Getting answers to bullets (numbered items) from text via NLP
If we want to search for What are the steps to create a website, all you need to do is the find which set of bulleted points is going to answer that. One thing that you can try is that you can vectorize your question using some pretrained model (w2v, GloVe etc) and also encode the descriptions before the bulleted list ( For eg : How to create a website). Once you have the query vector $q$ and the descriptions vectors $d1, d2, d3,..., dn$ , you can perform cosine similarity of the query vector with all the description vectors and choose the description with the maximum similarity. Following this, the corresponding bullet points will be the answer.