Which machine learning problem is this? I am not able to figure out what kind of machine learning is this:
Training set: consists of sentences with object labels for object phrases
Example:
&quot;This is a black chair. It is next to a large bed.&quot;

Phrases 'This', 'black chair', 'it' were annotated with the label &quot;chair&quot; and phrase 'large bed' was annotated with the label 'bed'. There are 18 available labels that can be assigned.
For an unannotated sentence, I want to predict the labels for each phrase in the sentence.
For example:
There is a study table in the corner of the room, behind it is a small chair.

I would like the model to predict a label (available 18 labels) for each phrase that represents an object in the above sentence.
Expected output:
'study table', 'it' -----&gt; label 'table'

'small chair' -----------&gt; label 'chair'

Is this a classification, regression, or a different kind of problem?
Technically this is sequence labeling, the most common application being Named Entity Recognition.
However it looks like in this case you're trying to solve a problem of coreference resolution, which is a quite difficult task in general. I think this usually involves a more complex model than simple sequence labeling, but I'm not an expert in this. You might want to search around this topic, there are certainly some relevant papers and tools about it.