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A Practical Approach to Terminology Work

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1. INTRODUCTION

The current paper aims to be a practical  proposal for terminology work based on practical  experience  having  as scenario an individual translator or  a  small  team  of  translators. Terminology is one of the most time-consuming  tasks  involved in a translation project. In order to face the challenge that terminology poses on translators it is necessary not only to know a  set of  appropriate  tools  but also to bear in mind strategies that  will  make  possible  it  to deliver the job on-time and within the translator’s time budget. 

It is important to take into account that terminology search and management are two specialized tasks, which fully justify the role of translators as technical writers versus subject specialists. For a review of the importance  of language resources in the translation profession see Yuste (2002). If we  constrain  ourselves  to  any particular  sphere of  knowledge
(i.e., medicine), we cannot expect  any  specialist to know every aspect of his or her area of knowledge.  Translators  should be specialized, but the important objective  is  that  they  have  the competence to  investigate  and deal with any text related to the field of their specialization due to their  documentation and terminology search abilities. 

This  paper  is  aimed  at those newcomers to the profession and  at  experienced  translators willing to revise their terminology search strategies. The practical examples illustrated in this paper will  use

the linguistic combination English-Spanish. 

2. TERMINOLOGY SEARCH TOOLS

Primary  sources:  Parallel  texts and specialists 

A primary source (PS) is basically any kind of original oral or written  text  produced  by  a native speaker. Examples of primary sources are handbooks, newspapers, technical documentation, fiction books, websites,  etc.  The  terminology work using primary sources will focus on finding context where source  language (SL) terminology is used in the target language (TL) text. 

Traditionally, hardcopy books have been the main resource of PSs. Nowadays electronic copies  and  mainly  the  Internet are switching the nature of PSs, and  this switch  is  even  more important  for  terminology  work performed  during  a  translation project.  Note  that  dealing  with electronic  data  makes possible the use of software applications to manage rapidly and automatically enormous batches of  data
(i.e., automatic terminology extraction, quick  term searches, etc.). As the goal of this paper is to be a practical guide  for professional translators, we will consider the current biggest knowledge databases  available at translators’ fingertips, that is to say, Internet search engines. Please see section 5, Using Internet  Based  Resources for further information. 

A versatile and important PS is the  knowledge  accumulated  by field specialists. Any competitive translator who aims to be a real specialist in a specific field should have a set of specialists related to his/her field of specialisation available for consultation. To achieve this goal may be seen as a sign of maturity as a specialized translator and, by no means, a stroke of luck; medical doctors, competent lawyers, engineers or any other knowledgeable highly-specialized professionals are generally all too busy and well paid to establish a mutually beneficial  business  relationship with  translators. Perhaps translator should look for retired professional who may be suitable  and  willing  to be the specialized  support to translators. Besides, we need to evaluate and check the terminology that a particular professional may use; many times  the  economy principle  of language makes professionals stay  away  of  more  formal  and standardized terms in the written  language,  which  are the most appropriate for translation. 

Secondary sources: Dictionaries and glossaries (hard copy, electronic copy and the Internet) 

Secondary sources are basically monolingual and bilingual dictionaries and glossaries. They can be found in their hardcopy, electronic or on-line versions. A comprehensive and quality-orientated  secondary source  is the dream of any translator. They can make terminology research really easy. 

Nowadays, we  find  publishers releasing dictionaries in the above-mentioned different formats.  For  example,  we  can find the Encyclopædia Britannica on-line (www.britannica), on CD or in its traditional hardcopy  version. As romantic as we may think hardcopy  books  are,  the reality is that a term search in the electronic or on-line version of a dictionary is much quicker, which as professionals we need to consider  as  a top  relevant factor. 

