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James Lougheed


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James Lougheed
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Published by jloug099@uottawa.ca on 2012-06-13

          As I stated in one of my last blogs, I think about words…a lot. But all those studying or working in translation are essentially programmed to think critically about words. We work to ensure their accuracy. After all, our job is to examine the written word. I often think critically in terms of the spoken word too; this, however, is a whole different ball game. As a translator, I forget about the differences between the domains of translation and interpretation. Although I categorize them under interlanguage communications, the skills and work involved are quite distinct.

 

          Recently, I had the opportunity to speak with Michel Mertens, a retired interpreter from Belgium who spent most of his career working in the House of Commons and the Senate. He has thus done his fair share of interpretation with the federal government in Ottawa and has accumulated a great deal of experience in the field. During our discussion, I wanted to find out the principal challenges and benefits of the profession.

  

          Having grown up in a trilingual French-English-Dutch environment, Michel says that he naturally chose interpretation as his field after graduating in 1969 because it was the “fashionable” thing to do at the time. “Those were good years for interpreters because what with the common market then, now the European Union, the demand for interpreters was huge…We could be pickers.” After a few dozen job offers, Michel chose to come to Canada because he wanted to see North America, where he would spend most of his career. And although he is now considered a retired interpreter, he still performs interpretation work on demand.

 

          Michel starts by stressing the importance of knowledge and comprehension in the field. He explains that in order to be a good interpreter, you must be continually learning. “It’s one of those specialities where you have to, by definition, learn as you go.” What we know as a human race is perpetually growing and developing; since interpreters need to stay in the know in order to work in any domain, they have to be more than just well-read. “Interpretation is a lifelong learning experience.” “And how does an interpreter keep up?” I ask. “Well, you keep reading.”

 

          Much like translators, interpreters have an incessant need to be mini-experts in any field. Despite the fact that there are translators and interpreters with very strong backgrounds in many specific subject areas, there are many who only have a limited time to learn as much as they can. Michel recounts that in his last ten days of work, he has needed to read up on nuclear energy, criminal justice and cattle-raising.

 

          In contrast, Michel also describes a distinct difference between the two professions to this effect. Translators are able to flip through documentation and retrieve knowledge as they go, whereas interpreters do not have the time on their side. While interpreting, one has to deal with the intense pressure of fully understanding a subject and extracting it instantaneously. It doesn’t always come at the drop of a hat. According to Michel, it is a five-day process. Once he has read through his assignments, he may spend the first couple of days lost in all the jargon, terms, abbreviations and specificity. The third and fourth days come to him more easily as the material begins to sink in. By the fifth (and maybe final) day, he’s cracked it. “The funny thing about it is…once you have it, you won’t touch it again for years.”

 

          We can all agree that as a demanding profession that requires constant professional development, interpretation is in no way for the faint of heart.

 

James Lougheed
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Published by jloug099@uottawa.ca on 2012-05-08

              Although stating that the use of new technology is becoming increasingly ubiquitous in almost all aspects of the present world would be beating a dead horse, I cannot help but raise the topic again. Ironic as it is to say (as this appears on a website dedicated to translation technologies), it is phenomenal to see the extent to which we rely on computer-based technology to translate efficiently and effectively. And even if the majority of these technologies fail, the existence of Google on its own would facilitate easier translation methods. Now let us take a moment to think about translation in earlier days when we did not have access to any such tools; how would one translate without using a computer?

 

 

                A lot of work, isn’t it? It’s scary, really, to think of the amount of research and long hours that one would require to translate even a short memo. Successful translators would most likely have to have a larger knowledge base; a good memory; an overwhelming quantity of notes, books, and paper resources; and a strong idea of the principles of translation. As a community that relies heavily on the availability of resources and transmission of information, we translate using a great deal more aids in comparison with the olden days where we would have had to do more snooping on our own.

               

              I was reminded of how great a change the translation industry has undergone when browsing an article concerning Xuan Zang (玄奘), a renowned Chinese Buddhist monk and scholar from the seventh century. Given my interest in the Chinese language and language theories, I was quite intrigued to read that he is accredited with being one of the first and most significant translators in the East. Xuan Zang was known primarily for his 17-year search for Buddhist scriptures in India and his translations of them from the Sanskrit originals. During his lifetime (602-664), he translated 1335 volumes of scriptures, amounting to 130 million words. The standard translator who goes through 3000 words a day would take over 118 years to translate just as many! In addition to his impressive rate of translating with next to none of the resources we have today, his translations are often seen as “exact, fluent and consummately skillful.”1

               

