Automatic Meaning Discovery Using Google
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2023-2024学年河南省信阳市高一英语下学期期末考试卷(含答案)注意事项:本试卷分四部分,考试时间120分钟,满分150分。
考生应首先阅读答题卡上的文字信息,然后在答题卡上作答,在试题卷上作答无效。
第一部分听力(共两节,满分30分)做题时,先将答案标在试卷上。
录音内容结束后,你将有两分钟的时间将试卷上的答案转涂到答题卡上。
第一节(共5小题;每小题1.5分,满分7.5分)听下面5段对话。
每段对话后有一个小题,从题中所给的A、 B、C三个选项中选出最佳选项,并标在试卷的相应位置。
听完每段对话后,你都有10秒钟的时间来回答有关小题和阅读下一小题。
每段对话仅读一遍。
1.Where is Jason going today?A.His father’s farm.B.The basketball court.C.His grandparents’ house. 2.How many people are eating with the man?A.Two.B.Three.C.Four.3.What is the topic of the dialogue?A.A paper.B.A speech.C.A teacher.4.What are the speakers probably doing?A.Talking on the phone.B.Chatting face to face.C.Making a video call. 5.How do the cookies taste?A.Salty.B.Sweet.C.Tasteless.第二节(共15小题;每小题1.5分,满分22.5分)听下面5段对话或独白。
每段对话或独白后有几个小题,从题中所给的A、B、C三个选项中选出最佳选项,并标在试卷的相应位置。
听每段对话或独白前,你将有时间阅读各个小题,每小题5秒钟;听完后,各小题将给出5秒钟的作答时间。
2025高考英语步步高大一轮复习讲义人教版必修第一册高考题型组合练必修第一册Unit 4Natural DisastersⅠ.阅读理解A(★)As a shift in the polar vortex(极地涡旋) swept across much of the US,many people in the country were hit with a sudden snap of cold.Heavy ice and snow coupled with fallen trees caused the outages in major cities,with companies unable to tell their customers when power will be restored.Polar vortices were noticed long ago.But the first known use of the term “polar vortex” was in a magazine in 1853.Polar vortices are present year-round,but we don’t hear about them until they cause problems.They maintain freezing temperatures at the North and South Poles by moving in tight counterclockwise patterns.Polar vortices grow stronger in winter and weaken in summer.They are kept in place at the poles by another atmospheric current called the jet stream.However,when the jet streams weaken,the cold winds of the polar vortex are pushed southwards and it is during this time that people begin to pay attention!In Texas,roads froze over,causing six traffic deaths,and many schools were shut down.People are not the only Earthlings to struggle with the cold.Crops and animals are also freezing.This could have major consequences,especially if herds of cattle die.If snow blocks cattle,the animals can’t reach basic necessities like food and fresh water.On a brighter note,some Texas cities were more prepared than others,for instance,Amarillo,which is located in North Texas,so they are more accustomed to colder temperatures.Amarillo is notable because the city was redesigned to stand up to severe winter storms.Officials have spread out fire stations to increase coverage of first responders,employed modified dump trucks for clearing ice,and upgraded civic centers to provide shelter during storms.Hopefully,other Texas cities will follow the good example set by Amarillo!1.What does the underlined word “outages” refer to in paragraph 1?A.Traffic jams. B.Power struggles. C.Power cuts. D.Traffic accidents.2.What can we learn about polar vortices?A.They grow stronger in summer. B.They are affected by jet streams.C.They were first observed in 1853. D.They move in a clockwise direction.3.What is the last but one paragraph mainly about?A.The definition of the polar vortex.B.The characteristics of the polar vortex.C.The ways to deal with the polar vortex.D.The serious impact made by the polar vortex.4.Why is Amarillo striking?A.Because it is located in the north of Texas.B.Because it has been upgraded and modernized.C.Because it has been regarded as an example to other cities.D.Because it has taken effective measures to resist winter storms.BWhat is the 15-minute city?It’s the urban planning concept that everything city residents need should be a short walk or bike ride away—about 15 minutes from home to work,shopping,entertainment,restaurants,schools,parks and health care.Supporters argue that 15-minute cities are healthier for residents and the environment,creating united mini-communities,boosting local businesses,and encouraging people to get outside walk,and cycle.Many cities across Europe offer similar ideas,but Paris has become its poster child.Mayor Anne Hidalgo has sought to fight climate change by decreasing choking traffic in the streets and fuel emissions.In 2015,Paris was 17th on the list of bike-friendly cities; by 2019,it was 8th.Car ownership,meanwhile,dropped from 60 percent of households in 2001 to 35 percent in 2019.The 15-minute city figured largely in Hidalgo’s successful 2020 re-election campaign.The idea has also gained support in the U.S.It clearly won’t work everywhere:Not every city is as centralized and walkable as Paris.Some car-dominated cities like Los Angeles and Phoenix would be hard-pressed to provide everything people need within walking distance.In addition,some urban planners argue that the 15-minute city could increase the separation of neighborhoods by income.Neighborhoods equipped with all the conveniences required by the 15-minute city also tend to have high housing costs and wealthier residents.Despite some resistance,the basic principles behind the 15-minute city are influencing planning in cities around the world,including Melbourne,Barcelona,Buenos Aires,Singapore,and Shanghai.Urban designer and thinker Jay Pitter says cities where basic needs are within walking distance create more individual freedom than needing to drive everywhere.“In a city where services are always close by,” he says,“mobility is a choice:You go where you want because you want to,not because you have to.My fight is not against the car.My fight is how we could improve the quality of life.”5.Which best describes the 15-minute city?A.Modern. B.Smart. C.Entertaining. D.Convenient.6.What’s the original intention for Paris to advocate the 15-minute city?A.To address climate issues. B.To beautify the city.C.To promote the bike industry. D.To help Hidalgo get re-elected.7.What’s some urban planners’ worry about the 15-minute city?A.It slows the city’s expansion.B.It represents a setback for society.C.It may widen the gap between neighborhoods.D.It can cause the specialization of neighborhoods.8.What’s Jay Pitter’s attitude to the concept of 15-minute city?A.Doubtful. B.Favorable. C.Critical. D.Uninterested.C(★)Earthquake forecasting is one of the most ancient skills known to mankind.From ancient Greece to the present day,countless scientists have tried to develop tools to predict earthquakes.Their attempts usually focused on searching for reliable evidence of coming quakes.However,there are many reasons why predicting quakes is so hard.“We don’t understand some basic physics of earthquakes,” said Egill,a research professor at the California Institute of Technology.Scientists have also attempted to create mathematical models of movement,but precisely predicting would require great mapping and analysis of the Earth’s crust.Other challenges include a lack of data on the early warning signs,given that these warning signs are not yet entirely understood.Actually,real earthquake prediction is very similar to the diagnosis of potential human illnesses based on observing and analyzing each patient’s signs and symptoms.As it turns out,quake prediction is extremely difficult.Many sources show that earthquake forecasting was recognized science in ancient Greece.Ancient Greeks lived very close to nature and were able to detect unusual phenomena and forecast earthquakes.The first known forecast was made by Pherecydes of Syros about 2,500 years ago:he made it as he scooped water from a well and noticed that usually very clean water had suddenly become muddy.Indeed,an earthquake occurred two days later,making Pherecydes famous.Nowadays,seismic(地震的) and remote-sensing methods are considered to have the greatest potential in terms of solving the earthquake prediction problem.Currently,Terra Seismic can identify a forthcoming earthquake with a high level of confidence.Generally,Terra Seismic does not predict a quake if the earthquake’s epicenter is located beyond a depth of 40km.Fortunately,such quakes are almost always harmless,since quake’s energy reduces before reaching the Earth’s surface.“Scientists have tried every possible method to try to predict earthquakes,” Bruneau said.“Nobody has been able to crack it and make a believable prediction.”9.What do we know about earthquake forecasting?A.Scientists have been passionate about accurately predicting earthquakes.B.As long as enough data is collected,earthquakes can be avoided.C.Mathematical models of motion can simulate and predict earthquakes.D.Scientists have fully studied the structure of earthquakes.10.How did Pherecydes successfully predict that earthquake?A.By seismic and remote-sensing methods.B.By observing unusual natural phenomena.C.By living in seismic zones throughout the year.D.By looking into data on the early warning signs.11.What was Bruneau’s opinion about the current methods of earthquake prediction? A.He strongly believed the Terra Seismic can solve the difficult problem.B.He was sure that humans could accurately predict earthquakes in the future.C.He considered it harmless to humans for an earthquake deeper than 40km.D.He thought that scientists had no reliable method to predict earthquakes.12.What is the text mainly about?A.Why do humans predict earthquakes.B.How to protect oneself during an earthquake.C.What methods can be used to forecast earthquakes.D.When to achieve accurate earthquake forecasting.Ⅱ.七选五(★)Hurricane season can be wild and unpredictable. 1 Here are some ways you can beef up your home security in hurricane weather,even if you need to move out.2 That actually does nothing to ensure your safety in the powerful winds.Sticking to hurricane shelters or plywood(胶合板) is the only way to go when it comes to protecting those points of entry in hurricane conditions.Buy sheets of plywood,measure your windows and use brackets(支架) to hold the plywood in place.Sandbags are very useful.While sandbags won’t be able to help in the extreme storm,many people will be able to prevent flooding and extensive damage to their belongings by placing sandbags. 3 Any storm water that is kept out of your home is storm water that won’t be able to damage the belongings inside your home,so sandbags are well worth having at your doorways during a hurricane.It’s important to prepare the inside of your home for strong winds and rain.But you should also keep an eye on the outside of your house,too.Trim(修剪) trees,especially dead branches,to prevent anything else that could fly through a window and cause damage during a hurricane. 4 You should also take pictures of expensive items like electronics and keep notes of their serialnumbers. 