1 INTRODUCTION

2 KNOWLEDGE SOURCE
2.1 Linguistic Knowledge
2.2 Encyclopedia Knowledge
2.3 Commonsense Knowledge
2.4 Application/Domain Specific Knowledge

3 KNOWLEDGE GRANULARITY
3.1 Text Chunk-based Knowledge
3.2 Entity Knowledge
3.3 Relation Knowledge
3.4 Subgraph Knowledge

4 APPLICATIONS
4.1 Text Generation
4.2 Entity-related Tasks
4.3 Question Answering
4.4 Knowledge Graph Completion
4.5 Sentiment Analysis Tasks

5 CHALLENGES AND FUTURE DIRECTIONS
5.1 Exploring More Applications
5.2 Exploring More Knowledge Sources
5.3 Integrating Complex Knowledge More Effectively
5.4 Optimizing Computational Burden
5.5 Noise Resilient KE-PLMs
5.6 Upper Bound Study

6 CONCLUSION