1.
Language meets Knowledgein digital content management
Tatiana Gornostay

2.
In outline…
•Terminology
•Language ≈Linguistics
•Knowledge ≈Semantics
•Language Technology ≈ Natural Language Processing
•Machine Translation ≈ Automated Translation
•Terminology ≈ SpecialisedLexicon vs. General Lexicon
•Assumption
•Language OR Knowledge will not work
•Academia OR Public OR Business will not work
•Our future is in AND = cooperation
•Our future is in our users

3.
Language ><Knowledge
•Terminology
•A typical example of “theory” competition
•Traditionally oriented on Public and Translation
•Businesses suffered andarestill suffering
There is no direct connection between language and reality, between linguistic units and things. (Eugen Wüster, 1968)
‘tree’

4.
Language ><Knowledge
•Machine Translation
•Language-based approach “dethroned” by Mathematics
•great progress
•Knowledge-based approach developed autonomously
•the time has come for changes and the most promising can be found on the edge

5.
Embracing innovations

6.
Terminology examplebased on Tilde experience

7.
TerminologyResource
TerminologyServer
TerminologyService

8.
Machine Translation examplebased on Tilde experience

9.
Linguistics- based
Statistics- based
Hybrid waiting for Semantics
Desktop application
Translation server
Custom service

10.
Language <> Knowledge
•Terminology and Machine Translation
•We are ready 
•Scalability, Availability, Intelligence
•We can help Semantics
•Multilinguality
•Disambiguation
•Semantics can help us
•Improve quality of NLP output
•Form single digital content space –applications beyond translations can benefit from rich structured data
•We can evolve and benefit in this rapidly changing world
•Consistency, quality, efficiency

11.
Danke