             One of his most famous theories caught my eye in both its simplicity and its value to translation: the Five Untranslatables (or the five instances in which one should transliterate). While translating scripture, Xuan Zang had listed a series of cases when one should not translate into Chinese. They are as follows:

 

1.       Secret information – the material is understood by few (mostly for nouns and arcane language)

2.       Word ambiguity and polysemy

3.       Lack of equivalents in the target language

4.       Existence of already accepted transliterations – perhaps there already exists traditional translations

5.       Lack of stylistic equivalents – although B is often translated as A, A cannot convey the deeper meaning of B

 

             Nowadays, it may be a little farfetched to use this as a template for transliterating since people are generally more knowledgeable than those of that time and access to further information is readily available. But I think it does give a really good guideline as to when one should be careful during the process, especially given the period in which it was written. In essence, when one comes across with “mystical” terms, one should not simply translate them non-contextually.  

 

Take, for instance, the following examples:

 

1.       Secret information: When translating an article on Icelandic traditions for a Canadian general interest magazine, one should explain terms, such as activities, garments and food, by either finding Canadian equivalents or adding footnotes.

2.       Ambiguity: When the end translation may conceal more than one possible meaning, whether in its words or its syntax, one should reword what is written so that it can only mean what is meant in the source text. A sample translation of “Les produits de nettoyage peuvent être dangereux“ could be “Cleaning products can be dangerous,“ though it should be revised as it is structurally ambiguous. Do cleaning products have the potential to be dangerous, or is it the cleaning of products that does?  

3.       No direct equivalents: One of the few that should be considered for true transliteration; after not finding an English equivalent for Schadenfreude, one could leave it as a German loanword as the concept does not exist as a single term in English.

4.       Already accepted transliterations: Although a traditional Chinese dress (Mandarin: qípáo 旗袍) could be easily translated as its Mandarin romanization, qipao, one might opt for its more common name from Cantonese roots, the cheongsam.

5.       No stylistic/conceptual equivalents: As is the case with many words in French, global has a much wider range in meaning compared to its frequent English equivalent. It may also be translated as “comprehensive,” “cumulative,” and “worldwide.” One should keep the proper context in mind when coming across terms with a broader or narrower definition than its typical translation.

 

              This list is by no means complete. As the world becomes increasingly globalized, translation itself becomes more and more muddled with new concepts and terms that pose difficulties to translators; with each new one, we have yet another decision on how to translate it into any language. Nowadays, we often look to the internet for a variety of resources that guide us to how to translate a term. Subconsciously, we are taught to take into account the cases Xuan Zang outlines.

 

              Since his time, he has been remarked as being a great contributor to modern translation theory and also as a frontrunner in many other common translation devices we use today: omission, shifting, borrowing, restoration of pronouns, etc. As much as we depend on new technology and cutting-edge software to get our work done, it is really thanks to these fundamentals that we can create effective translations. If only Xuan Zang knew that bringing the Buddhist scriptures to the Chinese would pave the road for such an essential method of communication…


1 http://www.tandfonline.com/doi/abs/10.1080/0907676X.2003.9961462#preview(external link)

 

James Lougheed
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Published by jloug099@uottawa.ca on 2012-03-27

 

Now, I don’t want to start a controversy, but for the sake of this blog, it cannot go unsaid. Google Translate has developed into quite a useful and relatively accurate tool. And although you language students and professionals may find the statement rather blasphemous to the field, you can’t argue with the increase in validity it has shown over the years. I use it as a quick dictionary and when I have translator’s block and need suggestions. Really, it is for good reason. When it comes to translating English and French, and most other European languages, it can be a good free tool to have at your disposal. But again, it is only good with European languages. As an avid lover of Asian languages, Google Translate leaves me up a creek without a paddle.  

 

I do understand Google’s plight: Asian languages are, for the most part, harder to translate into Western languages and vice versa. It is not that they are needlessly complicated or that Google has a harder time processing the information. They are just entirely different grammatically and idiomatically. Evidently, since East Asian languages did not develop anywhere near European ones, the way things are said can be quite different. When we use the common example of “it’s raining cats and dogs,” we would rather say “下倾盆大雨” meaning that big rain that can bend basins is falling. There is a big shift in concept, even without the vastly different grammatical structure. It isn’t surprising that Google has some troubles.  

 

Where does that leave us? Well, it seems we have to look to other resources, even when doing quick and straight-forward translation. And although I have yet to find a good translation tool that works well for the languages I have studied, I would like to share with you a dictionary tool that I have used time and again that can help with your translation woes: Perapera Language Tools!  

