>>> That is fine, from an academic point of view, but the fact is that
>>> a glossary function must have the ability to recognise items from
>>> the source text that are in the glossary. No program can recognise
>>> concepts. Only words can be matched. Therefore, glossaries must
>>> be word based.
>>
>> Since I think glossaries are maintained by humans, the glossaries could be
>> concept based.
>
> I'm interested to know how a glossary server would match a concept (from
> the glossary) to a word (in the source text). Or... were you thinking
> of having a glossary server that doesn't perform any automatic matching
> of words from the source text?
If you have two concept entries (in the glossary you are querying)
that for the english have one given translation (for example the word
"horse") if you query that word ("horse") then the server returns the
two concept entries with all the translations for another given
language (for example galician, my language).
I accept your premise that word based glossaries are better for
translators, but for maintaining them (and for using TBX with is
concept oriented) I think is better the concept based choice.
>>> Isn't Martin Benjamin working on such a list via AnLoc?
>>> http://africanlocalisation.net/en/terminology
>>
>> Perhaps. In the last times there are lot of tools for translating,
>> maintaining TM, glossaries... Too much for me.
>
> No, the Anloc Terminology project is not a tool -- it is a list. It is
> a list of 2500 terms, to be translated into many African languages. If
> one can get one's hands on that list, it could be a useful start for a
> super list of GUI terms. Martin's list also has nothing to do with TM.
Interesting. This could be useful.
>> Yes, perhaps could do term editing, but if we set up a terminology server,
>> the term editing should be considered term suggestion that must be approved
>> by some user of the terminology server (a human).
>
> And this is why such a terminology server will fail. If users who add
> terms find that their expertise is not respected by the community, and
> that their contributions are regarded as second-rate until formally
> approved by some other guy, they will lose interest in participating.
I don't know how in other projects do the terminology stuff. We
discuss the translations in our mailing list, and yes, sometimes one
or two people disagree with the others, but we vote and one or more
translations are recommended.
In the server this would be equal. One translator suggest a new term
from the CAT tool (with some optional information: translation (one or
more), definition, where he found this...) to the server. Then the
users registered on the server could vote and discuss on this new
term, and after that the term could be rejected, or accepted without
changes, accepted with changes (adding other translation or
translations, changing other information). This includes the
possibility of a new term that the translator doesn't know how to
translate. Perhaps my description is not exhaustive...
>>> A way to judge a CAT tool's term recognition is (a) whether it can
>>> do fuzzy matching when doing glossary recognition...
>>
>> Where is "exact matching"? I think that in TMs "fuzzy matching" is very
>> important, but in glossaries it isn't so important.
>
> I did not mention exact matching because I assumed that exact matching
> is a given.
>
> Fuzzy matching can be important in glossaries if the glossary does not
> contain all possible permutations of a word from the source text. If
> the glossary contains "file" but not "files", will the CAT tool give a
> result if the source text contains "files"?
Yes, you are right. Without fuzzy matching this won't we very useful.
Bye,
Leandro Regueiro
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