Hi Eliot,
If this information is explicitly available in the text then you can try to achieve this with a QA model. Asking questions like “What is the house type ?”, “What’s the color of the house ?” etc.
There are other methods for such type of semantic parsing tasks, but one way you can approach this using  is using text2text approach with T5 (it’s seq-to-seq model where you can feed in some text and ask the model to output some text). i.e given your text you can train T5  to output a structured text, something like
house_type: apartment <sep> color: grey <sep> house_size: 1000
This might be a overkill but I tried this as a experiment in my work and so far it’s doing really well.
One other approach would be to frame this as an entity extraction task, you entities will be house_type, color and size. Something like spacy could really help. If you are new to Entity extraction see this demo 9 to get an idea