5 Also,there are always bad people out right after a storm.If the worst happens and your home is broken into right after a bad storm,having pictures and detailed notes about what was in your home prior to the hurricane will make it easier for police to track down stolen items. A.You should have a camera at home.B.It can be strong enough to resist the forceful winds.C.Making sure nothing is loose in your yard is important.D.You may see people taping windows before a hurricane comes.E.They will be able to effectively keep storm water out in many cases.F.It will aid with your insurance company if anything needs to be replaced.G.These dangerous storms can bring damage to your home and belongings.必修第一册Unit 5Languages Around the WorldⅠ.阅读理解AMost of us take the task of buying a cup of coffee for granted,as it seems simple enough.However,we have no idea just how stressful tasks like this can be for people who suffer from disabilities.That’s why it’s so heart-warming to see a story like this in which a barista (咖啡师) does something small to make life a little easier for someone who is deaf.Ibby Piracha lost his hearing when he was only two years old,and he now goes to his local cafe in Leesburg,Virginia to order a cup of coffee at least three times a week.Though all the baristas who work there have his order memorized,Ibby always writes his order on his phone and shows it to the barista.One day,however,one of the baristas did something that changed everything! After Ibby ordered his coffee,he was amazed when barista Krystal Pane handed him a note in response.“I’ve been learning sign language just so you can have the same experience as everyone else,” the note read.Krystal then asked Ibby in sign language what he would like to order.Ibby was touched that she would learn sign language just to help him feel welcome.“I was just so moved that she actually wanted to learn sign language.It is really a totally different language and it was something that she wanted to do because of me.Because I was a deaf customer.I was very,very impressed,” Ibby said.Krystal had spent hours watching teaching videos so that she could learn enough sign language to give Ibby the best customer service that she could! “My job is to make sure peoplehave the experience they expect and that’s what I gave him,” Krystal says.Ibby posted a photo of Krystal’s note online,and it quickly went viral,getting hundreds of likes and comments that praised Krystal for her kind action.1.What can we learn about Ibby Piracha from paragraph 2?A.He was born deaf. B.He lives a hard life.C.He loves to order take-out food. D.He visits the cafe regularly.2.Why did Krystal learn sign language?A.To serve Ibby better. B.To attract more customers.C.To give Ibby a big surprise. D.To make herself more popular.3.Which of the following can best describe Krystal?A.Kind and considerate. B.Honest and responsible.C.Sociable and humorous. D.Ambitious and sensitive.4.What message does the author want to convey in the text?A.Two heads are better than one. B.A small act makes a difference.C.One good turn deserves another. D.Actions speak louder than words.B(★)(2024·湖北武汉调研)When I mentioned to some friends that we all have accents,most of them proudly replied,“Well,I speak perfect English/Chinese/etc.” But this kind of saying misses the point.More often than not,what we mean when we say someone “has an accent” is that their accent is different from the local one,or that pronunciations are different from our own.But this definition of accents is limiting and could give rise to prejudice.Funnily enough,in terms of the language study,every person speaks with an accent.It is the regular differences in how we produce sounds that define our accents.Even if you don’t hear it yourself,you speak with some sort of accent.In this sense,it’s pointless to point out that someone “has an accent”.We all do!Every person speaks a dialect,too.In the field of language study,a dialect is a version of a language that is characterized by its variations of structure,phrases and words.For instance,“You got eat or not?”(meaning “Have you eaten?”) is an acceptable and understood question in Singapore Oral English.The fact that this expression would cause a standard American English speaker to take pause doesn’t mean that Singapore Oral English is “wrong”or “ungrammatical”.The sentence is well-formed and clearly communicative,according to native Singapore English speakers’ solid system of grammar.Why should it be wrong just because it’s different?We need to move beyond a narrow conception of accents and dialects—for the benefit ofeveryone.Language differences like these provide insights into people’s cultural experiences and backgrounds.In a global age,the way one speaks is a distinct part of one’s identity.Most people would be happy to talk about the cultures behind their speech.We’d learn more about the world we live in and make friends along the way.5.What does the author think of his/her friends’ response in paragraph 1?A.It reflects their self confidence.B.It reflects their language levels.C.It misses the point of communication.D.It misses the real meaning of accents.6.Why does the author use the example of Singapore Oral English?A.To justify the use of dialects. B.To show the diversity of dialects.C.To correct a grammatical mistake. D.To highlight a traditional approach.7.What does the author recommend us to do in the last paragraph?A.Learn to speak with your local dialect.B.Seek for an official definition of accents.C.Appreciate the value of accents and dialects.D.Distinguish our local languages from others’.8.What can be a suitable title for the passage?A.Everyone Has an Accent B.Standard English Is at RiskC.Accents Enhance Our Identities D.Dialects Lead to MisunderstandingⅡ.完形填空One summer night in a seaside cottage,a small boy was in bed,sound asleep.Suddenly,he felt himself 1 from bed and carried in his father’s arms onto the beach.Overhead was the clear starry sky.“Watch!” As his father spoke, 2 ,one of the stars moved.It 3 across the sky like a golden fire.And before the 4 of this could fade,another star leapt from its place,then another...“What is it?” the child asked in 5 .“Shooting stars.They 6 every year on a certain night in August.”That was all:just an 7 encounter of something magic and beautiful.But,back in bed,the child stared into the dark,with mind full of the falling stars.I was the 8 seven-year-old boy whose father believed that a new experience 9 more for a small boy than an unbroken night’s sleep.That night,my father opened a door for his child,leading him into an area of splendid10 .Children are naturally curious,but they need someone to 11 them.This art of adding new dimensions to a child’s world doesn’t 12 require a great deal of time.It simply 13 doing things more often with children instead of for them or to them.Good parents know this:The most precious gift they can give a child is to spark their flame of 14 .That night is still deeply 15 in my memory.Next year,when August comes with its shooting stars,my son will be seven.1.A.hidden B.robbed C.lifted D.kicked2.A.incredibly B.accidentally C.apparently D.actually3.A.exploded B.circled C.spread D.flashed4.A.success B.wonder C.exhibition D.discovery5.A.amazement B.horror C.relief D.delight6.A.blow up B.turn up C.show off D.give out7.A.uncomfortable B.unbearable C.undetected D.unexpected8.A.curious B.fortunate C.determined D.chosen9.A.worked B.mattered C.deserved D.proved10.A.newness B.emptiness C.freedom D.innovation11.A.protect B.challenge C.guide D.believe12.A.absolutely B.basically C.possibly D.necessarily13.A.involves B.risks C.admits D.resists14.A.hope B.faith C.curiosity D.wisdom15.A.trapped B.set C.lost D.rootedⅢ.语法填空(★)The Olympics are a series of international athletic competitions held in different countries.They’re 1. important multi-sport event that takes place every four years.For the Olympics,participants from all over the world train for years and try their best 2. (win).Pierre Coubertin,a French man,3. (found) the International Olympic Committee (IOC) in 1894.He was once a teacher and historian.In his honor,French had the official status(地位) and 4. (prior) over other languages at the Olympics.According to the Olympic Charter,English and French are the official languages of the Olympics.Therefore,every participant needs to have their documents 5. (translate) in both languages.Besides,real-time interpretations in Arabic,German,Russian,and Spanish must be available for all sessions.The IOC has a complete guide for those 6. want to apply to these contests.French has the status of being the first official language for Olympic events and it was the language of diplomacy (外交) in the beginning.But later,more countries considered 7. (participate) in this contest.The IOC then made French and English the official languages of the Olympics.8.(actual),more than 100 countries in the world speak English now.Besides,almost every country has made 9. a must that children learn English in schools and colleges.This 10. (influence) status has caused the IOC to make English one of the official languages.必修第一册Welcome UnitⅠ.阅读理解AThroughout all the events in my life,one in particular sticks out more than the others.As I reflect on this significant event,a smile spreads across my face.As I think of Shanda,I feel loved and grateful.It was my twelfth year of dancing,I thought it would end up like any other year:stuck in emptiness,forgotten and without the belief of any teacher or friend that I really had the potential to achieve greatness.However,I met Shanda,a young,talented choreographer(编舞者).She influenced me to work to the best of my ability,pushed me to keep going when I wanted to give up,encouraged me and showed me the real importance of dancing.Throughout our hard work,not only did my ability to dance grow,but my friendship with Shanda grew as well.With the end of the year came our show time.As I walked to a backstage filled with other dancers,I hoped for a good performance that would prove my improvement.I waited anxiously for my turn.Finally,after what seemed like days,the loudspeaker announced my name.Butterflies filled my stomach as I took trembling steps onto the big lighted stage.But,with the determination to succeed and eagerness to live up to Shanda’s expectations for me,I began to dance.All my troubles and nerves went away as I danced my whole heart out.As I walked up to the judge to receive my first-place shining,gold trophy(奖杯),I realized that dance is not about becoming the best.It is about loving dance for dance itself,a getaway from all my problems in the world.Shanda showed me that you could let everything go and just dance what you feel at that moment.After all the doubts that people had in me,I believed in myself and did not care what others thought.Thanks to Shanda,dance became more than a love of mine,but a passion.1.What did the