Essence of Factual Knowledge

TL;DR

This paper explores how extracting patterns and essential facts from large knowledge bases can reduce their size while maintaining their relevance and usefulness for inference.

Contribution

It introduces a method to identify and extract core patterns and essential facts to minimize knowledge bases without losing critical information.

Findings

Knowledge bases show strong relation patterns within topics.

Pattern extraction can effectively reduce KB size.

Essential facts retain inference capabilities after minimization.

Abstract

Knowledge bases are collections of domain-specific and commonsense facts. Recently, the sizes of KBs are rocketing due to automatic extraction for knowledge and facts. For example, the number of facts in WikiData is up to 974 million! According to our observation, current KBs, especially domain KBs, show strong relevance in relations according to some topics. These patterns can be used to conclude and infer for part of facts in the KBs. Therefore, the original KBs can be minimzed by extracting patterns and essential facts.