When I use terms.teach with English words, it works very well, very quickly suggesting to me relevant words in the web app.
e.g. using the follwing code brings up the web server and I get many food related terms
python -m prodigy dataset food_seeds_en "seeds for foods english"
python -m prodigy terms.teach food_seeds_en en_core_web_lg --seeds "carrot, spinach, pasta, soba, udon, pizza, Bibimbap, gyudon"
However, when I do the same but using the Japanese language model and Japanese language seeds, all the terms shown to me in the web app (as shown below) are in latin letters not Japanese words. Why am I getting these results? Is the language model not registering properly?
python -m prodigy dataset food_seeds "seeds for foods"
python -m prodigy terms.teach food_seeds ja_core_news_lg --seeds "人参, ほうれん草, パスタ, そば, うどん, ピザ, ビビンバ, 牛丼"