Actually this _is_ about turning ContentTranslation off, that is what several users in the community want. They block people using the extension and delete the translated articles. Use of ContentTranslation has become a rather contentious case. Yandex as a general translation engine to be able to read some alien language is quite good, but as an engine to produce written text it is not very good at all. In fact it often creates quite horrible Norwegian, even for closely related languages. One quite common problem is reordering of words into meaningless constructs, an other problem is reordering lexical gender in weird ways. The English preposition "a" is often translated as "en" in a propositional phrase, and then the gender is added to the following phrase. That gives a translation of "Oppland is a county in…" into something like "Oppland er en fylket i…" This should be "Oppland er et fylke i…". (I just checked and it seems like Yandex messes up a lot less now than previously, but it is still pretty bad.) Apertium works because the language is closely related, Yandex does not work because it is used between very different languages. People try to use Yandex and gets disappointed, and falsely conclude that all language translations are equally weird. They are not, but Yandex translations are weird. The numerical threshold does not work. The reason is simple, the number of fixes depends on language constructs that fails, and that is simply not a constant for small text fragments. Perhaps if we could flag specific language constructs that is known to give a high percentage of failures, and if the translator must check those sentences. One such language construct is disappearances between the preposition and the gender of the following term in a prepositional phrase. If they are not similar, then the sentence must be checked. It is not always wrong to write "en jenta" in Norwegian, but it is likely to be wrong. A language model could be a statistical model for the language itself, not for the translation into that language. We don't want a perfect language model, but a sufficient language model to mark weird constructs. A very simple solution could simply be to mark tri-grams that does not already exist in the text base for the destination as possible errors. It is not necessary to do a live check, but at least do it before the page can be saved. Note the difference in what Yandex do and what we want to achieve; Yandex translates a text between two different languages, without any clear reason why. It is not to important if there are weird constructs in the text, as long as it is usable in "some" context. We translate a text for the purpose of republishing it. The text should be usable and easily readable in that language. On Tue, May 2, 2017 at 7:07 PM, Amir E. Aharoni < amir.aharoni(a)mail.huji.ac.il&gt; wrote:

Content translation with Yandex is also a problem in Bengali Wikipedia. Some users have grown a tendency to create machine translated meaningless articles with this extension to increase edit count and article count. This has increased the workloads of admins to find and delete those articles. Yandex is not ready for many languages and it is better to shut it. We don't need it in Bengali. Regards On May 3, 2017 12:17 AM, "John Erling Blad" &lt;jeblad(a)gmail.com&gt; wrote:

Creating machine translations only in the draft space (or in the user space in the projects which do not have draft) could help. Cheers Yaroslav On Tue, May 2, 2017 at 10:16 PM, Pharos &lt;pharosofalexandria(a)gmail.com&gt; wrote:

