Hi all,
I’ve recently started into the NLP world, so this might seem like an obvious question but are there models to generate tags from text? E.g. lets say you have a corpus of text describing houses and you would like to retrieve the house type, size and color. The goal would be to get an output like this for every house description {house_type: ‘apartment’, size: ‘1000sqft’, color: ‘grey’}
It seems that question answering model are able to understand that information (or at least answer to one of the questions at a time), but I’m not sure if there’s a way to adapt these for the above task.
It seems to me that it could be pretty useful to train other models (e.g. vision) in a self-supervised way (e.g. get the house type size and color from a house photo using the output of the model above as target variable)
Thanks!
Elliot