author think her dancing would be for the twelfth year?A.A change for the better. B.A disappointment as before.C.A proof of her potential. D.A pride of her teachers and friends.2.How did Shanda help the author?A.By offering her financial help. B.By entering her in a competition.C.By coaching her for longer hours. D.By awakening her passion for dancing.3.How did the author feel when she stepped on the stage?A.Proud. B.Nervous. C.Scared. D.Relieved.4.What can we learn from the author’s story?A.Success lies in patience. B.Fame is a great thirst of the young.C.A good teacher matters. D.A youth is to be treated with respect.B(★)Are you a good judge of character?Can you make an accurate judgement of someone’s personality based only on your first impression of them?Interestingly,the answer lies as much in them as it does in you.One of the first people to try to identify good judges of character was US psychologist Henry F Adams in 1927.His research led him to conclude that people fell into two groups—good judges of themselves and good judges of others.Adams’s research has been widely criticized since then,but he wasn’t entirely wrong about there being two clearly different types.More on that in a moment,but first we need to define what a good judge of character is.Is it someone who can read personality or someone who can read emotion?Those are two different skills.Emotions such as anger or joy or sadness can generate easily identifiable physical signs.Most of us would probably be able to accurately identify these signs,even in a stranger.As such,most of us are probably good judges of emotion.In order to be a good judge of personality,however,there needs to be an interaction with the other person,and that person needs to be a “good target”.“Good targets” are people who reveal relevant and useful signals to their personality.So this means “the good judge” will only manifest when reading “good targets”.This is according to Rogers and Biesanz in their 2019 journal entitled “Reassessing the good judge of personality”.“We found consistent,clear and strong evidence that the good judge does exist,” Rogers and Biesanz concluded.But their key finding is that the good judge does not have magical gifts of perception—they are simply able to “detect and use the information provided by the good target”.So,are first impressions really accurate?Well,if you’re a good judge talking to a “good target”,then it seems the answer is “yes”.And now we know that good judges probably do exist,more research can be done into how they read personality,what kind of people they are—and whether their skills can be taught.5.What can we learn about Adams from paragraph 2?A.He is a good judge of character.B.He divided psychologists into two groups.C.His research result has been widely accepted.D.His research on good judges was partially right.6.What does the author think of emotion reading?A.Annoying. B.Joyful. C.Simple. D.Strange.7.Which of the following would Rogers and Biesanz agree with?A.A good target is necessary for personality judgement.B.A good target needs to get his personality reassessed.C.A good judge can provide useful signals to our personality.D.It’s possible to be a good judge just by looking at the other person.8.What does the author think future research should focus on?A.The skills of good communication. B.The features of good judges.C.The ways to read personality. D.The accuracy of first impressions.C(2023·新课标Ⅱ,C)Reading Art: Art for Book Lo v ers is a celebration of an everyday object—the book,represented here in almost three hundred artworks from museums around the world.The image of the reader appears throughout history,in art made long before books as we now know them came into being.In artists’ representations of books and reading,we see moments of shared humanity that go beyond culture and time.In this “book of books”,artworks are selected and arranged in a way that emphasizes these connections between different eras and cultures.We see scenes of children learning to read at home or at school,with the book as a focus for relations between the generations.Adults are portrayed(描绘) alone in many settings and poses—absorbed in a volume,deep in thought or lost in a moment of leisure.These scenes may have been painted hundreds of years ago,but they record moments we can all relate to.Books themselves may be used symbolically in paintings to demonstrate the intellect(才智),wealth or faith of the subject.Before the wide use of the printing press,books were treasured objects and could be works of art in their own right.More recently,as books have become inexpensive or even throwaway,artists have used them as the raw material for artworks—transforming covers,pages or even complete volumes into paintings and sculptures.Continued developments in communication technologies were once believed to make the printed page outdated.From a 21st-century point of view,the printed book is certainly ancient,but it remains as interactive as any battery-powered e-reader.To serve its function,a book must be activated by a user: the cover opened,the pages parted,the contents reviewed,perhaps notes written down or words underlined.And in contrast to our increasingly networked lives where theinformation we consume is monitored and tracked,a printed book still offers the chance of a wholly private,“off-line” activity.9.Where is the text most probably taken from?A.An introduction to a book. B.An essay on the art of writing.C.A guidebook to a museum. D.A review of modern paintings.10.What are the selected artworks about?A.Wealth and intellect. B.Home and school.C.Books and reading. D.Work and leisure.11.What do the underlined words “relate to” in paragraph 2 mean?A.Understand. B.Paint. C.Seize. D.Transform.12.What does the author want to say by mentioning the e-reader?A.The printed book is not totally out of date.B.Technology has changed the way we read.C.Our lives in the 21st century are networked.D.People now rarely have the patience to read.Ⅱ.七选五Wonderful views from the mountains,breathtaking places waiting to explore,fresh air,as well as all the special health benefits,are the main rewards of mountain hiking. 1You need to train your lower body muscles,anytime and anywhere.Strong legs and core muscles will improve your balance and help you hike longer.Focus on your lower body strength and on your cardiovascular(心血管的) workout. 2 You really can train anywhere:use your backyard,living room,or bedroom to keep your body ready for the true conditions in the mountains.You will need a stronger back.Who’s going to carry your backpack? 3 So we are quite sure what the true answer is.Develop back muscles with exercises like V-ups,deadlifts,diver push-ups,and exercise named “mountain climbers”:Start in a traditional plank(平板支撑) position and then bring your knee forward under your chest.You will start to feel your abs(腹肌) for sure,too.4 Even Rome wasn’t built in a day so give yourself the pleasure to enjoy discovering what your body is capable of! All the perfect benefits will improve your blood pressure and blood sugar levels,helping you strengthen your core,and even help you control your weight as an additional benefit.5 Just don’t forget to stretch after each training.Please remember that your training for mountain hiking should be combined with real hiking.And don’t miss the other clues on what to do for mountaineering training!。
小学上册英语第3单元测验试卷英语试题一、综合题(本题有100小题,每小题1分,共100分.每小题不选、错误,均不给分)1.The _____ (绿色能源) movement promotes plant-based solutions.2.The _____ (cat/dog) is sleeping.3.The ______ (香味) of flowers can be very strong.4.What do we call a scientist who studies the properties of matter?A. ChemistB. PhysicistC. BiologistD. Geologist答案:A5.I want to _____ (see/watch) a movie tonight.6.What is the main language spoken in the USA?A. SpanishB. FrenchC. EnglishD. German答案:C7.The cake is ________ and sweet.8.We share ______ (秘密) with each other.9.I enjoy going ______ (远足) to enjoy the beauty of nature.10.The ______ teaches us about civic responsibilities.11.The chemical properties of an element depend on its ______ structure.12.The country famous for its tango is ________ (阿根廷).13.What is the opposite of 'fast'?A. QuickB. SlowC. SpeedyD. Rapid14.What is the capital of Tunisia?A. TunisB. SousseC. MonastirD. Bizerte答案:A15.What do you call a house made of ice?A. IglooB. CabinC. CastleD. Hut答案:A16._____ (当地植物) can adapt to specific environments.17.Chemical reactions often involve a change in ______.18.The __________ is the layer of skin that helps to protect against injury.19.I enjoy making memories with my toy ________ (玩具名称).20.I can ________ (manage) my time effectively.21.What do we call the opposite of ‘clean’?A. DirtyB. NeatC. TidyD. Clear22. A __________ is a sudden release of energy in the Earth's crust.23.My friend is a ______. He loves to collect stamps.24.My dad shows me how to be __________ (勇敢的) in difficult times.25.What is the largest country in the world?A. CanadaB. ChinaC. RussiaD. India26.The _______ (The Battle of Waterloo) marked the defeat of Napoleon.27.The ____ is a small creature that hides under leaves.28.What do we call the study of the universe?A. BiologyB. AstronomyC. GeologyD. Physics答案:B29.The _____ (果实) develops after a flower blooms.30. Wall of China was built to __________ (保护) the country from invasions. The Grea31.The ant carries food back to its ______ (巢).32.What is 4 + 5?A. 8B. 9C. 10D. 1133.The _____ (水果收成) happens in late summer.34.Many plants have a specific ______ period for blooming. (许多植物有特定的开花期。
