Where/how to find sentences from your native language (or English) into your target language, and quickly create flashcards out of it (with Anki or another software) ?

I want to create flashcards with my native language (or English) sentence on the front, and the corresponding target language sentence on the back of the card. I prefer sentences, instead of single words. I noticed over time that I remember and understand better like that.

I study a STEM degree, so don't have much free time, and find it time consuming to create my own sentences in English (or my native language), then having to translate each single sentence into my target language with DeepL/Google Translate, and then having to copy/paste each single sentence into my Anki deck.

While browsing through old Reddit posts, I saw some users suggest taking sentences from a book/website instead of translating them. This idea makes sense, but 1) I would first need to find a good database/PDF where to find those sentences and 2) find a quick and efficient way to create Anki flashcards out of it.

I know about Tatoeba.org, but when downloading a list of sentences, there are many redundant sentences. It seems possible to create a python script (with help from ChatGPT) to filter out duplicate sentences in English/your native language, while keeping the several different target language translations and then import the file into Anki (so in Anki it would look like this: Front Card: sentence in English. Back Card: all the different target languages translations)

I also found an Anki deck on AnkiWeb with over 15'000 sentences from English into my target language. https://ankiweb.net/shared/info/1713927804 Some people in the comments/reviews of the deck say there are some translation mistakes, but for now, aside of a tendency to use more formal pronouns, I haven't found mistakes.

I just wonder if someone here found something else, or better/more efficient, for someone in my situation, so I can save time. There are surely some people here who faced similar issues and found a neat/efficient solution.

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