Guide Si todo fuera fácil (Spanish Edition)

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From Wikipedia, the free encyclopedia. Puerto Rico portal. Accessed October 18, Archived from the original on Retrieved CS1 maint: Archived copy as title link. Authority control MusicBrainz : eefb4fe. Bring up a chair for me, please. He approached the door. Whoever guesses the number wins.

He couldn't find the house. He hit the bull's-eye. These oranges are very sour. That suit you bought's a good choice. He was elected by acclamation. This matter must be clarified. It seems to be clearing up. It's a well-to-do family. Put the suitcases carefully on the rack. She adapts herself to circumstances. Make yourselves comfortable, for we have plenty of time. They agreed to it unanimously. Do you remember this? Would you please shorten the jacket.

It's time to put the children to bed. He became sick and they laid him on a bench. He goes to bed early but it takes him a long time to get to sleep. He was lying on the couch. He's an accredited representative of the French government. He's a doctor of good reputation. It's a solvent firm. His creditors are after him. There's been a lot of activity around the office this morning. In addition to his regular job, he has a lot of other activities. It was an act of courage. The ceremony took place in the afternoon.

The third act is about to begin. He did it right away. Present circumstances are unfavorable.

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Nowadays coffee is scarce. At the present time he's in Chicago. They rushed to his aid. He didn't keep his appointment. They came to an agreement. We're of the same opinion. I did it according to your instructions. They accused him of manslaughter. We acknowledge receipt of your letter.

Exercise: Modo Subjuntivo / Subjunctive mood

You have to pay in advance in that hotel. This boy surpasses the rest of the class. They went ahead of all the others. They were doing eighty kilometers and they passed us. Your watch gains time. Put your watch ahead; it's slow. My watch is five minutes fast. His Spanish is improving little by little. I wanted to invite you, but your friend beat me to it. Go ahead. From now on we'll do it this way. You'll understand it later on. Farther on we came upon a house. Come in! This house has all the latest improvements. I don't want to go, and besides it's too late.

Besides fruit we're going to have ice cream. I'm going inside. I'll bet you can't guess what happened to me today. I'm amazed at his nerve. He admired his friend's work. They were amazed at his courage. He was admitted to the engineering school. Tips not accepted. He doesn't allow interruptions. You can't go where I'm going.

Where are you going? They adopted a little girl. They've adopted a new plan. He assumed an air of great importance. The room's nicely fixed up for the party. The dress was trimmed with lace. They paid customs duties. I noticed some mistakes in his report. I'm warning you not to do it again. I told you so. He has regard for all his office companions. I'm a great baseball fan. This is an amateur company. He's very fond of reading. He's become fond of sports. He's one of my in-laws.

The loss of their mother grieved them very much. They grieved over their friend's misfortune. Loosen the bandage a little. Don't slacken in your work in war time. The storm let up. Let's go out. They live in the suburbs. Get out! Bend down; the ceiling's very low. Hold the rope tight. I caught an awful cold. She caught hold of my arm so she wouldn't fall. He's agent for a big insurance company. The company's sent several representatives to discuss the matter. Ask the policeman where St.

James Square is. He's quick in his movements. She has a very quick mind. Shake well before using. The politician stirred up the workers. When she heard it she got very excited. They ran through the inheritance. He's wearing himself out working so much. The edition went out of print quickly. The provisions gave out in a short time. I appreciate your kindness. I thanked him very much for his help. They're going to enlarge their store. This makes the situation worse. The patient got worse. We saw the military attache of the American Embassy.

You have to add more details to the report. He wants a glass of cold water. We're having a rainy spell. You're right, that's as clear as crystal. Man overboard! Last night's storm washed out the road. You have butterfingers.


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Don't be a wet blanket. It's amazing how much he can stand. This is unbearable. Hang on tight! You have to take it. We expect him tomorrow at ten o'clock. I've been waiting for you for hours. The knife had a very sharp point. He's a very clever boy. She has a very high-pitched voice. He's always making such witty remarks! The two streets form an acute angle.

What would you like after dinner — coffee, tea, or mint water? Do you have a needle to sew on these buttons? One of the hands has fallen off my watch. The train's passed the switch.

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Sharpen the end of the stick a little. He pricked up his ears. There's your friend. What have you got there in your pocket? That way, please. Your hat's somewhere around here. Hello there, what's new? He tried to choke him. Many animals were drowned in the flood. This room's so small and hot that I'm suffocating.

I'm going home now. Now, what do you think? Now then, let's get this problem cleared up. Do it right away. He just left. We'll do it this way from now on. Up to now we've never had this problem. We have enough food for the present. They hanged him the same day. We're going to see him right now.

How much have we saved this month? The air in this room's very stuffy. There's a very strong wind blowing. He looks like a millionaire. He looked very tired. We spent three hours in the open air. Se da aires de persona importante. He puts on airs. Don't meddle in other people's affairs. He started swearing. You have to tighten those screws. This cover doesn't fit. They met to decide peace terms.