小学上册英语第2单元期末试卷英语试题一、综合题(本题有100小题,每小题1分,共100分.每小题不选、错误,均不给分)1.__________ can evaporate and leave behind a solid residue.2.How many seasons are there in a year?A. TwoB. ThreeC. FourD. Five3. A mixture that has a uniform appearance is called a ______ mixture.4.The ______ (老鼠) is afraid of cats.5. A __________ is a natural resource that can be depleted.6.She is _____ (writing) in her notebook.7.ts are ______ (肉质的) and store water. Some pla8.Which planet is known for having a "great red spot"?A. VenusB. MarsC. JupiterD. SaturnC9.What is the main language spoken in the UK?A. FrenchB. SpanishC. EnglishD. German10.The ______ creates beautiful art.11.How many letters are in the English alphabet?A. 24B. 25C. 26D. 2712.There is a __________ in the sky.13.The phone is ringing ________ (响).14.How do you say "friend" in Spanish?A. AmigoB. AmieC. FrèreD. Buddy15.I like to collect _____ from different places. (postcards)16.The fruits are fresh and ___. (juicy)17.Which animal is famous for its slow movement?A. CheetahB. SlothC. RabbitD. HorseB18.My ________ (玩具名称) is inspired by my favorite character.19.What is the opposite of fast?A. QuickB. SlowC. SpeedyD. Rapid20.The _______ (蜥蜴) can be very quick.21.I find ________ (化学) very interesting.22.I have a ________ that glows in the dark.23.This girl, ______ (这个女孩), enjoys acting in plays.24.The ________ (覆盖层) protects the soil.25.The snow is ___ (white/black).26.ocean) is home to many fish and other marine life. The ____27.I enjoy exploring nature and going on ______ (远足) with my family. We see beautiful ______ (风景) along the way.28.The ancient Greeks held the Olympic Games every __________ years. (四年)29.The ________ was a major event that shaped modern European history.30.What is the name of the famous American musician known for "Shallow"?A. Lady GagaB. Kelly ClarksonC. AdeleD. Kacey MusgravesA31.The _____ (pillow) is soft.32.What is the name of the ocean on the east coast of the USA?A. Atlantic OceanB. Pacific OceanC. Indian OceanD. Arctic OceanA33.Many _______ have different blooming seasons.34.The __________ (历史的理解过程) is essential for growth.35.The trees in the _______ provide shade in summer.36.What type of animal is a penguin?A. MammalB. BirdC. ReptileD. FishB37.What do we call the process of turning milk into cheese?A. FermentationB. CoagulationC. PasteurizationD. Homogenization38.The _______ of a plant can be green, yellow, or brown.39.My sister is learning how to ____ (swim) this summer.40.The ________ (城市发展) affects many people.41.I have a ___ (story/book) to read.42.My cat purrs when it feels _______ (放松).43.The ________ (气味) of herbs is wonderful.44. A ________ (生态平衡) ensures diversity.45.The __________ helps to create new cells in the body.46.I can ______ (唱) very well.47.The _____ (iris) blooms in various colors.48.My brother is my ________ (哥哥). We play video games together every weekend.49.The flowers are ______ in the garden.50.The ancient Greeks established many ________ (城邦).51.The ocean is _______ (闪闪发光).52.He plays _______ (video games) every weekend.53.The _______ (Silk Road) was a trade route that connected the East and West.54.Which of these is a flying mammal?A. BatB. DogC. CatD. Elephant55.What is the name of the fairy that helps Peter Pan?A. Tinker BellB. CinderellaC. BelleD. ArielA56.What do you call the process of planting seeds?A. SowingB. HarvestingC. CultivatingD. TillingA57.The part of the atom that has a negative charge is called an _______.58.What is the opposite of fat?A. ThinB. SlimC. LeanD. All of the aboveD59.I see a ___ (star/moon) shining.60.Earth has one moon, while Mars has ______.61.The cat is __________ on the sofa.62.My birthday is in ______ (七月). I want to have a big ______ (派对) with cake and ______ (气球).63.What do you call the main character in a comic book?A. HeroB. VillainC. SidekickD. Comic reliefA64.What is 15 divided by 5?A. 2B. 3C. 4D. 5B65.My grandma teaches me how to ____ (knit).66.The moon affects the ______ of the oceans.67.What is the sound of a duck?A. QuackB. MooC. WoofD. Baa68.The __________ (历史的多样性) enriches dialogue.69.What is the name of the tree that produces acorns?A. PineB. MapleC. OakD. BirchC70.We have ______ at the picnic. (sandwiches)71. A ______ is a natural feature that can influence local climates.72.What do you call a person who studies stars and planets?A. ScientistB. AstronomerC. BiologistD. GeologistB Astronomer73.The _____ (雨伞) is red.74. A turtle can hide in its ______ for protection.75. A ______ plays a key role in the habitat.76.The first successful double hand transplant was performed in _______. (2008年)77. A __________ is a narrow strip of land connecting two larger land areas. (地峡)78.What do you call a place where you can borrow books?A. SchoolB. LibraryC. ParkD. StoreB79.I want to ________ (learn) English.80.What do you call the person who helps you learn in school?A. DoctorB. TeacherC. CookD. Driver81.The ________ likes to chase after butterflies.82.I like to watch the ________ when I go outside.83.Acids taste ______ and can be sour.84.The _____ (园艺) in my backyard is my favorite place.85.The main component of antioxidants is _____.86.My dog loves to fetch a ______ (球).87.The chemical formula for acetic acid is _____.88.What is the name of the ocean on the east coast of the United States?A. AtlanticB. PacificC. IndianD. Arctic89.My sister is a ______. She likes to help others.90.The country known for kangaroos is ________ (澳大利亚).91.What is the name of the famous scientist known for his work on electromagnetism?A. James Clerk MaxwellB. Nikola TeslaC. Thomas EdisonD. Michael FaradayA92.The first successful airplane flight took place in ________.93.The movie was very ___ (interesting).94.The _____ (balloon/kite) is flying.95. A base can neutralize an ______.96.The movie was ___ (exciting/boring).97.What do you call a person who studies history?A. HistorianB. ArchaeologistC. GeographerD. Anthropologist答案:A98.The __________ (历史的持续演变) reflects societal changes.99.I think it’s important to ________ (保持积极).100.What is the name of the traditional Japanese dish made with rice and fish?A. PizzaB. SushiC. PastaD. BurgerB。
2024年人教版英语初一上学期期中模拟试卷与参考答案一、听力部分(本大题有20小题,每小题1分,共20分)1、Listen to the following dialogue and choose the best answer to complete the sentence.A. What’s your name?B. How old are you?C. Where are you from?Answer: BExplanation: In this dialogue, the first speaker is asking about the age of the second speaker. Therefore, the correct answer is “How old are you?”.2、Listen to the following passage and answer the question.Question: What is the main topic of the passage?A. The importance of exercise.B. The benefits of reading.C. The importance of eating healthy.Answer: AExplanation: The passage talks about the importance of exercise for both physical and mental health. Hence, the main topic is the importance of exercise,which makes “The importance of exercise” the correct answer.3、Listen to the conversation and choose the best answer to the question you hear.Question: What does the man suggest they do next?A) Go to the library.B) Have a picnic.C) Watch a movie.Answer: B) Have a picnic.Explanation: The man suggests they have a picnic, which is option B. The other options are not mentioned in the conversation.4、Listen to the short passage and answer the question.Question: What is the main topic of the passage?A)The benefits of reading.B)The history of the book.C)The importance of education.Answer: C) The importance of education.Explanation: Although the passage does touch on the benefits of reading and the history of the book, the main topic is the importance of education, making option C the best answer.5、You hear a conversation between two students discussing their weekend plans.Student A: “Are you going to the beach this weekend?”Student B: “Yes, I am. It’s going to be sunny and warm.”Student A: “That sounds great! Are you planning to bring anything to do there?”Student B: “I think I’ll bring some books to read. How about you?”Question: What activity does Student B plan to do at the beach?A) Go swimmingB) Read booksC) Play sportsD) Visit a friendAnswer: B) Read booksExplanation: In the conversation, Student B mentions that they think they will bring some books to read at the beach, indicating that reading is their planned activity.6、You hear a short dialogue between a teacher and a student about the upcoming science fair.Teacher: “Hi, John. Are you ready for the science fair next week?”Student: “I’m almost there, Mrs.Smith. I just need to finish my project on renewable energy sou rces.”Teacher: “That sounds interesting. Do you already have all the materials you need?”Student: “Yes, I have all the materials, but I’m still working on the experiment to test the efficiency of the solar panel.”Question: What is the student working on for the science fair?A) A paintingB) A renewable energy projectC) A history presentationD) A music performanceAnswer: B) A renewable energy projectExplanation: The student explicitly states that they are working on a project about renewable energy sources for the science fair, indicating that the correct answer is B.7、听力材料:W: Hi, John! How was your science project fair?M: It was great! I presented a model of the solar system and explained how each planet orbits the sun.Q: What did John do at the science project fair?A. He presented a model of the solar system.B. He explained the theory of relativity.C. He demonstrated a new type of rocket.D. He showed a collection of insects.Answer: AExplanation: The question asks what John did at the science project fair. In the dialogue, John says, “I presented a model of the solar system,” which directly answers the question.8、听力材料:M: Have you ever tried the new Italian restaurant downtown?W: Yes, I went there last weekend. The pasta was amazing, but the service was a bit slow.Q: What did the woman think about the service at the restaurant?A. It was very quick.B. It was satisfactory.C. It was quite slow.D. It was exceptional.Answer: CExplanation: The question inquires about the woman’s opinion of the service at the restaurant. The woman says, “the service was a bit slow,” which indicates that she found the service to be slow, thus making option C the correct answer.9.You are listening to a conversation between two students, Alex and Sarah, discussing their weekend plans.M: (9) Hi, Sarah, what are you planning to do this weekend?W: Oh, I’m thinking of going hiking with a group of friends. How about you, Alex?M: That sounds fun! I mig ht just stay home and relax. Maybe I’ll go for a walk in the park.Q: What is Alex’s plan for the weekend?A: To stay home and relax.B: To go hiking with friends.C: To go for a walk in the park.D: To go shopping with Sarah.Answer: AExplanation: In the conversation, Alex says, “Maybe I’ll go for a walk in the park,” indicating that he plans to stay home and relax.10.You are listening to a phone conversation between a teacher, Mr. Green, and a student, Lily.M: (10) Hi, Lily. How are you doing with your homework assignment?W: Hi, Mr. Green. I’m almost done. I just have one question about the math problem.M: Sure, go ahead and ask me.W: Okay, it’s about the quadratic equation. I’m not sure how to find the vertex.M: Well, Lily, to find the vertex of a quadratic equation, you need to use the formula for the x-coordinate, which is -b/2a, and then plug that value into the equation to find the y-coordinate.Q: What is Lily’s question about the math problem?A: How to solve a linear equation.B: How to find the vertex of a quadratic equation.C: How to factorize a trinomial.D: How to simplify an expression.Answer: BExplanation: Lily directly asks Mr. Green, “I’m not sure how to find the vertex,” which is related to the quadratic equation.11.You are listening to a conversation between two students, Tom and Lily, discussing their weekend plans. Listen carefully and answer the question below.Q: What are Tom and Lily planning to do this weekend?A: Tom and Lily