NER vs Text classification for very short sentences
Using NER (more generally sequence labeling) means classifying every token in the sentence, so if the goal is only to label every sentence there's no strong need for it in your case.

However NER might be more appropriate in case the order of the words is important, because sequence labeling models take it into account whereas traditional text classification methods often use a "bag of words" representation (order doesn't matter).

To some extent it also depends whether the labels are always related to a particular term in the sentence: if yes, then NER might be better at locating these terms (this is related to the point about order). If no, then classifying at the level of sentences is likely to perform better.