Phrase-based SMT

Let's settle accounts. He lifted the trunk to show off his strength. The sleeves of this coat have to be lengthened. Would you hand me the suitcase, please? The children are making a lot of noise. He's always short of money. They caught up with us quickly. I can't reach that can of tomatoes. He reached the rank of general. From here I can't see it. The flowers will brighten up the table. I'm very glad to see you. Why are you so happy today? They're very cheerful people. What a bright-colored suit that is!

He's a little tipsy. He showed great joy when he saw him.


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He was ill, but today he's all right. She needs a little cheering up. Encourage him to do it. Have you something to tell me? It seems rather expensive to me. Have you got some money? You must have a reason for telling me. I don't know whether this'll be of any use to you. Somebody's knocking at the door. Has anybody come? I hope you'll come again some day. I want to ask you some questions. Do you want to ask me any questions? Do you need anything else? He visits us now and then. Some people have no patience. He was out of breath when he got here. Es una persona de muchos alientos.

He's a very energetic person. We have to lighten the load. Hurry up, it's late. This food's not nourishing enough. He enlisted in the Foreign Legion. We'd better get ready early because the train won't wait. There it is! He's up there waiting for you. Your friends are in there. Let's go that way. The village is beyond those trees. I saw 'em over there a while ago. Put it over there. His house is there on the right. She lives far from there. From there one could see perfectly.

He says we should go that way. It's a town of people. My dear child! Lo siento en el alma. I'm terribly sorry. Lo voy a consultar con la almohada. I'm going to sleep on it i. They rented a house. Rooms for rent.


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  5. They were sitting around the table. It cost about thirty pesos. We have to make some changes in our plans. He showed signs of great emotion. There were disorders all over the country. His coming changed our lives completely. Don't get excited; it's nothing. What's that very tall building? He talked to a high official of the Treasury Department. Prices are very high in this store. Don't talk so loud. He returned very late at night. They live in the upper story of that house. The house is on top of the hill.

    We've overlooked many important facts. We stopped along the way to have lunch. The soldiers halted at the entrance to the town. I don't feel well at such a high altitude. The lighting's poor in this part of the city. The street lamps don't give enough light. Can you light the way? He didn't raise his eyes from the book. They revolted against the government. He stole the money. In the summer it dawns earlier than in the winter. That guy's very embittered. He makes life miserable for everyone around him. He couldn't stand the bitterness of the coffee.

    His misfortunes caused him great bitterness. They soon became friends. He made friends with John. He got acquainted there in a short time. We talked with the owner of the house. Don't tell the boss. He likes to talk of love. He's found a new love. Yes, darling. He has too much pride. He was peeved by what you said. I want an enlargement of this photograph.

    They furnished the house very luxuriously. Do you think the road's wide enough for cars? This suit's too big for me. What's the width of the material? We took a long hike up to the summit. You're a great gadabout, my boy. It's too far to walk. The train began to move. Is that clock going? I've been chasing around all day. He didn't win the prize, but he came close to it.

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    The child's going on seven. Move on! Go on! The jockey fell right by the rail. The liveliness of the gathering surprised me. Don't be a jackass! Let's encourage the players. His arrival pepped up the party. I'm urging him to come with us. He was in good spirits. She cheered him up because he was depressed. It gets dark at five now.

    I'm anxious to meet her. The year before last we went to Europe. I told you that before. This street used to have another name. Let's eat before we go.

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    They left before we arrived. Above all, don't forget to write me. He lent me 30 pesos. They advanced the date of the party. They arrived half an hour early. He got ahead of me. She likes to dress in an old-fashioned way. She does whatever comes into her mind. Lo hago porque se me antoja. I do it because I take a notion to.

    Happy New Year. I'm twenty years old. Put out the light. The lights went out. He was surprised by the sudden appearance of his friend. That's a separate question. Put this package aside. Don't get off while the vehicle's in motion. They were grieved by the illness of their aunt. We were worried because we weren't getting any news. He can hardly walk.

    Let me know as soon as he comes. He got very depressed after his failure. They crushed all resistance. They flattened his nose. They flattened themselves against the wall. He's very studious. They put a coat of paint on the chair. How much do you bet? I bet I get there before you. Rest your foot on that step. No one supported his motion. I second the motion. He's leaning on a cane. I have great respect for him.

    I may like it or not, I might have done the whole thing quite differently, but if the translation is correct, I leave it as it is. Some time ago, I was asked to bid for the translation into Spanish of some mutual fund reports. I had to translate a sample text, which was short but full of twists and turns. I submitted the translated sample rather dubiously… but they happily gave us the job. Javier and I worked together for the following month.

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    Every time I finished two or three of the reports, I forwarded them to him. In the course of the month, I learnt a lot about that specific terminology and, by the end of it, Javier just had to make minor adjustments to my texts. We would discuss, argue and even quarrel, but finally came to agreements.