 

A “pop-up dictionary and study tool for Japanese and Chinese,” Perapera Language Tools are free to download and function as add-ons with both Mozilla Firefox and Google Chrome. And though they have only Japanese and Mandarin Chinese available to download, a Korean dictionary is apparently in development.  

 

The main thing I love about plug-ins is their automatic integration into my web browser. With Perapera- kun (a cutesy pet name for the tool), you can simply browse your favourite websites and move your cursor over any recognized Japanese or Mandarin writing to start using it. Once you do, the selected word’s possible translations are displayed in a bubble, whether there is one or there are ten.  

 

For the blog, I analyzed both of these dictionaries. For the Japanese dictionary, I used short excerpts from the homepages of Mixi, a popular Japanese social networking site, and Renren, a Facebook- equivalent Chinese social networking site.  

 

Japanese Perapera    

 

2CxaOQMRNvLUMuDVzadGjx3632RKL-bVU3JxLZNf  

 

Google Translate’s solution: Mixiprovides a comfortable connection to all people, As the mission is to

                                                   create the world can become a protagonist that everyone, We will continue

                                                    to challenge new.

 

We are presented with a sensible solution that, minus the poor grammar, captures the main ideas of the paragraph. But let’s take a look at some words that need specific clarification.      

 

 TSI403k5I2SSrRZR_mH3MtkRBma5VtXt146RF5Ef
Connection: (n,uk) connection; link; relationship; (P).

 


awH5yy4kPjzqyY0DiHaT453UL4dXBxlvcUipy6Rt
Protagonist: (n,adj-no) leading part; leading actor (actress); (P)

 

 

ivqkB8Q53Swp6koHav_wvKpYZw3utMs55W0UEg2cv1LPt1LzQjzikFp-GNxMQ72f-sqOXut0Vah9CZXA
Challenge + new: (adj-na,n,adv) new; fresh; novel; newly; freshly; re-; (P) + (n,vs) self-challenge; trying hard to do something; (P)

 

 

GBydIt5ELBaSfqI4kInEF99ZRn_K18oLzxPZlRWp
Mixi: (n) Mixi (Japanese social networking website) 

 

As you can see in these examples, PP is quite good at giving context, at least more than Google Translate provides. In the second sample, although we are still not given a sensible equivalent, we can understand more of the context with PP’s solution of “leading part,” indicating that it plays a leading role. In the third example, we can more clearly see that Google Translate put the words “challenge” and “new” in the improper order. And finally, we also see that PP identifies and explains some proper names, such as people and places.

 

Like any good dictionary, Perapera-kun lists its definitions with parts of speech for help with sentence structure, including: noun (n), godan/ichidan verb (v5/v1), archaic (arch), partical (prt), no-, na- and i-adjectives (adj-no, -na, -i) etc. And for those who are learning kanji (characters), the tool can zero in on kanji to display their own definition, readings, radicals, strokes, and it highlights the root and ending of a verb for conjugation.

 

Chinese Perapera

 

  WkwwrRL7SP7qT9qk7PqIVQ0hkpSuKEtjz3HrxAkm

 

Google Translate’s solution: Everyone Network is a real social network, to join her, you can:

·         Contact friends, learn about their latest

·         Photographs and logging life, to show themselves

·         And your friends share photos, music and movies

·         Freedom, security control of personal privacy

·         Find old classmates and meet new friends

 

 

AbUtEXGUtc7goF8PnfWRMp-yDlWkbHHTVlZwovbm9rZ4BwSo5tgn9R0jz-ZyMb6t8qH6hgHLgXDC3oWV

 Latest: (zuì xīn) latest, newest / (dòng tài) development, trend, dynamic state, movement, moving

 

 

q88Nb2W_JnaQ2x9x17QSCBtGjwyl-5YfnNINuQa4L39kF4XUJ2gU639WtlMQySh5HAVJxUynsQ4bE1JW

Logging: (rì zhì) journal, log (computing) / (jì lù) to record, record (written account)… CL:個|个

 

 

yjxXZr6aWCqm5OCn97M8u_neYltgdQvxllqoSrL5
Meet: (jié shí) To get to know sb, to meet sb for the first time

 

 

C7XMqPyl<strong>yhQbGVYF1TCgBjwsx6aIadurvWZ6V7
Everyone Network: (rén rén) everyone, every person   

 

Similar to the Japanese dictionary, Mandarin Perapera is effective (for the most part) at clarifying words and defining in an explicative context. For the example of “latest,” Google Translate cuts the word that should follow, “trends” or “status.” We also see that PP gives a greater context for words like “meet” in the text. The downfall is that its knowledge of proper nouns, as far as I have seen, is not as extensive. In the last example, we see that the dictionary does not register 人人as the name of a website, just translated literally as “everyone.” (I assume that this is because the creators were students in Japan, so it is not as updated as the Japanese dictionary)

 

Once again, for those who have yet to master Mandarin, there are a couple tools (though fewer than that of its Japanese counterpart) that can help you. This includes a pinyin pronunciation indicator, a dual simplified and traditional character display and a list of counters for countable nouns.