Either using a primary or secondary source, it is important to  consider  their  reliability.  We need to stress here that printed publications will  normally  rank higher when considering the reliability of the source. This is not a fixed criterion as there are excellent resources available in electronic format and, at the same time, there are lousy printed  publications  which may be the result of a bad translation work or poor quality terminology compilation. Furthermore, we  increasingly find a great deal of data reproduced in electronic and  hardcopy  versions. Basic criteria to evaluate the reliability of a source are:
¾ Reputation of the author

(well-know, specialist, reliable)

  • Type  of publication (specialized magazine, thesis, original technical documentation...)
  • Whether  the  source  is an original or a translation
  • Publisher's  prestige  (public institutions, universities...).  The following chart presents Harris’ CARS Checklist (Harris, 1997), which may help us to evaluate deeper resources found on the Web

Credibility
Trustworthy source, author’s credentials, evidence of quality control, known or respected authority, organizational support. Goal: an authoritative source, a source that supplies some good evidence that allows you to trust it. 

Accuracy
Up to date, factual, detailed, exact, comprehensive, audience and purpose reflect intentions of completeness and accuracy. Goal: a source that is correct today (not yesterday), a source that gives the whole truth. 

Reasonableness
Fair, balanced, objective, reasoned, no conflict of interest, absence of fallacies or slanted tone. Goal: a source that engages the subject thoughtfully and reasonably, concerned with the truth. 

Support
Listed sources, contact information, available corroboration, claims supported, documentation supplied. Goal: a source that provides convincing evidence for the claims made, a source you can triangulate (find at least two other sources that support it). 

3. A MODEL OF TERMINOLOGY MANAGEMENT

When  approaching  terminology work from a professional point of view, there is a somewhat complicated balance between time  and

quality. As professionals  seeking to maintain,  broaden  or  improve our  customer portfolio,  we can only  deliver quality  but, at  the same time, we need to deliver that competitive quality within a reasonable and profitable timeframe.  In  order  to  achieve this goal, there are some points we  need  to  take  into account when facing terminology work in any translation project: 

  • Whether developing a glossary is worth the effort
  • Automatic terminology extraction versus traditional human extraction
  • Setting priorities
  • Strategies to overcome terminology uncertainty
  • Retrieving terminology  

 

3.1 Whether developing a glossary is worth the effort

Depending on the nature of the translation project and our customer, we can estimate that the time invested in creating a glossary  will  pay  off  in  future assignments or within the same project, not only regarding terminology search time but also in  quality  through consistency and accuracy. As a rule of thumb,  if  we  got  a  long-term relationship with our client or are seeking  it,  the  creation  of  a glossary will be a key factor to  render a  quality  and  profitable job.  On  the  other hand,  if  the translation is going to be done by a team of translators, which will  mean  that  we  are  dealing with a large project, the creation of a glossary will be highly advisable  as  to  save  the  time requested for the project by avoiding redundant term searches and to provide a higher consistency. 

The creation of a glossary will be equally important if we are thinking  of  translating  using  a Machine Translation system. Most  of  these  applications will allow us to create a customary dictionary that will be used during translation. As described by  Kübler  (2002),  this method may produce good quality results. 

3.2. Automatic Terminology Extraction  versus Traditional Human Extraction

Once we have decided to create a  glossary, there are  at  least three different approaches to the compilation of SL list of terms: automatic terminology extraction, human terminology extraction before or human terminology extraction during translation. 

Automatic terminology extraction 

This is a technology which is a good  candidate  to  become  a standard in the industry. Automatic terminology extraction is  based on  the  principles  of corpus linguistics, that is to say, the study of language based on large text databases (or corpora) through software applications. This makes possible a statistical approach  to  language  through the  study  of  word  frequencies  and concordance patterns, among  other variables.

Terminology extraction applications generally use word frequencies to propose a list of candidate words. The principle is easy: if a term is repeated several times through a text, it may be a term specific to that particular field. After this automatic  selection of  potential terms, the translator needs to go over it and select the terms he considers to be relevant terms to be included in the glossary. 

This technology is far from providing exact results. For example,  pertinent  terms  may have a low frequency and therefore will not be included in the  candidate  list.  The  point  is that for large projects this could be  an  important  time  saver.  A commercial application using this basic principle is for example TerminologyExtractor or Trados  Term Extract.  The latter features a function for exclusion  terms  (for  example, terms already stored in a MultiTerm  database). Termight, another extraction terminology tool, uses taggers and a set of syntactic patterns defined by regular  expressions  to  identify candidate  terms and expressions. It also features an interface  showing term concordance to help the user to decide if a word should be considered as a term. 

