Please pardon me as the title might not be very accurate
I am trying to create a model that learns the word representation and then is able to predict word representation in another piece of text. An example will make it more clear. Please see below for the example:
Model Training Text:
I lived in *Munich last summer. *Germany has a relaxing, slow summer lifestyle. One night, I got food poisoning and couldn't find !Tylenol to make the pain go away, they insisted I take !aspirin instead.
When I lived in Paris last year, France was experiencing a recession. The nightlife was too fun, I developed an addiction to Adderall and Ritalin.
The question is that what sort of NLP technique will be helpful in such a case. I don't even know what are these kind of problems called. Can you please tell what are these problems called?
One approach I can think of is to train the
Embedding Layer to predict the position of
* will be prefixed to the name of the country and
! will be prefixed to the name of the drug but my challenge is that how can I structure my data for such training. Is it a feasible approach?
Is there any resource/material I can refer to and draw the inspiration from?
I would very much appreciate any help or suggestions. Thanks a lot in advance.