 

Conclusion

 

Overall, I think Perapera-kun is a great tool for learners of Japanese and Mandarin who want to integrate learning more actively into their daily web surfing. Also, it is great for understanding the gist of websites without having to rely on Google Translate – along with the satisfaction of learning on the way!

 

Additionally designed for students learning the fundamentals of grammar, Perapera Language Tools effectively break down words within a sentence to show where one word ends and one begins, along with explanations of individual kanji – a must for beginner students and experts alike (especially with the different character sets and alphabets the language has to offer).

 

Perapera-kun is by no means a perfect program, and does not contain as many entries as Dixio (a program that I studied in an earlier blog), but it is quite comprehensive in both vocabulary and definitions. I would suggest this tool for anyone learning, perfecting or just generally using either Japanese or Mandarin Chinese in their work or at home on a regular basis. If you have any suggestions or remarks regarding this program or any similar programs you would like to recommend, please feel free to leave a comment below.

 

James Lougheed
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Published by jloug099@uottawa.ca on 2012-03-21

Just when I thought I had written enough about words... (Well, let's be honest, there is no such thing!), I was thinking further on the relation of the translator's mind to these morphological instances. As I mentioned previously, they are a principal and essential part of the field. After all, everything we do is concerned with them: reading them, writing them, transforming them, finding equivalents and researching them. And although I thoroughly appreciate that they can bring joy to any page and create an immense depth, they can be a pain!

 

If I were to ask you to list the top five attributes of a good translator, I am confident that the term meticulous would be among them. If you were a bit more jaded by the translation world, however, I have a feeling that nit-picky might be the word of choice. This is, of course, for good reason. Translators do need to be accurate in their word choices: even one slip-up could cause damage. When we are always trying to cover our own hides, is it not surprising that we are always asking each other where we draw the line?

 

During my experience at the University of Ottawa, I had the idea that one must choose one's words with utmost care drilled into my brain. Many a class we would spend going through texts and discussing potential meaning errors, ungrammatical phrases, and politically incorrect and misused terminology. As much as we needed to be good writers, I often felt that we missed out on the liberties that most writers can take in their work. The writers whose work we would translate would clear a new path with their ideas; meanwhile, we would tiptoe behind, careful not to wander off the trail.

 

Living in the national capital region of Ottawa-Gatineau, we were taught with some emphasis on political correctness. Our region is politically charged for many reasons: it houses the Parliament of Canada and the Federal Government, it (along with much of Canada) is seeing a rise in cultural and ethnic diversity and it is a frontier between the greatest Francophone and Anglophone populations in Canada (those of Ontario and Quebec). When we translate, we have to be very careful so as to not offend anyone or imply anything that would (not anymore so than the writer intended to, at least). Again, we have to really "tiptoe" through our work and analyze it through the eyes of the writer and the reader. As tedious a task as this can be, it only goes to prove the implications words can carry; they have the power to really move us in any way.

 

When I look at it from a purely physical viewpoint, this seems odd. We create these things we designate as "words" by moving several mouth muscles and our vocal cords. And this physical movement can potentially create this ill will? Words themselves are not the culprit, in my opinion. It is the use of them over time. After all, words are (for the most part) created somewhat neutral to convey a concept. But as they are used more and more, they become implicated with new meanings within the contexts in which they are used. For example, if we deemed a new idea or object as a "Goonk," it would in its first instance be known as exactly what it is. Once we start using the word in relation to other objects, we give it context. It will continue to accumulate meaning, whether good or bad, as it is used more and more.

 

This reminds me of the work of French philosopher Jacques Derrida, who developed the theory of différance. In one of his essays, he argues that the way we view words is not through the reference they make to the referent, but rather by means of its difference from other words and phrases. By using a signifier (in other words, a word), we convey meaning by eliminating any other possibilities. As an example, a cup can be understood as such by using the term to separate it from things that are not designated as "cups." He also states that every signifier is not only a representation of the signified (the object or concept) as it stands in context; we must also consider everything else that it has ever or will ever signify, whether it is in a political, scientific, historical or cultural sense.*

 

Although that example is a little more than translators think when analyzing a text, it is because of it that we have to be wary of our every move. Even if they do not directly offend anyone or convey wrong information, our word choices make us the good translators that the world needs. As insignificant as some words may be, think about the words you choose when you are translating your next text or even writing your essay final. Think about how only one word could make all the difference!