This approach should be seriously  considered  if  we  are dealing with large projects as it will  help  to  rapidly  deliver  a glossary  to  a  translator  team. The shortcoming of having some terms  left  out  of  the  glossary may  be managed  by  including those terms during translation. In any case, these terms are likely  not to have a high impact due to their low frequency. 

Human terminology extraction before translation 

This is the current practice and consists of reading the document to be translated, focusing on tables, figures, indexes, tables of contents and other key text elements in order to establish which terms are good candidates (Dagan and Church, 1994). As happens with automatic  extraction, this approach may be defective due to human errors, so we can also expect to have some terms left out of the glossary. The advantage of this traditional approach  is  that  the  translator will have available the context at any  moment,  which may  be  a key factor for deciding about the appropriateness of a word to be added to the glossary. Note that some automatic terminology applications offer practical solutions  to  make  the context available.  A  drawback  to  this method is that it is very time -consuming compared to the automatic approach. Despite this,  we  can  assume  that  this method will be valid for relatively small projects as automatic terminology  extraction is expected  to  be  more  efficient when dealing with large projects. 

A  practical  tip  to  minimize  the time required to create a monolingual glossary when working in a word processor, is to create a macro (so called in MS  Word)  which  automatically copies and pastes the selected word or expression into a table created in another file. This way we avoid the distracting and time-wasting task of coping and pasting or typing entry by entry. 

Either with this approach or using  some  of  the  automatic terminology extraction tools existing on the market, we will need to set strategies to leave out of our term list those terms that we already have in an existing term database. A possible procedure would be to look up any individual term in the database. A less time-consuming way is to copy and paste the candidate terms highlighted from a table into another table containing all the database terms. If we sort this table  alphabetically,  we  could easily discern redundant terms. 

Human extraction terminology during translation 

Another  possible  option is to introduce terms in the glossary at the same time we are performing the translation. I have not  found  an  empirical  study comparing translation word ratios to evaluate productivity including terminology when creating the glossary before or during  the  translation. We  can assume that when creating bilingual glossaries before translating, the difficulties to render some  solutions  may  be greater or more time consuming as the translator will have generally a more superfluous understanding of the term, but, when  translating,  we  will  have less interruptions due to terminological searches which can help  to  concentrate  better and  to  produce  more  coherent translations. 

On the other hand, the creation of  glossaries  during  translation will help us to produce directly bilingual glossaries with a deeper knowledge of the context. While using many of the commercially  available  memory  translation tools (i.e., Start Transit, SDLX or the latest Trados version), it will be relatively easy to add a new term to  an  existing  term  database, checking simultaneously  if  that term has been already collected. Note that even using the automatic terminology extraction or the human extraction before translation strategies, the use of this on-going term extraction feature is highly probable. In any case, the use of human terminology extraction during translation is discouraged if we are dealing with a large project involving a team of translators, as we cannot guarantee the consistency of the terms and this will need to be thoroughly checked afterwards. 

3.3. Setting Priorities

Ideally, we will search a list of terms to solve all the terminology work until we are fully documented  and  satisfied  with the results. This means we can do a four-hour search for a single  term,  depending on  the efficiency of our search and the available resources (we may need  to  visit  some  libraries or wait to contact a reliable specialist). But normally the job is for yesterday, so setting search priorities is a valid way to get the best possible results within a limited timeframe. Here there are some guidelines which may help to judge which terms should be considered the most important:

  • Terms appearing in an index, glossary of contents, titles and other relevant text elements
  • Repetitive terms
  • Terms we reckon to be established  and fixed formulas  in the  TL  in an  industry, regardless the frequency or the place where they appear 

For  example,  it  seems rather obvious that a product name in an instruction manual will have maximum priority. The chances are that such term will appear in the title of the publications and that the frequency of occurrence in the text will be rather high; it is also  highly probable  that  the term has a standard translation solution in the TL. 

On the other hand, when dealing with  terminology,  we  can  find terms that are not consistent in their use in TL within a specific field of knowledge. When facing those terms (and recognising them requires sometimes an experienced translator’s intuition), we can translate them with a solution which delivers the meaning and sounds natural, saving  the  time  to  look  up  a dictionary or to search in parallel texts.  On  the  other hand,  we need  to  recognize  those  terms whose use may be well standardized in a particular specialist  jargon  and  that  will need an exhaustive terminology search. 