are planning to go hiking this weekend.Answer: AExplanation: The conversation starts with Tom saying, “Hey Lily, do you want to go hiking this weekend?” and Lily replies, “Sure, that sounds like fun!” This indicates that they have planned to go hiking.12.You are listening to a weather report for a city. Listen carefully and answer the question below.Q: What is the weather forecast for tomorrow in the city?A: The weather forecast for tomorrow in the city is sunny with a high of 25 degrees Celsius.Answer: Sunny, 25°CExplanation: T he weather report states, “Tomorrow, we expect a sunny day with a high of 25 degrees Celsius.” This provides the information needed to answer the question.13.You hear a conversation between two students discussing their weekend plans.A. What did the first student plan to do on Saturday?1.Go to the movies.2.Visit a museum.3.Go hiking.Answer: 2. Visit a museum.Explanation: The first student mentions that they have a free Saturday and decides to visit the museum with a friend.14.You hear a short dialogue between a teacher and a student about a school project.A. What was the student’s initial plan for the project?1.To complete it by next week.2.To do it in groups.3.To work on it over the weekend.Answer: 3. To work on it over the weekend.Explanation: The student explains to the teacher that they had planned to work on the project over the weekend but need additional help.15.You are listening to a conversation between two students, Alex and Emily, discussing their weekend plans. Listen to the conversation and answer the question.Question: What activity does Alex plan to do on Saturday afternoon?A) Go shopping with friends.B) Attend a football game.C) Visit a museum.Answer: B) Attend a football game.Explanation: In the conversation, Al ex mentions, “I’m going to a football game with some friends on Saturday afternoon,” which indicates the correct answer is B) Attend a football game.16.Listen to a short dialogue between a teacher and a student, discussinga school project. Answer the following question.Question: What is the main topic of the project?A) Science fair experiments.B) Historical figures research.C) Environmental conservation efforts.Answer: B) Historical figures research.Explanation: The teacher says, “The project is abo ut researching a historical figure from the past,” which suggests that the main topic of the project is B) Historical figures research.17.You are listening to a conversation between two students, Tom and Alice, about their weekend plans. Listen carefully and answer the following question: What does Tom plan to do on Saturday afternoon?A. Go to the movies.B. Go shopping with Alice.C. Visit his grandparents.Answer: AExplanation: In the conversation, Tom says, “I’m going to the movies this afternoon. Do you want to come with me?” This indicates that Tom plans to goto the movies on Saturday afternoon.18.Listen to a short passage about the importance of exercise and answer the following question:What is the main idea of the passage?A. Exercise is good for physical health.B. Exercise is important for mental health.C. Exercise can help people lose weight.Answer: BExplanation: The passage discusses the positive effects of exercise on mental health, such as reducing stress and improving mood. While physical health benefits are also mentioned, the main idea of the passage focuses on the mental health aspect of exercise.19.You are listening to a conversation between two students discussing their weekend plans.St udent A: “Hey, have you thought about what you’re going to do this weekend?”Student B: “I was thinking of going hiking. How about you?”Student A: “That sounds fun! I was actually planning to visit the city museum with my family.”Student B: “Oh, that’s cool. Do you know if there’s anything special going on there?”Student A: “Yes, they have a special exhibit about ancient artifacts. It’sreally interesting.”Question: What is Student A planning to do this weekend?A) Go hikingB) Visit the city museumC) Go to the moviesD) Go shoppingAnswer: BExplanation: Student A mentions planning to visit the city museum with their family, which indicates that this is their weekend plan.20.You are listening to a weather forecast for the coming week.Narrator: “This week, we can expect a mix of sunny and cloudy days. Monday will be mostly sunny with a high of 75 degrees Fahrenheit. Tuesday will see some scattered showers in the afternoon, with a high of 68 degrees. Wednesday and Thursday will be sunny with highs in the low 70s. Friday will bring a chance of thunderstorms in the evening, with a high of 72 degrees. The weekend will be partly cloudy with a high of 68 degrees on Saturday and 70 degrees on Sunday.”Question: Which day of the week will have the highest temperature?A) MondayB) TuesdayC) WednesdayD) SundayAnswer: DExplanation: The forecast indicates that the highest temperature will be on Sunday, with a high of 70 degrees Fahrenheit.二、阅读理解(30分)Reading ComprehensionPassage:The first day of school is always an exciting and nervous time for students. Imagine walking into a new classroom, filled with unfamiliar faces and a teacher who is about to be your guide through a new language. For many students in China, this experience is multiplied when they start learning English in the first grade. English is a challenging subject for beginners, but it opens up a world of opportunities.In the first grade, students are introduced to basic English vocabulary and grammar. They learn simple words like “hello,”“goodbye,” “yes,” and “no,” as well as basic sentence structures. One of the first activities they do is to create a simple “Hello, my name is…” card, which helps them practice their new vocabulary and introduces them to the concept of proper introductions.The classroom environment is designed to be engaging and interactive. There are posters with colorful pictures and words, and there are often games and activities that reinforce the lessons. One popular game is “Simon Says,” where the teacher calls out commands beginning with the word “Simon says,” and the students only follow the commands if they are preceded by “Simon says.”Despite the excitement, the first day of English class can also be daunting. Many students are worried about making mistakes and being corrected in front of their peers. However, the teacher reassures them that learning a new language is a process, and mistakes are a natural part of that process.Questions:1.Why is the first day of school exciting for students?2.What are some of the basic words and sentence structures that first-grade students learn in English?3.How does the classroom environment help students learn English?Answers:1.The first day of school is exciting for students because they are starting a new journey, meeting new classmates, and learning a new subject.2.Some of the basic words and sentence structures that first-grade students learn in English include “hello,” “goodbye,” “yes,” “no,” and simple sentence structures like “I am…,” “My name is…,” and “This is…”.3.The classroom environment helps students learn English by being engaging and interactive, with colorful posters and games that reinforce the lessons.三、完型填空(15分)Title: Human Education Edition Grade 7 English Mid-term Exam - Part 3: Cloze TestQuestion 1:Reading the following passage, choose the best word or phrase for each blankfrom the options given below.In the small town of Greenfield, the [1] of the library was always a topic of conversation among the residents. The library was more than just a place to borrow books; it was a [2] where people of all ages could gather and share their interests.Last year, the library [3] a new program called “Community Reads.” The program encouraged everyone in the town to read the same book and then come together for discussions. It was a great success, and the library became a [4] place for the community to connect.Unfortunately, the library’s budget was cut this year, and it looked like the “Community Reads” program might [5]. Many residents were worried that the library would no longer be the heart of the community.1.A) importance B) attraction C) benefit D) opportunity2.A) meeting B) gathering C) destination D) collection3.A) introduced B) removed C) destroyed D) expanded4.A) favorite B) private C) outdated D) abandoned5.A) continue B) stop C) replace D) combineAnswer Key:1.B2.C3.A4.A5.B四、语法填空题(本大题有10小题,每小题1分,共10分)1、Tom______(go) to the movies last night, but he had too much homework.A. goesB. wentC. is goingD. will go答案:B解析:根据句意,这里描述的是昨晚的动作,所以需要使用一般过去时。
2024年教师资格考试高中英语学科知识与教学能力模拟试卷与参考答案一、单项选择题(本大题有30小题,每小题2分,共60分)1、In the following sentence, the word “that” is used as a relative pronoun. Which sentence best illustrates the use of “that” in this context?A. The book that you gave me is very interesting.B. She told me the story that she had just read.C. The students that were late were given extra homework.D. I don’t remember the name of the person that I met yesterday.答案:A解析:选项A中的”that”引导一个定语从句,修饰先行词”book”,并在从句中作宾语,省略了”which”或”whom”。
其他选项中的”that”要么引导非限制性定语从句(B选项),要么在从句中作主语或宾语,但没有省略”that”。
2、Which of the following sentences is correctly punctuated?A. The teacher said, “Let’s start the class now.”B. She asked, “Where are you going?”C. He replied: “I’m going to the library.”D. The student: “I have finished my homework.” The teacher: “Good job!”答案:B解析:选项B中的句子正确地使用了问号,因为它是直接引语,而直接引语中的句子如果是疑问句,则必须以问号结尾。
中国科学院遗传研究所硕士学位研究生1991年入学考试普通遗传学试题一、名词解释(20分)剂量补偿作用组成性突变性选择压力渐渗杂交转染 F因子回文环异源多倍体反义核酸克隆(无性繁殖系)选择学说二、选择题(10分)1、某人是一个常染色体基因的杂合子Bb,而他带有一个隐性的X连锁基因d。
在他的精子中有多大比例带有bd基因。
(a)0;(b)1/2;(c)1/8;(d)1/16;(e)1/4。
2、有图谱系中,涂黑者为带有性状的W个体,这种性状在群体中是罕见的。
如下哪种情况是于谱系中的传递情况一致的?●□●□□●■○●●●●■○(a)常染色体隐性;(b)常染色体显性;(c)X连锁隐性;(d)X连锁显性;(e)Y连锁。
3、在一个突变过程中,一对额外的核苷酸插入DNA内,会得什么样的结果?(a)完全没有蛋白产物;(b)产生的蛋白中有一个氨基酸发生变化。
(c)产生的蛋白中有三个氨基酸发生变化。
(d)产生的蛋白中有一个氨基酸发生变化。
(e)产生的蛋白中,插入部位以后的大部分氨基酸都发生变化。
4、假设某种二倍体植物的细胞质在遗传上不同于植物B。
为了研究核-质关系,想获得一种植株,这种植株具有A的细胞质,而细胞核却主要是B的基因组,应该怎样做?(a)A×B的后代连续自交(b)B×A的后代连续自交(c) A×B的后代连续与B回交(d) A×B的后代连续与A回交(e) B×A的后代连续与B回交;(f)B×A的后代连续与A回交。
三、问答题:1、某城市医院的94,075个新生儿中,有10个是软骨发育不全的侏儒(软骨发育不全是一种充分表现的常染色体显性突变),其中只有2个侏儒的父亲或母亲是侏儒。
试问在配子中来自软骨发育不全的突变频率是多少?(10分)2、某种介壳虫的二倍体数为10,在雄性细胞中,5个染色体总是呈异染色质状态,另外5个染色体呈常染色质状态。
而在雌细胞中,所有10个染色体都是常染色体的。
英语作文字典的应用英语作文,英语字典的应用。
