated literacy programs, after-school programs and more.”

    For its part, the Queens Library plans to expand a “Kick Off to Kindergarten” program that attracted more than 180 families for a series of workshops last year. Library officials said that more than three-quarters of the children who enrolled, many of whom spoke a language other than English at home, developed measurable classroom skills.

From: www.nytimes.com/2015/11/02

A
coordinating conjunction.
B
subordinating conjunction.
C
adverbial conjunction.
D
contrastive conjunction.