Doc2vec(gensim) - How to calculate the most similar sentence and get its label?
As far as I understood you are using type of TV as tag of particular sentence , and you are using doc2vec model for future classification . So As above answer is suggesting that model will learn semantic meaning of type of TV(tag).
let's suppose s is your future sentence for prediction. then you use infer vector.

model = Load_model('model.doc2vec')
infer_vector = model.infer_vector(s)
similar_documents = model.docvecs.most_similar([infer_vector], topn = 1)

here similar document is list of tuples. where first element is label.
let me know if this help you.