3.4.  Strategies  to Overcome Terminology Uncertainty

In  the  translation  profession,  a job often needs to be delivered to the client but some terms may have not been satisfactorily resolved. This results in different scenarios and requires different strategies: 

  • Scenario 1: The term is well understood but no validated  solution (through a primary source) has been found. Strategy:  Paraphrase  or  use  a natural term, assuring that it will be understood by the target reader. 
  • Scenario  2:  The  term  is  not understood and no validated solution  has  been  found.  We should make all possible efforts to avoid such circumstances, but any  experienced  translator  will sooner or later face this compromising situation. Strategy:  1)  Literal  translation; Unfortunately, the market is swamped  with dubious translations  which tend  to be literal, avoiding the responsibility and effort of understanding the SL  text  and  standardizing  the use  of  those  calques  or  loan translations; apart from this, it is also the tendency among specialists to use highly technical terms created in an SL (of course, this is specially true for translations from English, due to the use of this language as lingua franca). So the chances of being understood by the target reader  are high,  especially  if translating for a specialist audience. Depending on the type of text it may be acceptable to put the TL term in brackets, so we broaden our chances of being understood, as there may be cases when the target reader knows the terminology in the TL (for  example,  this  will  be  the case  if  translating  a software magazine from English into Spanish); 2) Undertranslation; This solution  may  be rendered when the term was not entirely understood  but  because  of  the  context  can be  classified  as a term belonging to a certain category.  For  example,  if  we know that the specific term is a tool, there will be occasions where such an undertranslation will  work  as  the context  will provide  the target  reader  with the representation or meaning of the specialized term we are avoiding to mistranslate. 

3.5. Terminology Databases

Once we have a bilingual glossary, we need to think out a way to retrieving terms when we need them. Taking into account that literary translation may account for 2-3% of the translation market, I believe that translators  should  own any  of the  current commercial translation memory programs which will improve performance in most translation projects. Translation memories are an efficient tool to gain consistency and save time. They are a word databank of all previous translations  which  can then be reused or where already translated terms can be looked up. But the important point regarding  terminology  work  is that  TMs  come  integrated  with terminology databases. This integration permits a feature in the TMs that automatically recognizes  terms  stored  in  our database. So while we are translating, we will have a window where the terms already found in the terminology database will be displayed. Below I have inserted a screen shot showing how this is presented in Trados WorkBench: On the bottom left corner of this screenshot  appears the terminology recognition window, which  will  pop up  when the terms are  detected  in  a  new open segment  (blue  box)  and existing  in  the  open  database file. 

This feature is a step further in terminology  management.  The traditional method implies at best an  automatic  search  using  the Find function to locate a term in a glossary produced with a word processor or a spreadsheet. This way of looking up terminology in a glossary is time-consuming compared to the automatic recognition  feature we  find  in current translation memory  applications,  not  only  because we need to copy and paste the term or type it to do the search in the glossary's file, but because sometimes we  may  expect a term to be included in the glossary only to realise this was not  the case  once we  have invested  the  time  in  searching for it. 

Besides this, the terminology recognition feature in TM applications carries out fuzzy searches. This means that if a word  in  the glossary  or  in  the source text is misspelt, the program will  still  look up  for terms very close to the misspelt words, assuring that they will be recognised  or  plural nouns will  get detected if the entry in the glossary was the singular form. 

Normally,  we  will  be  able  to easily import our glossary from a word processor or datasheet into the terminology database, though we will need to convert the glossary file to a .txt file and perform some changes. Note that  the  terminology  databases integrated with  TM  applications are sophisticated products. This means  that  we can  create  a much  greater  number  of  fields (including graphics) than our practical approach will suggest.

