Given a large set of short sentences (around 20-30 words) and multi label task (around 100 labels , can be to 3 labels per sentences ).
The location of each annotation is not impotent (i.e i only need to know if the annotation is included in the sentence)
Which method will be more beneficial ? using NER models with labels attached to the tokens from each sentence, or text classification where the sample is the whole sentence .
The labels are action that physician is doing (i.e "clean wound" , "remove skin" etc)