Knowledge Bases (also known as knowledge graphs or ontologies) are valuable resources for developing intelligence applications, including search, question answering, and recommendation systems. The goal of Knowledge Base Population is discovering facts about entities (NER, NEL) and building a knowledge base with it.
There is often an Inference Engine to complement the Knowledge Base. Together they can be seen as an Expert System. The Knowledge Base represents facts and rules. The Inference Engine applies the rules or AI model to the known facts to deduce new facts.
This article is part of the project Periodic Table of NLP Tasks. Click to read more about the making of the Periodic Table and the project to systemize NLP tasks.