4. A MODEL OF A TERMINOLOGY SEARCH

Depending  at  what  stage  we decide to create the glossary, we may have a list of terms we need to understand and to translate. We will assume that the decision was to create the glossary before translation, when so may proceed as follows: 

  1. Context: Once we have isolated  the  term  in a glossary,  we  may  need to go back to that term in its context. To do so, we can simply do a search on  the electronic document we are dealing with. If the project  is  made up of multiple files, it is advisable to find a way to review the context with  a  unique  search. For example, if we have a batch of text files, we could  create  a  file  with all  the  content.  As  we proceed to render a translation  for the different  entries  in  the glossary,  it  is  important to be able to access the context  of  the  terms  in the  list  to determine  in which sense the term is used in the SL text. 
  2. Understanding  the  SL term: It seems obvious that  to  render  the  best possible solution and to avoid errors in meaning, the understanding of the SL  term  is  compulsory. There are basically three approaches to  this:  a) general dictionaries, specialized dictionaries and monolingual glossaries, b) SL written primary  source,  and c) specialist consultation. Note that it will be  possible to take a definition of a term applicable  to our context, because we can access  this  context  to determine which definition applies. 
  3. Finding  a  translation: Here we find again three possible ways to provide a  solution: a)  bilingual general dictionaries, bilingual specialized dictionaries and bilingual glossaries, b) TL written primary  source,  and c) specialist consultation. Note that when finding a solution  in  a  secondary source, we will need to validate that solution in a primary source.  Many times we may find ourselves at a dead end; we are not able to find in the  resources  available a  reliable solution, sometimes just because we are dealing with terms which  have  not been  rendered  into  the TL. Please  see  section Strategies to overcome terminology uncertainty. 
  4. Entering information in the  glossary: We  will need to enter in the glossary all the information we have been finding. I would suggest creating optional fields in the glossary such as context, definition and non-verbal  elements.

Ideally, at least these fields should be inserted in  a  glossary,  but  the reality  is  that  for  many professionals this is too  time-consuming  to  pay off.  Nevertheless,  it  will be sensible to create these fields for terms that may be deemed especially complicated, relevant or repetitive. Sometimes we may find that  the  same  word  is used as a technical term with different meanings, and possibly different translations, so we need a definition or a context to make a distinction. On the  other  hand,  if  the glossary created will be used by a team, it will be reasonable  to  add  the maximum information possible. 

These four basic steps are many times  interrelated and, depending  on individual circumstances,  can be performed completely or partially and in a different order. This will always be justified as long as an optimal solution  is  achieved  in the shortest possible period. 

5. USING INTERNET-BASED RESOURCES

This section will show a set of practical resources we can find on  the  Internet.  Following  the spirit of this paper, this section does not aim to be a comprehensive  display  of  web-based resources  and  possible strategies; instead, it looks up to be an informative and stimulating  view  of  the  kind  of resources we  can  find on  the Web. 

On the Internet, we can find a great  number  of  all  types  of resources described in section 2. The  Internet  connects  us  with such a variety of resources that  the translator needs to be cautious  not  to  get  lost in  this myriad of data. Saving time delivering quality is the goal, so we will need to concentrate on those resources which yield the best  results.  Most  experienced translators will finally select those resources which they have found more helpful. 

A very practical point to bear in mind when working with the Internet is the type of connection we  have.  Note  that  a  dial-up connection can be 5 to 10 times slower  than  a  cable or  ADSL connection, which correlates with the search rate per hour at which  we  will  be  able  to  work with these different types of connection. 

Search engines  and  directories will help us to locate those web pages which  may  contain  the  information we are interested in. Directories (such as Yahoo!) classify web sites in categories; while  this  may  be  an  efficient way to locate information, search engines are a quicker and more comprehensive tool for this purpose. There is a wide range of search engines we can use: Google, Yahoo, AltaVista, Lycos, MSN,

Excite, HotBot, LookSmart,  AOL,  WebCrawler, InfoSeek and many more. Many of them will be just a change of interface but will render the same searches, for example Yahoo! searches are based on Google algorithms; MSN and AOL  are  powered  by  Inktomi (the number two Internet traffic generator), HotBot gives us the possibility to use Inktomi, Google or Teoma to perform a search. As said before, one can get lost easily  in  front  of  this range  of  options. I began searching with Yahoo!, changed to Altavista and finally stuck to Google. Google has gained a lot of the search engine business, despite having appeared in the industry long after Yahoo! or Altavista. As a matter of fact, now Yahoo! is powered by Google, and Altavista has lost a lot of surfers in favour of Google. The point is that Google’s algorithms seems to deliver more pertinent searches, apart from having one of the largest website databases and  allowing  for sophisticated advanced searches. Below there is a view of the different options to do advanced searches using Google. You get to this window by going to www.google.com and clicking  on  the  link  called "Advanced Search." Please read through the screen to get familiar with these options.

