Assign sentences to their respective topics using LDA

Is there a way to find out what sentences fall under which topic detected using Latent Dirichlet Allocation (LDA)?

Assume I have already used LDA to extract topics. Now I want to determine which sentences in my document (single document) fall under these topics (let's say top 5 or 10 topics). How do I do that?

I'm using gensim library for LDA.

Also, Would applying LDA separately on each sentence of the document yield different results (i.e. topics extracted) from if I applied LDA to the whole document?

Is LDA on sentences equivalent to LDA on documents? The answer here is no. In deciding what topic each word of the corpus comes from, LDA inference algos borrow information from what other words are in the corpus through a parameter (denoted by $$\theta$$ in the original LDA paper) which gives the topic prevalence for each document. Therefore, doing LDA with each sentence being considered its own document will give a different result, since sentences won't "borrow strength" from one another. I would conjecture that you will get a somewhat similar result, but it won't be the same. Further, standard LDA inference algos have difficulty with short documents (such as tweets, which are sometimes aggregated so as to have longer docs, see e.g. this article), so you may see some degradation in the quality of the results.