Introduction:An English dictionary is an essential tool for English language learners. It provides definitions, explanations, and examples of words, helping learners to expand their vocabulary and improve their language skills. This essay will discuss the importance of English dictionaries and how they are used in different ways.The Importance of English Dictionaries:English dictionaries play a crucial role in language learning. They help learners to understand the meaning and usage of words, enabling them to communicate effectively in English. Dictionaries also provide information on word forms, pronunciation, synonyms, antonyms, and idiomatic expressions, facilitating learners' comprehension and usageof the language. Moreover, dictionaries can enhancelearners' reading skills as they encounter unfamiliar words while reading. By using a dictionary, learners can decipher the meaning of these words and broaden their understandingof the text.Types of English Dictionaries:There are various types of English dictionaries available, catering to different needs and proficiency levels. The most common types include learner's dictionaries, bilingual dictionaries, and specialized dictionaries. Learner's dictionaries are designedspecifically for language learners, providing simplified definitions, examples, and explanations. Bilingual dictionaries, on the other hand, offer translations ofwords from one language to another, assisting learners in understanding words in their native language. Specialized dictionaries focus on specific fields such as medicine, law, or technology, providing in-depth explanations of technical terms.Using English Dictionaries:English dictionaries can be used in different ways depending on the purpose and context. Here are some common ways dictionaries are utilized:1. Vocabulary Expansion: Learners can use dictionaries to look up new words they encounter while reading or listening. By understanding the meaning and usage of these words, learners can expand their vocabulary and improve their language skills.2. Word Pronunciation: Dictionaries provide phonetic transcriptions and audio pronunciations, helping learners to pronounce words correctly. This is particularly useful for non-native English speakers who may struggle with English phonetics.3. Word Forms: Dictionaries provide information on word forms such as verb conjugations, noun plurals, andadjective comparisons. This helps learners to understand how words change in different contexts and grammaticalstructures.4. Synonyms and Antonyms: Dictionaries offer synonyms and antonyms for words, enabling learners to enhance their vocabulary by exploring alternative words with similar or opposite meanings.5. Idiomatic Expressions: Dictionaries provide explanations and examples of idiomatic expressions, helping learners to understand and use these phrases in appropriate contexts.Conclusion:In conclusion, English dictionaries are indispensable tools for language learners. They provide definitions, explanations, and examples of words, helping learners to expand their vocabulary, improve their language skills, and enhance their overall understanding of the English language. By utilizing dictionaries effectively, learners can overcome language barriers and communicate more confidently and accurately in English.。
Automatic Meaning Discovery Using GoogleRudi Cilibrasi∗CWIPaul Vitanyi†CWI,University of Amsterdam, AbstractWe present a new theory of relative semantics between objects,based on information distance and Kolmogorov complexity.This theory is then applied to construct a method to automaticallyextract the meaning of words and phrases from the world-wide-web using Google page counts.The approach is novel in its unrestricted problem domain,simplicity of implementation,andmanifestly ontological underpinnings.The world-wide-web is the largest database on earth,andthe latent semantic context information entered by millions of independent users averages out toprovide automatic meaning of useful quality.We give examples to distinguish between colors andnumbers,cluster names of paintings by17th century Dutch masters and names of books by Englishnovelists,the ability to understand emergencies,and primes,and we demonstrate the ability to do asimple automatic English-Spanish translation.Finally,we use the WordNet database as an objectivebaseline against which to judge the performance of our method.We conduct a massive randomizedtrial in binary classification using support vector machines to learn categories based on our Googledistance,resulting in an a mean agreement of87%with the expert crafted WordNet categories.1IntroductionObjects can be given literally,like the literal four-letter genome of a mouse,or the literal text of War and Peace by Tolstoy.For simplicity we take it that all meaning of the object is represented by the literal object itself.Objects can also be given by name,like“the four-letter genome of a mouse,”or“the text of War and Peace by Tolstoy.”There are also objects that cannot be given literally,but only by name, and that acquire their meaning from their contexts in background common knowledge in humankind, like“home”or“red.”To make computers more intelligent one would like to represent meaning in computer-digestable form.Long-term and labor-intensive efforts like the Cyc project[19]and the WordNet project[30]try to establish semantic relations between common objects,or,more precisely, names for those objects.The idea is to create a semantic web of such vast proportions that rudimentary intelligence,and knowledge about the real world,spontaneously emerge.This comes at the great cost of designing structures capable of manipulating knowledge,and entering high quality contents in these structures by knowledgeable human experts.While the efforts are long-running and large scale,the overall information entered is minute compared to what is available on the world-wide-web.The rise of the world-wide-web has enticed millions of users to type in trillions of characters to create billions of web pages of on average low quality contents.The sheer mass of the information∗Supported in part by the Netherlands BSIK/BRICKS project,and by NWO project612.55.002.Address:CWI,Kruislaan413,1098SJ Amsterdam, The Netherlands.Email:Rudi.Cilibrasi@cwi.nl.†Part of this work was done while the author was on sabbatical leave at National ICT of Australia,Sydney Laboratory at UNSW.Supported in part by the EU EU Project RESQ IST-2001-37559,the ESF QiT Programmme,the EU NoE PASCAL,and the Netherlands BSIK/BRICKS project.Address: CWI,Kruislaan413,1098SJ Amsterdam,The Netherlands.Email:Paul.Vitanyi@cwi.nl.1Dagstuhl Seminar Proceedings 06051Kolmogorov Complexity and Applicationshttp://drops.dagstuhl.de/opus/volltexte/2006/629available about almost every conceivable topic makes it likely that extremes will cancel and the majority or average is meaningful in a low-quality approximate sense.We devise a general method to tap the amorphous low-grade knowledge available for free on the world-wide-web,typed in by local users aiming at personal gratification of diverse objectives,and yet globally achieving what is effectively the largest semantic electronic database in the world.Moreover,this database is available for all by using any search engine that can return aggregate page-count estimates for a large range of search-queries, like Google.Previously,we and others developed a compression-based method to establish a universal similarity metric among objects given asfinite binary strings[2,22,23,7,8],which was widely reported [17,18,12].Such objects can be genomes,music pieces in MIDI format,computer programs in Ruby or C,pictures in simple bitmap formats,or time sequences such as heart rhythm data.This method is feature-free in the sense that it doesn’t analyze thefiles looking for particular features;rather it analyzes all features simultaneously and determines the similarity between every pair of objects according to the most dominant shared feature.The crucial point is that the method analyzes the objects themselves.This precludes comparison of abstract notions or other objects that don’t lend themselves to direct analysis,like emotions,colors,Socrates,Plato,Mike Bonanno and Albert Einstein.While the previous method that compares the objects themselves is particularly suited to obtain knowledge about the similarity of objects themselves,irrespective of common beliefs about such similarities,here we develop a method that uses only the name of an object and obtains knowledge about the similarity of objects by tapping available information generated by multitudes of web users.Here we are reminded of the words of D.H.Rumsfeld[28]“A trained ape can know an awful lot/Of what is going on in this world/Just by punching on his mouse/For a relatively modest cost!”1.1An Example:While the theory we propose is rather intricate,the resulting method is simple enough.We give an example:At the time of doing the experiment,a Google search for“horse”, returned46,700,000hits.The number of hits for the search term“rider”was12,200,000.Searching for the pages where both“horse”and“rider”occur gave2,630,000hits,and Google indexed8,058,044,651 web ing these numbers in the main formula(3.6)we derive below,with N=8,058,044,651, this yields a Normalized Google Distance between the terms“horse”and“rider”as follows:NGD(horse,rider)≈0.443.In the sequel of the paper we argue that the NGD is a normed semantic distance between the terms in question,usually in between0(identical)and1(unrelated),in the cognitive space invoked by the usage of the terms on the world-wide-web asfiltered by Google.Because of the vastness and diversity of the web this may be taken as related to the current objective meaning of the terms in society.We did the same calculation when Google indexed only one-half of the current number of pages:4,285,199,774.It is instructive that the probabilities of the used search terms didn’t change significantly over this doubling of pages,with number of hits for“horse”equal23,700,000,for“rider”equal6,270,000,and for“horse, rider”equal to1,180,000.The NGD(horse,rider)we computed in that situation was≈0.460.This is in line with our contention that the relative frequencies of web pages containing search terms gives objective information about the semantic relations between the search terms.If this is the case,then the Google probabilities of search terms and the computed NGD’s should stabilize(become scale invariant)with a growing Google database.21.2Related Work:There is a great deal of work in both cognitive psychology[34],linguistics,and computer science,about using word(phrases)frequencies in text corpora to develop measures for word similarity or word association,partially surveyed in[31,33],going back to at least[32].One of the most successful is Latent Semantic Analysis(LSA)[34]that has been applied in various forms in a great number of applications.We discuss LSA and its relation to the present approach in Appendix A. As with LSA,many other previous approaches of extracting meaning from text documents are based on text corpora that are many order of magnitudes smaller,and that are in local storage,and on assumptions that are more refined,than