It is quite possible the Yandex people has done something as the translations are a lot better now than previously. It also imply that it is really important to correct the text inside CT. The question is how would we do it with our software. I simply cannot There are several places this can be inserted, both in VE and in MW. What I want is a kind of rather simple language model, but Aharoni proposed Languagetools in private communication. That lib is very interesting. Perhaps one day some AI/machine-learning system like ORES would be able to I've seen language models implemented as neural nets, but it is not necessary to do it like that. Actually it is more common to do it with plain statistics. On Tue, May 2, 2017 at 9:25 PM, Amir E. Aharoni < amir.aharoni(a)mail.huji.ac.il&gt; wrote: > 2017-05-02 21:47 GMT+03:00 John Erling Blad &lt;jeblad(a)gmail.com&gt;om>: > > > Yandex as a general translation engine to be able to read some alien > > language is quite good, but as an engine to produce written text it is > not > > very good at all. > > > ... Nor is it supposed to be. > > A translator is a person. Machine translation software is not a person, > it's software. It's a tool that is supposed to help a human translator > produce a good written text more quickly. If it doesn't make this work > faster, it can and should be disabled. If no translator > > > > In fact it often creates quite horrible Norwegian, even > > for closely related languages. One quite common problem is reordering of > > words into meaningless constructs, an other problem is reordering lexical > > gender in weird ways. The English preposition "a" is often translated as > > "en" in a propositional phrase, and then the gender is added to the > > following phrase. That gives a translation of "Oppland is a county in…" > > into something like "Oppland er en fylket i…" This should be "Oppland er > > et fylke i…". > > > > I suggest making a page with a list of such examples, so that the machine > translation developers could read it. > > > > (I just checked and it seems like Yandex messes up a lot less now than > > previously, but it is still pretty bad.) > > > > I guess that this is something that Yandex developers will be happy to hear > :) > > > > > The numerical threshold does not work. The reason is simple, the number > of > > fixes depends on language constructs that fails, and that is simply not a > > constant for small text fragments. Perhaps if we could flag specific > > language constructs that is known to give a high percentage of failures, > > and if the translator must check those sentences. One such language > > construct is disappearances between the preposition and the gender of the > > following term in a prepositional phrase. > > > > The question is how would we do it with our software. I simply cannot > > > > A language model could be a statistical model for the language itself, > not > > for the translation into that language. We don't want a perfect language > > model, but a sufficient language model to mark weird constructs. A very > > simple solution could simply be to mark tri-grams that does not already > > exist in the text base for the destination as possible errors. It is not > > necessary to do a live check, but at least do it before the page can be > > saved. > > > > See above—we don't have support for plugging something like that into our > workflow. > > Perhaps one day some AI/machine-learning system like ORES would be able to > > > > Note the difference in what Yandex do and what we want to achieve; Yandex > > translates a text between two different languages, without any clear > reason > > why. It is not to important if there are weird constructs in the text, as > > long as it is usable in "some" context. We translate a text for the > purpose > > of republishing it. The text should be usable and easily readable in that > > language. > > > > This is a well-known problem in machine translation: domain. > > Professional industrial translation powerhouses use internally-customized > machine translation engines that specialize on particular domains, such as > medicine, law, or news. In theory, it would make a lot of sense to have a > customized machine translation engine for encyclopedic articles, or maybe > even for several different styles of encyclopedic articles (biography, > science, history, etc.). For now what we have is a very general-purpose > consumer-oriented engine. I hope it changes in the future. > _______________________________________________ > Wikimedia-l mailing list, guidelines at: https://meta.wikimedia.org/ > wiki/Mailing_lists/Guidelines and https://meta.wikimedia.org/ > wiki/Wikimedia-l > New messages to: Wikimedia-l(a)lists.wikimedia.org > Unsubscribe: https://lists.wikimedia.org/mailman/listinfo/wikimedia-l, > <mailto:wikimedia-l-request@lists.wikimedia.org?subject=unsubscribe> >

Perhaps it would be a good idea to compare the translated text to the text that the user wants to save. If they are more than 95% the same, that means that the user didn't take the effort to correct the text. Cheers, Micru On Wed, May 3, 2017 at 10:31 AM, Wojciech Pędzich &lt;wpedzich(a)gmail.com&gt; wrote: -- Etiamsi omnes, ego non

Note that some language pairs could easily be 100% correct. On Wed, May 3, 2017 at 1:06 PM, David Cuenca Tudela &lt;dacuetu(a)gmail.com&gt; wrote:

Hello, This seems to me like a social problem, rather than a technical one. Shutting down the tool would be a disadvantage for those people who benefit from the tool and do good things with it. What is the general opinion among the Norwegians about this issue? Is there consent about how to deal with this kind of "articles"? If most people agree they should be speedy-deleted, this would be a useful deterrence for those who are not careful enough when using the tool? Kind regards Ziko 2017-05-03 13:22 GMT+02:00 John Erling Blad &lt;jeblad(a)gmail.com&gt;om>:

My idea was that adding an extra button to press brings the probability of the whole process down. If someone is determine to systemically add bad machine translations to the main namespace I guess only blocks could help. On the other hand, and extra button gives at leat an opportunity to read the result and reflect on it. Cheers Yaroslav