approach for multi label text classification
So, you are asking about how to develop this system / model, which can classify text. 
Yes, it is a great idea to instantiate a "baseline" or dummy model, which can be rule-based or randomly assigns a label to a certain piece of text.
From this dummy model, yes you can then use RNN/LSTMs that does multiple-inputs (e.g. words in text) to single output probability over classes as a more sophisticated model and yes you would then compare the validation and test accuracy, F1-score, etc. to see if that improvement to the model is warranted by the change in the model's functionality to classify the texts.