Just to elaborate my brief comment on the question:
Identifying the primary concepts of a paragraph required understanding of the meaning of the text. In natural language processing we are still a long way off even recognising and representing the meaning of text, let alone summarising the meaning of multiple sentences into a single statement.
Note that this is different from simply summarising a text: this can be done without any understanding based on textual features within the text itself, and ways of doing that have been around for a while. But such approaches will generally remove sentences which seem less relevant to the text, thus shortening it. They will not express the content in different words.
Conceivably people might try this with deep learning, where you train a system with paragraphs and the corresponding concepts, but again such a system would not have any understanding of the meaning, and thus results would be more or less accidental.