While not everyone will have the same workflow, I think it is good practice to split all possible values into different fields. For example, in Canada, some federally generated data has attribute tables where toponyms appear for both official languages. They are split into two fields, which makes searching for entities much easier.
I would advise to split the fields. Joining will be much easier, and searching the data will also be simplified. If your csv always uses the same language, you might want to extract only the matching value in your field. For this you can use the method described here and repeat it until your string is split in the required fields.
I took a look at your data and the number of entities is relatively low, which makes it realistic to fix them. To split the values into new fields, go to the field calculator and use those two expressions (replacing "Test" with your own field).
The first one isolates the first substring before the '|' character while the second one will isolate the rest of the string after the first '|'. Just repeat the second one on every new split field until you have no vertical slashes left.
You'll probably have to manually copy the values you want in a new field because the languages aren't all the same but it'll work for this small entity number.