Google

While all options may be practical during a search, here it is  a summary  of  those  more generally used. Note that to perform quicker queries Google gives the possibility to type in the main  search  box  some  search option codes, so we avoid having to go the Advanced Search page. The use of these codes is strongly recommended to further minimize search time. 

Whenever we do a search with Google entering more than one word,  Google  will  find pages which  have  at  least  all words typed,  not  considering  for  the search very common words such as "the", "of", "is", "are" and the like. 

Code: + 

This code will be useful when we want a very common word to be included in the search. For example,  when  an  acronym  is spelt  as a  very  common  word
(i.e., IS may stand for Intensity Stereo  or  AS  for  Associate  in Science).

The following screenshot illustrate  a  search with 4 words, "as", "in", "associate" and "science". As we have introduced the code with "as" and "in", Google will consider these words while searching, and as we have introduced "associate" and "science", the chances are that we get pages were "AS" stands for "Associate in Science".

Code: -  When  using  this  code, we will get  pages where  the  -  coded words will not appear. This may be helpful when we get a high number of  pages  and want  to further fine tune the search. If we  look  at  the pages delivered  in the above screen shot, we will see that we obtained searches with "of", which actually introduces noise to our search. With the code -, we can get rid of this very  common  word  in our search  and  get  a  less  noisy  response. As we will see now in the following screenshot, the first four searches  show  "Associate in  Science",  when  before we only  got  two  pages with  this word  pattern.

Code: " " 

This is probably one of the most helpful search options we have in Google. As a matter of fact, we find this option in most  search engines. It is highly helpful when validating expressions or searching for specialized  web  contents. For example, in the educative example provided above, we  could just enter a search using quotation marks such as "associate  in  science  (AS)"  as this  screenshot shows:  The use of quotation marks gives us the possibility to search  for definitions, which we may not have  found any  dictionary,  by locating them in specialized texts  or finding  contexts  which will help us to infer a definition. The  following example illustrates this point:  Code: site:domain 

In Google we can make a search within a single domain. This may be  helpful  when  we have  no glossary from the client but we need to be consistent with the clients’ terminology, with Google and this function we can easily check if a term is used in the clients' website.  For  example, we could check if motherboard is translated  in  Intel's website  as placa madre or placa base, two different possible solutions. We could the use of this terminology by  entering  in  Google's search box: site:intel.com "placa base"; and in a second search, site:intel.com "placa madre". 

The  code site:domain is  very useful when dealing with different variants of a language. For example, if we are translating  for  an  international audience,  what  happens  often when translating into Spanish or into  English,  we  may  need  to know if a term is used in a locale or  had  different  uses  in  other  variants.  If we  investigate  the word computer in Spanish, which  should  be  translated  as computadora for  Latin  America and as ordenador for Spain, we will see that computadora appears in 11.500 pages in ".es" domains ("es"  is  the regional domain for Spain) versus 69.300 pages  in  ".mx"  domain  pages ("mx" is the regional domain for Mexico), on the other hand, ordenador appears  in 137.000 ".es"  pages  versus  4.110  ".mx pages". 

This  type of  constrain  may  be very useful to found more relevant and reliable resources. By  using  the  code site:domain we may filter a lot of web sites, which  are themselves translations and that should be considered less reliable than web sites  produced  by native-speaking specialists. Regional domains are more expensive, so we  can  expect  more  quality  in regional web pages. Another example,  if we are  looking  for documentation in English, is that  we can search just ".edu" web sites, which will belong to a post-secondary accredited educational institution in the US. 

Code: -site:domain 

This option is just the reversed option of the previous one. There may be cases in which it is  useful  to  be  able  to  avoid pages of a specified domain. 