what we propose.In contrast,[10,1]and the many references cited there, use the web and Google counts to identify lexico-syntactic patterns or other data.Again,the theory, aim,feature analysis,and execution are different from ours,and cannot meaningfully be compared. Essentially,our method below automatically extracts meaning relations between arbitrary objects from the web in a manner that is feature-free,up to the search-engine used,and computationally feasible. This seems to be a new direction altogether.1.3Outline of This Work:The main thrust is to develop a new theory of semantic distance betweena pair of objects,based on(and unavoidably biased by)a background contents consisting of a database of documents.An example of the latter is the set of pages constituting the world-wide-web.Semantics relations between pairs of objects is distilled from the documents by just using the number of documents in which the objects occur,singly and jointly(irrespective of location or multiplicity).The theoretical underpinning is based on the theory of Kolmogorov complexity[24],and expressed as coding and compression.This allows to express and prove properties of absolute relations between objects that cannot even be expressed by other approaches.The theory,application,and the particular NGD formula to express the bilateral semantic relations are(as far as we know)not equivalent to any earlier theory,application,and formula in this area.The current paper is a next step in a decade of cumulative research in this area,of which the main thread is[24,2,25,23,7,8]with[22,3]using the related approach of[26].Wefirst start with a technical introduction outlining some notions underpinning our approach:Kolmogorov complexity,information distance,and compression-based similarity metric (Section2).Then we give a technical description of the Google distribution,the Normalized Google Distance,and the universality of these notions(Section3).While it may be possible in principle that other methods can use the entire world-wide-web to determine relative meaning between terms,we do not know of a method that both uses the entire web,or computationally can use the entire web, and(or)has the same aims as our method.To validate our method we therefore cannot compare its performance to other existing methods.Ours is a new proposal for a new task.We validate the method in the following way:by theoretical analysis,by anecdotical evidence in a plethora of applications, and by systematic and massive comparison of accuracy in a classification application compared to the uncontroversial body of knowledge in the WordNet database.In Section3we give the theoretic underpinning of the method and prove its universality.In Section4we present a plethora of clustering and classification experiments to validate the universality,robustness,and accuracy of our proposal.In Section5we test repetitive automatic performance against uncontroversial semantic knowledge:We present the results of a massive randomized classification trial we conducted to gauge the accuracy of our method to the expert knowledge as implemented over the decades in the WordNet database.The actual experimental data can be downloaded from[5].The method is implemented as an easy-to-use software tool available on the web[6],available to all.31.4Materials and Methods:The application of the theory we develop is a method that is justified by the vastness of the world-wide-web,the assumption that the mass of information is so diverse that the frequencies of pages returned by Google queries averages the semantic information in such a way that one can distill a valid semantic distance between the query subjects.It appears to be the only method that starts from scratch,is feature-free in that it uses just the web and a search engine to supply contents, and automatically generates relative semantics between words and phrases.A possible drawback of our method is that it relies on the accuracy of the returned counts.It is well-known,see[1],that the returned google counts are inaccurate,and especially if one uses the boolean OR operator between search terms. For example,a search for“horse”returns106million hits,“rider”30.1million hits,but“horse OR rider”116million hits,respectively,violating set theory.(These numbers held at the time of writing this sentence.Above,we used an example with the same search terms but with numbers based on Google searches of the year before.)The AND operator we use is less problematic,and we do not use the OR operator.Furthermore,Google apparently estimates the number of hits based on samples,and the number of indexed pages changes rapidly.To compensate for the latter effect,we have inserted a normalizing mechanism in the CompLearn software.Linguists judge the accuracy of Google counts trustworthy enough:In[20](see also the many references to related research)it is shown that web searches for rare two-word phrases correlated well with the frequency found in traditional corpora,as well as with human judgments of whether those phrases were natural.Thus,Google is the simplest means to get the most information.Note,however,that a single Google query takes a fraction of a second,and that Google restricts every IP address to a maximum of(currently)500queries per day—although they are cooperative enough to extend this quotum for noncommercial purposes.The experimental evidence provided here shows that the combination of Google and our method yields reasonable results,gauged against common sense(‘colors’are different from‘numbers’)and against the expert knowledge in the WordNet data base.A reviewer suggested downscaling our method by testing it on smaller text corpora.This does not seem useful.Clearly perfomance will deteriorate with decreasing data base size.A thought experiment using the extreme case of a single web page consisting of a single term suffices.Practically addressing this issue is begging the question.Instead,in Section3 we theoretically analyze the relative semantics of search terms established using all of the web,and its universality with respect to the relative semantics of search terms using subsets of web pages.2Technical PreliminariesThe basis of much of the theory explored in this paper is Kolmogorov complexity.For an introduction and details see the textbook[24].Here we give some intuition and notation.We assume afixed reference universal programming system.Such a system may be a general computer language like LISP or Ruby,and it may also be afixed reference universal Turing machine in a given standard enumeration of Turing machines.The latter choice has the advantage of being formally simple and hence easy to theoretically manipulate.But the choice makes no difference in principle,and the theory is invariant under changes among the universal programming systems,provided we stick to a particular choice. We only consider universal programming systems such that the associated set of programs is a prefix code—as is the case in all standard computer languages.The Kolmogorov complexity of a string x is the length,in bits,of the shortest computer program of thefixed reference computing system that produces x as output.The choice of computing system changes the value of K(x)by at most an additivefixed constant.Since K(x)goes to infinity with x,this additivefixed constant is an ignorable quantity if we consider large x.4One way to think about the Kolmogorov complexity K(x)is to view it as the length,in bits,of the ultimate compressed version from which x can be recovered by a general decompression program. Compressing x using the compressor gzip results in afile x g with(forfiles that contain redundancies)the length|x g|<|x|.Using a better compressor bzip2results in afile x b with(for redundantfiles)usually |x b|<|x g|;using a still better compressor like PPMZ results in afile x p with(for again appropriately redundantfiles)|x p|<|x b|.The Kolmogorov complexity K(x)gives a lower bound on the ultimate value:for every existing compressor,or compressors that are possible but not known,we have that K(x) is less or equal to the length of the compressed version of x.That is,K(x)gives us the ultimate value of the length of a compressed version of x(more precisely,from which version x can be reconstructed by a general purpose decompresser),and our task in designing better and better compressors is to approach this lower bound as closely as possible.2.1Normalized Information Distance:In[2]we considered the following notion:given two strings x and y,what is the length of the shortest binary program in the reference universal computing system such that the program computes output y from input x,and also output x from input y.This is called the information distance and denoted as E(x,y).It turns out that,up to a negligible logarithmic additive term,E(x,y)=K(x,y)−min{K(x),K(y)}.This distance E(x,y)is actually a metric:up to close precision we have E(x,x)=0,E(x,y)>0for x=y,E(x,y)=E(y,x)and E(x,y)≤E(x,z)+E(z,y),for all x,y,z.We now consider a large class of admissible distances:all distances(not necessarily metric)that are nonnegative,symmetric,and computable in the sense that for every such distance D there is a prefix program that,given two strings x and y,has binary length equal to the distance D(x,y)between x and y.Then,E(x,y)≤D(x,y)+c D,(2.1) where c D is a constant that depends only on D but not on x,y,and we say that E(x,y)minorizes D(x,y) up to an additive constant.We call the information distance E universal for the family of computable distances,since the former minorizes every member of the latter family up to an additive constant.If two strings x and y are close according to some computable distance D,then they are at least as close according to distance E.Since every feature in which we can compare two strings can be quantified in terms of a distance,and every distance can be viewed as expressing a quantification of how much of a particular feature the strings have in common(the feature being quantified by that distance),the information distance determines the distance between two strings according to the dominant feature in which they are similar.This means that,if we consider more than two strings,every pair may have a different dominant feature.If small strings differ by an information distance which is large compared to their sizes,then the strings are very different.However,if two very large strings differ by the same (now relatively small)information distance,then they are very similar.Therefore,the information distance itself is not suitable to express true similarity.For that we must define a relative information distance:we need to normalize the information distance.Such an approach wasfirst proposed in [22]in the context of genomics-based phylogeny,and improved in[23]to the one we use here.The normalized information distance(NID)has values between0and1,and it inherits the universality of the information distance in the sense that it minorizes,up to a vanishing additive term,every other possible normalized computable distance(suitably defined).In the same way as before we can identify the computable normalized distances with computable similarities according to some features,and the5NID discovers for every pair of strings the feature in which they are most similar,and expresses that similarity on a scale from0to1(0being the same and1being completely different in the sense of sharing no features).Considering a set of strings,the feature in which two strings are most similar may be a different one for different pairs of strings.The NID is defined byNID(x,y)=K(x,y)−min(K(x),K(y))max(K(x),K(y)).