 

 

 

*Derrida, Jacques. "Différance." Rpt. in Identity: A Reader. Du Gay, Paul, Jessica Evans and Peter

Redman, eds. London, Sage Publications, 2000.

cleardot.gif

 

James Lougheed
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Published by jloug099@uottawa.ca on 2012-03-10

Words. They are everywhere. All over this website. At school, at work, almost everywhere you go. I am sure that if you look around you, there are probably words to your left or words to your right. And if you are on this website, chances are that you have some sort of connection to them.

 

Me, I love words. I love the whole concept of them. Since the first utterances of human speech eons ago, words have formed arguably the easiest form of expressing and conveying thoughts and ideas among ourselves. They follow a certain set of rules, but they can also do some pretty random stuff. We can use them to show feelings and to affect others. They can be strong, weak, meaningful or meaningless. We can do so much with just a few movements of the mouth. And the best part of all: no one uses words exactly the same way. This is what led me to study languages and translation.

 

Whether you study language, work in the field, or take mere interest in it, I am positive you share some fascination with the way that words can put themselves together to form chains of thought. But would you ever say that it sometimes goes a little too far? If so, you are not alone!

 

If I haven’t emphasized it enough already, I love words! And after spending four years in a university translation program and other translation work environments here and there, I realize I have spent a lot of time speaking about words – even in my spare time. I could not help but laugh when a couple weeks ago, a friend and I were told to “stop talking about words.” Both products of the University of Ottawa translation program and language enthusiasts, my friend and I regularly discuss a variety of little language topics, whether it be etymology, grammar, translation errors, or just clever (or not-so-clever) puns. But in the company of others who are not as word-crazy as we are, we often forget that these do not make for the most thrilling of conversations. 

 

One day, while the two of us were having a night of playing cards with two other close friends (who are not word-crazy), we started up a word conversation without even thinking. After being told what we were doing, we led our chat back to more appropriate topics. Not long after, it happened again, and again. Needless to say, the night was sprinkled with reminders of “you're talking about words again...”

 

All taken in good fun, these reminders proved to be a further testament to the magic that words can hold. For us, it is evidently a profound interest that apparently knows no bounds (at least not within social situations). And I am sure that we are not the only ones in the language world to think so. Have you been told that you speak too much about words or languages from those that don't share this interest?


Words are wonderful. They have, in my opinion, become one of the most influential ways to communicate in our society. Furthermore, they offer so many options for getting our ideas across. Through language, we have invented the corresponding concepts of register, word choice, plain language and prose, among others. On top of that, there is the fact that we can do it using a variety of languages that use a variety of sounds and intonations. The fact that we all train ourselves to communicate in such an intricate way is nothing short of amazing!

 

James Lougheed
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Published by jloug099@uottawa.ca on 2012-02-13

There is no doubt that the integration of semantic technology into the world wide web is creating a new and more effective way of connecting people and information. In fact, it is with this technology that we form an even stronger web by linking ideas from site to site. In my last blog, I discussed the development of the semantic web, a relatively new method of connecting websites and information through semantic markup. In this blog, I will attempt to show how it works and uses syntax to create these links.

 

With a standard web page in HTML, a computer can display all the information it has been programmed to in a specific format. Links can be added to direct to different sites, texts, files, etc. But still, the computer can only do exactly as it has been told. A web page in the semantic web, however, is ideally filled with much more information so that it can actually understand a basic context of the data. A significant user of this type of technology right now is, unsurprisingly, Facebook. Let's have a look at how it is employing semantics to its advantage.

 

The semantic web is hinged primarily on the understanding underlying relations. How do we build these relations? Well, we start by organizing data using a programming model such as RDF (Resource Description Framework). With this model, data on a standard HTML web page can be equipped to carry relational information that can be used in other instances. This can be done using a syntax (in this instance, RDFa). A syntax, basically, is a way of describing the model to the computer.


When you publish information with RDFa, what you are actually doing is giving it a markup: each word or group of words is assigned a tag that provides it with additional information. In the case of RDFa, we use basic grammar as a framework for organizing the data. Let’s use a typical Facebook-related example: “John likes sports cars.” In RDFa, there are three classifications for a simple set of data; these are the subject, the predicate, and the object.

 

                   John            <>                 likes             <>             sports cars.

                  subject         <>             predicate         <>                    object

 

This statement is known as a triple.