    It was kind of stressing, but everything went just fine. In short, the relationship between translator and reviewer should be based on trust, friendship and genuine teamwork. Translation inaccuracies, failure to figure out ambiguities and to understand context in creative language, inability to successfully communicate nuances of meaning, and lack of cultural awareness are not the only cons of machine translation. It seems to me MT should be understood strictly as a tool, and be used as such. A tool to facilitate our work. A tool, just like the many others we use on a daily basis.

    Whatever your take may be on this issue, though, you may want to know how MT developed. Read on, my friends! You can also go ahead and read the original post here. Story begins in The invention was super simple— cards in four different languages, a typewriter, and an old-school film camera. The operator took the first word from the text, found a corresponding card, took a photo and typed its morphological characteristics noun, plural, genitive on the typewriter. The resulting tape was sent to linguists and turned into a belletristic text.

    So only native language was required to work with it. No one in the world knew about the machine until two Soviet scientists found his patents in It was at the beginning of the Cold War. IBM computer automatically translated 60 Russian sentences into English for the first time in history. However, the triumphant headlines hid one little detail. No one mentioned the translated examples were carefully selected and tested to exclude any ambiguity. For everyday use, that system was no better than a pocket phrasebook. Nevertheless, the Arms Race launched; Canada, Germany, France, and especially Japan, all joined the race for machine translation.

    The vain struggles to improve machine translation lasted for forty years. They had instead recommended focusing on dictionary development, which eliminated US researchers from the race for almost a decade. Even so, a basis for modern Natural Language Processing was created only by the scientists and their attempts, research, and developments.

    The first ideas of rule-based machine translation appeared in the 70s. These systems consisted of:. If needed, systems could be supplemented with hacks, such as lists of names, spell checkers, and transliterators. Just take a look at the Aliexpress to feel the soft breath of this golden age. This is the most straightforward type of machine translation.

    It divides the text into words, translates them, slightly corrects the morphology, and harmonizes syntax to make the whole thing sound right, more or less. When the sun goes down, trained linguists write the rules for each word. The output returns some kind of translation. The linguists wasted for nothing. In contrast to direct translation, we prepare first —determining the grammatical structure of the sentence, as we were taught at school—, and manipulate whole constructions, not words — afterwards.

    That helps to get quite a decent conversion of the word order in translation. In theory. It still resulted in verbatim translation and exhausted linguists in practice. On one side, it provided simplified general grammar rules, and on the other, it became more complicated because of the increased number of word constructions in comparison with single words. The source text is transformed to the intermediate representation, unified for all the world languages interlingua.

    Next, interlingua converts to any target language, and here comes the singularity! Because of the conversion, interlingua is often confused with transfer-based systems. The difference is the linguistic rules specific to every single language and interlingua, and not language pairs. It was extremely hard to create such universal interlingua —a lot of scientists have worked on it their whole life. They did not succeed, but thanks to them we now have morphological, syntactic, and even semantic levels of representation, only meaning-text theory costs a fortune! Even if anyone were to succeed in creating an ideal RBMT and linguists enhanced it with all the spelling rules, there are always some exceptions —all the irregular verbs in English, separable prefixes in German, suffixes in Russian, and situations when people just say it differently.

    Any attempt to take into account all the nuances would waste millions of man-hours. The same word can have a different meaning in a different context, which leads to a variety of translations. Languages did not develop based on a fixed set of rules that linguists loved. They were much more influenced by the history of invasions in the past three hundred years. How should I explain that to a machine? Japan was especially interested in fighting for machine translation. There was no Cold War, but there were reasons: very few people in the country knew English.

    It promised to be quite an issue at the upcoming globalisation party. So the Japanese were extremely motivated to find a working method of machine translation. Rule-based English-Japanese translation is extremely complicated —language structure is completely different, almost all words have to be rearranged and new ones added.

    In , Makoto Nagao from Kyoto University came up with the idea of using ready-made phrases instead of repeated translation. All we need is to figure out the difference between the two sentences, translate the missing word, and then not fuck it up. The more examples we have, the better the translation. EBMT showed the light of day to scientists from all over the world: it turns out, you can just feed the machine with existing translations and not spend years forming rules and exceptions. Not a revolution yet, but clearly the first step towards it.

    The revolutionary invention of statistical translation would happen in five years. At the turn of , at the IBM Research Center a machine translation system was first shown which knew nothing about rules and linguistics as a whole. It analyzed similar texts in two languages and tried to understand the patterns.

    The idea was simple yet beautiful. An identical sentence in two languages split into words, which were matched afterwards. This operation was repeated about million times to count, e. The method was much more efficient and accurate than all the previous ones. And no linguists were needed. The more texts we use, the better translation we get. The machine needs millions and millions of sentences in two languages to collect the relevant statistics for each word.