2018-06-18 2:12 GMT+03:00 Olya Irzak <oirzak(a)gmail.com>om>:
Dear Wikidata community,
We're working on a project called Wikibabel to machine-translate parts of
Wikipedia into underserved languages, starting with Swahili.
In hopes that some of our ideas can be helpful to machine translation
projects, we wrote a blogpost about how we prioritized which pages to
translate, and what categories need a human in the loop:
https://medium.com/@oirzak/wikibabel-equalizing-information-access-on-a-
budget-4038f750e90e
Rumor has it that the Wikidata community has thought deeply about
information access. We'd love your feedback on our work. Please let us know
about past / ongoing machine translation related projects so we can learn
from & collaborate with them.
I'm not sure how has the Wikidata community think deeply about it.
One project that does something related to what you're doing is GapFinder (
https://www.mediawiki.org/wiki/GapFinder ). As far as I know, the GapFinder
frontend is not developed actively, but the recommendation API behind it is
being actively maintained and developed, but you should ask the Research
team for more info (see
https://www.mediawiki.org/wiki/Wikimedia_Research ).
Project Tiger is also doing something similar:
https://meta.wikimedia.org/wiki/Project_Tiger_Editathon_2018
As a general comment, displaying machine-translated text in a way that
appears that is had been written by humans is misleading and damaging. I
don't know any Swahili, but in languages that I can read (Russian, Hebrew,
Catalan, Spanish, French, German), the quality of machine translation is at
its best good as an aid during writing a translation by a human, and it's
never good for actually reading. I also don't understand why do you invest
credits into pre-machine-translating articles that people can
machine-translate for free, but maybe I'm missing something about how your
project works.