 

To make sense of this data, the syntax is given a vocabulary. The vocabulary allows the computer to understand when we are speaking on a specific subject; without a vocabulary, a syntax is without meaning. One type of vocabulary used by Facebook is friend-of-a-friend (-foaf). With this, you can assign markups that further describe the data. For example, we can assign the attribute of person to “John.” In this way, we could also assign the attribute of thing to “sports car.” As for the predicate, we can provide it with a property such as rel (relation).

 

Now that we have created a context for the data, the computer can understand the relations between each packet of data. By knowing how everything relates, it can set up relations on its own based on pre-existing ones. Once John has expressed his interest in sports cars, Facebook may suggest other related pages to him (as I am sure you have experienced if you have a Facebook account). It may suggest that he like things that other people who like sports cars also like, such as the page for a company that produces sports cars.

 

In the same way, Facebook also operates through establishing relations between people. For example, you may see “John is now friends with Margaret.” Using the -foaf vocabulary, Facebook understands that “John” and “Margaret” are both people that are connected through the relation of friend. I can then use this relation to suggest other friends, pages or whatever else their relation may bring about.

 

To stop digging even deeper into technical programming jargon, I will leave it at that for now. Although, I am sure, I have only scratched the surface of how it actually works, I am by no means a computer programmer. What I have discovered so far, though, I believe has a large potential in the future for computer programmers and language professionals alike. Given the new developments in semantic technology, we now know how to allow computers to understand contexts and relations. It may still be a while before they understand texts the way the human brain does, but even this technology alone proves to be a significant breakthrough. Although the idea of free-thinking computers does not give the most comfortable feeling, the idea of a computer that can better understand a text and help with language-related tasks is ever so intriguing.

 

Sources

For more information on semantic technology, see my first blog: Semantic Technology.

Source video: RDFa Basics.

 

James Lougheed
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Published by jloug099@uottawa.ca on 2012-02-11

Have you ever stopped to think about how fundamental a role the internet has taken on in our lives compared to five or ten years ago? A large majority of us depend on it for providing entertainment, finding information and going about our daily lives. I remember a day when going online didn’t seem worth the loading time, when I would go to a library first to research a topic, when the concept of online instant messaging seemed so new and exciting. Now, the web is a common one-stop source for, well, anything.

 

Since my recent plunge into the world of semantic technology, I have come across countless mentions of what is called the semantic web. As the use of semantic technology grows, the semantic web is becoming more and more a topic of interest since it changes the way we use the internet.

 

As the World Wide Web Consortium (W3C) defines it, “The Semantic Web is a web of data (...) and provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries”. In other words, it connects different types of web data together and in an organized way. But how is this different from the way we use the internet now?

 

The traditional web as we know it is indeed connected with links that direct us from site to site and allow us to upload and download, among other things. With the semantic web, however, web data is given conceptual links to tie information together and “help computers ‘read’ and use the Web”. In a way, computers can understand the relationships between the words on a page. This can make web-related tasks incredibly simple since the computer can, to some degree, analyze data for us.

 

Say, for example, you are looking for a hotel in a vacation spot you are planning to visit in the coming weeks. While browsing different sites, you have a list of criteria that would constitute your ideal hotel room: size, location from downtown, price, amenities, availability, etc. With the traditional web, you will probably jump from site to site, jot down information and compare. With the semantic web, however, it is the computer that will retrieve this information and present it to you in an organized manner. By relating the data on a page, the computer can understand the relationship between a hotel room and its price, location and size. It is able to read the data and find what you need to know.

 

How is this applicable to language technology? Granted, the semantic web currently has a much larger influence on web developers and programmers than it does on language professionals. In my opinion, however, the semantic web is more applicable to the language industry than meets the eye. As I discussed in a previous post, the relation of words and concepts pose the greatest difficulty when translating and writing. After all, how can a computer understand something so complex? It seems, though, that we are getting closer.

 

As the semantic web is being incorporated into more and more websites, computers are becoming increasingly able to “read” text as more than just random data. In my next blog, I will discuss how the semantic web actually uses text on a page to understand its syntax and connect it all together. Hold on to your hats!

 

Sources

W3C Semantic Web Activity. W3C. 11 February 2012. http://www.w3.org/2001/sw/

How Semantic Web Works. Howstuffworks. 10 February 2012. http://www.howstuffworks.com/semantic-web.htm

 

James Lougheed
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Published by jloug099@uottawa.ca on 2012-02-01

No doubt about it, dictionaries are a translator’s best friend! When in trouble, we can always depend on them to help us find a solution. Each type of dictionary has its own look and layout, and contains its own set of tricks. And after a while, all translators seem to establish their favourite dictionary (or team of dictionaries) that will accompany them through the most difficult of tasks. What great companions they are!

