In an article that I am writing, I focus on word classification. A typical task that involves word classification is (named) entity recognition. Entity recognition is a rather broad task and seems to cover other sub-tasks as well.
Therefore, it seems fair to me to use the terms interchangeably.
Is this a fair assumption?
Is this a fair assumption?
No: Named Entity Recognition (NER) is a specific task which consists in detecting named entities. The more general term for this kind of task in Machine Learning is sequence labelling, because it's not only about classifying words but annotating a sequence of instances in which order matters (e.g. words).
It's true that NER is certainly the most famous task of this kind, but there are other important ones, for instance Part-Of-Speech (POS) tagging.
