NLP algorithms for categorizing a list of words with specific topics
Extending the basic idea stated in comments by @krayyem, you are looking for an Ontology and/or Taxonomy. The short story is to (1) build them based on your data or (2) use existing ones.

Building from your data

You need lots of Is-A pairs which indicate what kind of thing the concept is e.g. Maradona is a football-player and football is a sport. For this purpose, you extract info from your text based on some patterns and update info then update pattern based on info and the loop goes on till it does not change anymore. see this answer though.

Solution you are probably looking for

Use existing knowledge bases that some of which are in Python e.g. wordnet. You can find more in the links I provided for the answer I linked above.

How to proceed kind of idea

Find the dominant keyword in the found keywords. You may simply just count and go through the concept graph (your ontology, the knowledge base) and find the parent concept. If the graph is not accessible in this form, you may create it yourself in Python with existing APIs and/or graph libraries in Python like Networkx.

If more input is needed please comment here. Good Luck!