If I translate the following sentence in DeepL from French to English…
La crise liée à la COVID-19 a creusé les inégalités préexistantes.
… I get the following translation:
The VIDOC-19 crisis has deepened pre-existing inequalities.
1- If I click the proposed word “VIDOC-19”, I can get other suggestions like “COVID-19”.
2- If I change the word “pre-existing” to say “already”, it changes the next part of the translation accordingly.
I understand that “1” can be done by word alignment and “2” can be done by something like lexical constraints. My question: is it possible to apply 1 and 2 with OpenNMT (either py or tf) without changing the code?
Thanks and regards,