 

To continue with my last entry on semantic technology, I decided to try a demo version of Dixio the Smart Dictionary software, available through Semantix. This dictionary is claimed to use this type of technology to search for entries in a more effective and relevant way. By using “language detection, morpho-syntactical analysis and the analysis of context, the word you are looking up is examined and prepared for subsequent treatment.1” On YouTube, some demo videos of the software display its unique features, such as integrating into different file types and programs and detecting complex forms (tenses, derivatives, phrasal verbs, etc.).

 

With over 90 dictionaries and glossaries integrated into it, Dixio is packed with useful resources that contain a large number of entries for almost any term. Intrigued by this seemingly unique dictionary, I tried testing Dixio with a variety of terms to see what it could handle. Here are the results:

 

Sample 1:

I am amazed at our progress in creating systems that not only come closer to imitating the functions of the human brain, but that also go beyond its abilities.

Source:  WordNet

come close 

v.

1 nearly do something; She came close to quitting her job

2 (approximate) be close or similar; Her results approximate my own

© 2005 Princeton University

Sample source: Semantic Technology: It isn’t just about words on a page anymore

 

Sample 2:

It goes without saying that recent technological wonders have…

Source:  Concise Oxford English Dictionary

go without saying be obvious. 

See: say

© ISBN 9780199548415 Oxford University Press 2008


Source:  Diccionario Inglés-Español de Semantix

go without saying

loc.

ser obvio, no necesitar explicación;

Ver: say v.

Ver: go v.

© 2010 Semantix

Sample source: Semantic Technology: It isn’t just about words on a page anymore

 

Sample 3:

As my first order of business, I hope to…

Source:  WordNet

order of business 

n.

(agenda, agendum) a list of matters to be taken up (as at a meeting)

© 2005 Princeton University


Source:  Diccionario Inglés-Español de Semantix

order of business

comp.

agenda, orden del día, relación de temas a tratar;

Ver: order n.

Ver: business n.

Sample source: Semantic Technology: It isn’t just about words on a page anymore

 

Sample 4:

Each of these is produced artificially in a nuclear reactor, from the fertile…

Source:  Concise Oxford English Dictionary

reactor

 n.

1 (also nuclear reactor) an apparatus or structure in which fissile material can be made to undergo a controlled, self-sustaining nuclear reaction with the consequent release of energy.

2 a container or apparatus in which substances are made to react chemically.

3 Medicine a person who reacts to a drug, antigen, etc.

4 Physics a coil or other component which provides reactance in a circuit.

© ISBN 9780199548415 Oxford University Press 2008

Sample source: Physics of Uranium and Nuclear Energy

 

Sample 5:

Morgan Stanley, owner of the world’s largest brokerage, will also cap…

Source:  English Wikipedia

Morgan Stanley

Morgan Stanley is a global financial services firm headquartered in New York City serving a diversified group of corporations, governments, financial institutions, and individuals. Morgan Stanley operates in 42 countries, and has more than 1300 offices and 60,000 employees. The company reports US$779 billion as assets under its management. It is headquartered in the Morgan Stanley Building, in Midtown Manhattan, New York City. 


The corporation, formed by J.P. Morgan & Co. partners Henry S. Morgan (grandson of J.P. Morgan), Harold Stanley and others, came into existence on September 16, 1935, in response to the Glass-Steagall Act that required the splitting of commercial and investment banking businesses. In its first year the company operated with a 24% market share (US$1.1 billion) in public offerings and private placements. The main areas of business for the firm today are Global Wealth Management, Institutional Securities, and Investment Management.

Sample source: Morgan Stanley, Citigroup Lead Retreat on Investment Bankers’ Compensation

 

Sample 6:

…that has the potential to fill the gaps that machine translation leaves behind.

Source:  WordNet

leave behind 

v.

1 depart and not take along; He left behind all his possessions when he moved to Europe

2 (leave) be survived by after one's death; He left six children; At her death, she left behind her husband and 11 cats

3 (leave, leave alone) leave unchanged or undisturbed or refrain from taking; leave it as is;leave the young fawn alone; leave the flowers that you see in the park behind

© 2005 Princeton University


Source:  Diccionario Inglés-Español de Semantix

leave behind

phr. v.

1 (objeto) dejar, abandonar, no llevarse consigo;

2 (muerte) dejar, dejar como familiares directos supervivientes;

3 (lugar, planta, animal) dejar, dejar en paz (fig), dejar tranquilo, no molestar, dejar tal cual;

Ver: leave v.