(2.2)It has several wonderful properties that justify its description as the most informative metric[23].2.2Normalized Compression Distance:The NID is uncomputable since the Kolmogorov complex-ity is uncomputable.But we can use real data compression programs to approximate the Kolmogorov complexities K(x),K(y),K(x,y).A compression algorithm defines a computable function from strings to the lengths of the compressed versions of those strings.Therefore,the number of bits of the com-pressed version of a string is an upper bound on Kolmogorov complexity of that string,up to an additive constant depending on the compressor but not on the string in question.Thus,if C is a compressor and we use C(x)to denote the length of the compressed version of a string x,then we arrive at the Normal-ized Compression Distance:NCD(x,y)=C(xy)−min(C(x),C(y))max(C(x),C(y)),(2.3)where for convenience we have replaced the pair(x,y)in the formula by the concatenation xy.This transition raises several tricky problems,for example how the NCD approximates the NID if C approximates K,see[8],which do not need to concern us here.Thus,the NCD is actually a family of compression functions parameterized by the given data compressor C.The NID is the limiting case, where K(x)denotes the number of bits in the shortest code for x from which x can be decompressed by a general purpose computable decompressor.3Theory of Googling for MeaningEvery text corpus or particular user combined with a frequency extractor defines its own relative frequencies of words and pharses usage.In the world-wide-web and Google setting there are millions of users and text corpora,each with its own distribution.In the sequel,we show(and prove)that the Google distribution is universal for all the individual web users distributions.The number of web pages currently indexed by Google is approaching1010.Every common search term occurs in millions of web pages.This number is so vast,and the number of web authors generating web pages is so enormous(and can be assumed to be a truly representative very large sample from humankind),that the probabilities of Google search terms,conceived as the frequencies of page counts returned by Google divided by the number of pages indexed by Google,approximate the actual relative frequencies of those search terms as actually used in society.Based on this premiss,the theory we develop in this paper states that the relations represented by the Normalized Google Distance(3.6)approximately capture the assumed true semantic relations governing the search terms.The NGD formula(3.6)only uses the probabilities of search terms extracted from the text corpus in question.We use the world-wide-web and Google,but the same method may be used with other text corpora like the King James version of the Bible or the Oxford English Dictionary and frequency count extractors,or the world-wide-web again and Yahoo as frequency count extractor.In these cases one obtains a text corpus and frequency extractor biased6semantics of the search terms.To obtain the true relative frequencies of words and phrases in society is a major problem in applied linguistic research.This requires analyzing representative random samples of sufficient sizes.The question of how to sample randomly and representatively is a continuous source of debate.Our contention that the web is such a large and diverse text corpus,and Google such an able extractor,that the relative page counts approximate the true societal word-and phrases usage,starts to be supported by current real linguistics research [35,20].3.1The Google Distribution:Let the set of singleton Google search terms be denoted by S .In the sequel we use both singleton search terms and doubleton search terms {{x ,y }:x ,y ∈S }.Let the set of web pages indexed (possible of being returned)by Google be Ω.The cardinality of Ωis denoted by M =|Ω|,and at the time of this writing 8·109≤M ≤9·109(and presumably greater by the time of reading this).Assume that a priori all web pages are equi-probable,with the probability of being returned by Google being 1/M .A subset of Ωis called an event .Every search term x usable by Google defines a singleton Google event x ⊆Ωof web pages that contain an occurrence of x and are returned by Google if we do a search for x .Let L :Ω→[0,1]be the uniform mass probability function.The probability of such an event x is L (x )=|x |/M .Similarly,the doubleton Google event x T y ⊆Ωis the set of web pages returned by Google if we do a search for pages containing both search term x and search term y .The probability of this event is L (x T y )=|x T y |/M .We can also define the other Boolean combinations:¬x =Ω\x and x S y =¬(¬x T ¬y ),each such event having a probability equal to its cardinality divided by M .If e is an event obtained from the basic events x ,y ,...,corresponding to basic search terms x ,y ,...,by finitely many applications of the Boolean operations,then the probability L (e )=|e |/M .Google events capture in a particular sense all background knowledge about the search terms concerned available (to Google)on the web.The Google event x ,consisting of the set of all web pages containing one or more occurrences of the search term x ,thus embodies,in every possible sense,all direct context in which x occurs on the web.R EMARK 1.It is of course possible that parts of this direct contextual material link to other web pages in which x does not occur and thereby supply additional context.In our approach this indirect context is ignored.Nonetheless,indirect context may be important and future refinements of the method may take it into account.♦The event x consists of all possible direct knowledge on the web regarding x .Therefore,it is natural to consider code words for those events as coding this background knowledge.However,we cannot use the probability of the events directly to determine a prefix code,or,rather the underlying information content implied by the probability.The reason is that the events overlap and hence the summed probability exceeds 1.By the Kraft inequality [11]this prevents a corresponding set of code-word lengths.The solution is to normalize:We use the probability of the Google events to define a probability mass function over the set {{x ,y }:x ,y ∈S }of Google search terms,both singleton and doubleton terms.There are |S |singleton terms,and |S|2 doubletons consisting of a pair of non-identical terms.Define N =∑{x ,y }⊆S|x \y |,counting each singleton set and each doubleton set (by definition unordered)once in the summation.Note that this means that for every pair {x ,y }⊆S ,with x =y ,the web pages z ∈x T y are counted three times:once in x =x T x ,once in y =y T y ,and once in x T y .Since every web page that is indexed7by Google contains at least one occurrence of a search term,we have N≥M.On the other hand,web pages contain on average not more than a certain constantαsearch terms.Therefore,N≤αM.Defineg(x)=g(x,x),g(x,y)=L(x \y)M/N=|x\y|/N.(3.4)Then,∑{x,y}⊆S g(x,y)=1.This g-distribution changes over time,and between different samplings from the distribution.But let us imagine that g holds in the sense of an instantaneous snapshot.The real situation will be an approximation of this.Given the Google machinery,these are absolute probabilities which allow us to define the associated prefix code-word lengths(information contents)for both the singletons and the doubletons.The Google code G is defined byG(x)=G(x,x),G(x,y)=log1/g(x,y).(3.5) In contrast to strings x where the complexity C(x)represents the length of the compressed version of x using compressor C,for a search term x(just the name for an object rather than the object itself),the Google code of length G(x)represents the shortest expected prefix-code word length of the associated Google event x.The expectation is taken over the Google distribution p.In this sense we can use the Google distribution as a compressor for Google“meaning”associated with the search terms.The associated NCD,now called the normalized Google distance(NGD)is then defined by(3.6),and can be rewritten as the right-hand expression:NGD(x,y)=G(x,y)−min(G(x),G(y))max(G(x),G(y))=max{log f(x),log f(y)}−log f(x,y)log N−min{log f(x),log f(y)},(3.6)where f(x)denotes the number of pages containing x,and f(x,y)denotes the number of pages containing both x and y,as reported by Google.This NGD is an approximation to the NID of(2.2) using the prefix code-word lengths(Google code)generated by the Google distribution as defining a compressor approximating the length of the Kolmogorov code,using the background knowledge on the web as viewed by Google as conditional information.In practice,use the page counts returned by Google for the frequencies,and we have to choose N.From the right-hand side term in(3.6)it is apparent that by increasing N we decrease the NGD,everything gets closer together,and by decreasing N we increase the NGD,everything gets further apart.Our experiments suggest that every reasonable (M or a value greater than any f(x))value can be used as normalizing factor N,and our results seem in general insensitive to this choice.In our software,this parameter N can be adjusted as appropriate, and we often use M for N.The following are the main properties of the NGD(as long as we choose parameter N≥M):1.The range of the NGD is in between0and∞(sometimes slightly negative if the Google countsare untrustworthy and state f(x,y)>min{f(x),f(y)},See Section1.4);(a)If x=y or if x=y but frequency f(x)=f(y)=f(x,y)>0,then NGD(x,y)=0.That is,the semantics of x and y in the Google sense is the same.(b)If frequency f(x)=0,then for every search term y we have f(x,y)=0,and the NGD(x,y)=log f(y)/log(N/f(y)).2.The NGD is always nonnegative and NGD(x,x)=0for every x.For every pair x,y wehave NGD(x,y)=NGD(y,x):it is symmetric.However,the NGD is not a metric:it does8。