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Terminology without LQA? No way!

Terminology without LQA? No way!

We have heard it many times in customer projects and never tire of emphasizing it: Terminology alone is not enough! Texts will always need to undergo language quality assurance (LQA) and a terminology check. Only like this, terminology can be used in the first place. Similarly, it does not suffice to introduce LQA without clean terminology either.
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Data Grooming for Machine Translation

Preparing training data for Machine Translation (MT) by using data grooming can seem like a mammoth task. And there is some truth to this. In practice, the huge variety of “contaminations” in training data plus high training data volumes can pose real challenges. This blog discusses why grooming is still a worthwhile investment and how automation can help save a lot of time and effort.
Scoping – From Vision to Machine Translation

Scoping – From Vision to Machine Translation

"We'll just buy a good machine translation system and everyone can just use that!" This is pretty much what corporate management sounds like for translation managers when it comes to introducing machine translation. However, prior to implementing such a tool, the risks and complexity of introducing MT should be assessed carefully. For our customers, this is where scoping has proven its worth. What this means and how scoping should be carried out in a company is the subject of my blog.

Don’t stumble blindly into machine translation!

Machine translation (MT) seems ingenious: fantastic translation results, available to all thanks to neural MT - fast, uncomplicated and seemingly free of charge! All good reasons why companies are rushing to embrace machine translation (MT). Now is the time to form a solid strategy on how, why and with what benefit they want to use machine translation!
Synergies between terminology and ontology – my master’s thesis

Synergies between terminology and ontology – my master’s thesis

Last March I joined blc as a master's student. The goal: to write a master's thesis on the synergies of terminology and ontologies by October. And even though I am no longer a master's student, but now support blc in the area of translation and terminology management on a full-time basis, the topic is still with me. After all, it was my constant companion for 6 to 7 months. So in this blog, I will tell you a little more about the subject and why it is so important. First of all, synergies between terminology and ontology are not only something for the theoreticians among us. No, you can also use these synergies efficiently for yourself in day-to-day work.
Ontologies in the Semantic Web

Ontologies in the Semantic Web

Terms such as “Ontology” and “Semantic Web” are still a new territory for many. However, in today's information society, which is characterized by digitalization and automation, these terms are gaining more and more importance. We would like to show you why ontologies are becoming increasingly significant as the next logical step after the introduction of efficient terminology management and the establishment of a consistent terminology collection. But what are ontologies? What do they look like and how can they be represented? And what is their purpose - especially regarding their use in the Semantic Web?
From Terminology to Ontology

From Terminology to Ontology

Conceptual relations are the basic precondition that lead to understanding terminology. But what is behind these relationships? What relations exist between terms? How can a semantic network be created with conceptual relations? And how does this help us to re-use terminology in computer-readable ontologies?