© 2010 Semantix

Sample source: Semantic Technology: It isn’t just about words on a page anymore

 

In the many cases shown above, Dixio does more than the average electronic dictionary. Dixio takes a word or series of words and actually analyzes the morpho-syntactic structure to give a more contextual and precise definition. It was able to recognize proper nouns, compound nouns, idioms verb phrases and phrasal verbs, and even their derivations. Any translator or language learner knows that this is incredibly useful!

 

That is not without saying, though, that there weren’t any troubles with the software. Some compound nouns and more informal phrasal verbs (for example, “getting closer”) were not picked up by the program. In addition, Dixio shows some issues with Firefox as it sometimes misread text in the browser. And I was slightly disappointed by the fact that Wikipedia was a common resource for the dictionary, especially for compound and proper nouns.

 

For the most part, however, I was very impressed with Dixio the Smart Dictionary. Its ability to look past the text on the page and provide fast and comprehensive entries proved to be very useful. With some additions, such as more relevant and credible content and resources, Dixio would be an asset to any researcher, language-learner, translator or language professional.

 

Of course, one downfall of the software is that it is only available in English, Spanish and Catalan at the moment. And it does not, as it stands, have a translation function. Using this type of technology (semantic technology), however, I can easily see how translating could be that much quicker. Not only would you have access to more entries quicker, but you would also have definitions and translations in context! To me, that sounds like a translator’s dream.

 

Although I have started to see how semantic technology can be used through my test of Dixio, I feel that there is still more to be discovered about this context-based search tool. I will continue to dive into this topic and see what more there is to explore…



1 Our Technology, Semantix. <http://www.semantix.com/en/tecnologia.html>. 1 February 2012.

 

James Lougheed
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Published by jloug099@uottawa.ca on 2012-01-27

It goes without saying that recent technology wonders have arisen as a main topic of conversation over the last decade. And for good reason. It is a marvel that our grasp of technology has accelerated at the rate that it has. As someone who has solely a basic understanding of how these things work, I am amazed at our progress in creating systems that not only come closer to imitating the functions of the human brain, but that also go beyond its abilities. In my opinion, this is both a scary thought and a comforting one. It is comforting to know that technology’s presence will allow us to advance more and more; but at what point will it go too far?

   

Having studied four years in translation, I have heard two questions asked much more often than I have wanted to answer: “What is a translator?” and “You need a university degree for that?” I agree, translation is certainly not rocket science, but it does require skill, practice and a degree of intellect. I often like to highlight the fact that a translation can require many hours of research and technical understanding to complete. That is to say, translation needs some degree of a cognitive process. When you take into account ever-advancing machine translators (such as the notorious Google Translate), however, we are seen as less and less useful in this world.

   

It is hard to refute that our work is not significantly simplified by the technology available to us. Concordancers, translation memories and environments and terminological databases give us a much wider range of tools that can stretch our words-per-minute higher and higher. But do or will translation technologies have the ability to translate entirely on their own?

   

Most translators would not hesitate in answering “no,” whether it be due to their experience in the field or their pride and hope to not be replaced by machines. But one must admit, we are getting closer. Semantic technology, for instance, is one way we can more easily rely on machine translation as a more accurate and efficient means of translation.

   

So what is semantic technology exactly? According to Luca Scagliarini of Expert System Semantic Intelligence, semantic technology analyzes words within their proper context and understands their meaning, even in different forms. Additionally, it “incorporates morphological, logical, grammatical and natural language analysis that translates into higher precision and recall.” In other words, it is technology that has the potential to fill the gaps that machine translation leaves behind.

   

It seems that a large part of its development is currently stemming from a business point of view. Corporations are starting to use this software to analyze internal and external data concerning products, methods, etc. Furthermore, this technology is being used more in search engines and other web applications to give better, more relevant results. One prime example can be seen in Facebook, which uses semantic technology to provide members with information that is more pertinent to them. To what extent, though, has it impacted the translation industry? And how will it continue to shape the way we translate?

 

As my first order of business, I hope to explore this issue in more depth, as it is a concept that not only will affect the way we work, but also that already affects other aspects of our lives. I will start my research with an analysis of a bilingual English-Spanish dictionary software by Semantix, a team of various language professionals. “Dixio the Smart Dictionary” uses semantic technology to determine the specific context in which a word aims to provide better entries accordingly.

 

As I dive deeper into the world of semantic technology, I am sure to find some interesting and useful software that may be putting this technology to use in a translation context. Stay tuned for updates!