✹✹ Stats & Graphs ✹✹

Tatoeba Stats, Graphs & Charts have been updated:
https://tatoeba.j-langtools.com/allstats/

Heureux anniversaire, Lisa ! 🎂

Hello, Tatoeba was updated today. What’s new?

- Some listings have been limited to display the last 1000 sentences: the list of sentences having audio, the list of sentences in user-created lists, and the list of sentences having a specific tag. Background on this new limitation: https://github.com/Tatoeba/tatoeba2/pull/3199

- It is now possible to use @ immediately followed by a username to notify a member in Wall posts. It was already possible to do so in sentence comments, but not in Wall posts. Now you can do it in both.

- The API served at https://api.tatoeba.org was improved. While it is still a work in progress, it is now close to become stable. Technical details: https://github.com/Tatoeba/tatoeba2/pull/3201

Interface improvements:

- Error pages (such as 404 error) can now be localized, thanks to the contribution of SrulyP: https://github.com/Tatoeba/tatoeba2/pull/3198 The error pages can be localized just like any other part of the website, for how to contribute, please look at https://en.wiki.tatoeba.org/art...ce-translation

- For sentences in Chinese, the converted simplified/traditional script is now displayed correctly. Details: https://github.com/Tatoeba/tatoeba2/issues/3188

- 52 language icons should look nicer. They have been vectorized, which means they won’t look pixelated no matter how much you zoom in. A total of 153 out of 429 language icons (35%) are now vectorized. Today, it is my honor to publish the vectorized brazilian/portuguese flag of our deeply regretted fellow member Ricardo.

Hey all! Wanted to share that recently I wrote some scripts that help find sentences to translate on based on lists of vocab. Taking as input the Tatoeba corpus and a tiered list of vocab (e.g. lists of words ranked by the chapters in which they appear in a textbook) as well as some limited grammar concepts (cases, parts of speech, verb forms, etc), it generates tiered lists of sentences such that the sentences at level N only use the vocab/grammar at level N or lower.

I've been working through a Russian textbook and using it to find sentences here that appropriate for attempting to translate into English/Spanish based on the chapter I'm on. My scripts use the spaCy Python library to rank sentences by chapter, and this library is sometimes flawed in terms of lemmatization and grammar annotation, but so far it has been a huge help for me. (Of course, my translation attempts can also be very flawed, as the Russian natives here know... thank you marafon, Ooneykcall and EugeneGS for your patience! :-) )

As an example, here are some sentences (as of the current data dumps) at chapter 10 level based on my book:

1006495 Да, у меня есть дочь.
1006500 Вы изучаете английский.
10074251 У нас всё свежее.
10101554 Вода слишком холодная.
10110989 Кофе слишком горячий.

And here are some at chapter 20 level:

10031177 Интересно, пойдёт ли снег.
10031179 Интересно, будет ли снег.
10038848 Ничего странного я в этом не вижу.
10043008 Я ушёл домой пешком.
10055872 Он бежал в школу.

Just wanted to share this info here in case any other learners would find this helpful for their own studies. Whether you intend to translate sentences found this way or not, it can be helpful for finding lots of example sentences at your level when working through a textbook. If this sounds useful to you, feel free to reply / send me a message and I'll be happy to try generating ranked translated/untranslated sentence lists for your choice of language too.

✹✹ Stats & Graphs ✹✹

Tatoeba Stats, Graphs & Charts have been updated:
https://tatoeba.j-langtools.com/allstats/