Code: OR 

Using the code OR we will obtain pages which contains one of the two words or expressions searched.  We  can  use OR to simultaneously search in various domains. For example, we may decide to validate our IT technology by using the Spanish websites of three major IT vendors, such a Microsoft, Intel and Hewlett  Packard,  on  the basis that their multinational presence  and  power  will  have standardized the use of some IT terms. The next screenshot illustrates  this: Glossaries and dictionaries

On the Internet we find available a great deal of on-line specialized dictionaries, especially  if  our  SL  or  TL  is English. Here we find high quality dictionaries on-line such as Dorland’s and Stedman’s medical dictionaries or What is? and  CCI Computer  computing dictionaries.

A wonderful resource  to  find  definitions  in English monolingual dictionaries is Onelook, a portal that acts as a gateway to 933 on-line dictionaries. We can expect this kind of portals in other languages, and if not, it is very likely that this kind of solution will be popular in some years. At this  point, there is not any resource comparable  to  Onelook  for  the Spanish language. 

Multilingual or bilingual dictionaries  are not so comprehensive  as  a rule.  We find a practical example of this in Spanish.  Two  good resources are Eurodicautom, the official dictionary of the EU, and LOGOS, a multilingual dictionary made available on the Web by the  translation  company of  the same name. Onelook also offers the possibility to rendered translations  for  term  searches, though  it  is  not  very  efficient. None  of  this source may  be considered  as  reliable  as the high-quality  published bilingual  dictionaries. Unfortunately, we may found very poor translations in the mentioned on-line dictionaries. In any case, as we said in section 2, secondary sources should be always validated through a PS, more if we are dealing with SSs found on the Internet. 

An impressive tool to locate specialized dictionaries in a great number of language combinations is Lexicool, which has indexed over 3000 Internet dictionaries. The following screenshot illustrates the type of search  results  we can obtain with  Lexicool:  Regarding  glossaries, we  can find  multiple specialized glossaries published on the web  by public and private organizations. Many times a search with  the  term  and  the word  "glossary"  may  return  a  page with  a  glossary  and  the word itself. See example:  Note that this search was done only in  web sites  with  domain  ".edu"  in  order  to  increase  our  chances to obtain a reliable source. 

Professional web sites

Nowadays, there are a number of web sites for translators offering  freelancers and agencies to appear in their service  directory (www.proz.com;
www.gotranslators.com;  www.aquarius.net and many others). The leading translators’ web site is Proz.com, there you will find a large glossary of terms entered by other colleagues, beside you may post a query in real  time  to  all  the  translators accepting questions. This same concept has been implemented  by Aquarius, but at this moment the terminology activity at Proz.com is much higher. Translators are motivated to answer as they will score points to  show  potential  clients  their expertise, so answers should be taken  with caution  and always validated.

 

6. BIBLIOGRAPHY  

Dagan,  I.  and  Church,  K.  1994. Termight:  identifying  and  translating  technical  terminology.  In Proceedings of Applied Language Processing, pp. 34-40. 

El Hadi, M et al. 2001. The ARC A3 Project: Terminology Acqusition Tools: Evaluation Method and Task. In ACL-2001 Workshop on Evaluation Methodologies from Language and Dialog Systems, pp. 42-51. 

Harris, R. 1997. Evaluating Internet Research Sources. In http://www.virtualsalt.com/evalu8it.htm 

Kübler, N. 2002. Creating a Term Base to Customise and MT System: Reusability of Resources and Tools from the Translator's Point of View. Proceedings of the First International Workshop in Language Resources  for  Translation  Work  and  Research. Paris:  ELRA  (European Association  for  Language Resources). 

Yuste, E. 2002. Language Resources and the Language Professional. In Yuste, E. (Ed.) Proceedings of the First International Workshop in Language Resources for Translation Work and Research. Paris: ELRA (European Association for Language Resources).  

José Gambín's picture
José Gambín
José Gambín holds a 5-year degree in Biology from the University of Valencia (Spain) and a 4-year degree in Translation and Interpreting from the University of Granada (Spain). He has worked as a freelance translator, in-house translator, desktop publisher and project manager. From 2002, he is a founding member of AbroadLlink and currently works as Marketing and Sales Manager.