1. Introduction
2. Terminology Definition
2.1. Three Conceptual Layers about Story
2.2. Generative Language Model
2.3. Structured Knowledge
3. Integrating Structured Knowledge Into Story Generation: A Taxonomy
3.1. Structured Knowledge As Text
3.2. Structured Knowledge As Encoding
3.3. Summing Up
4. Knowledge-related Operations
4.1. Transforming Triples to Sentences
4.2. Extracting Keywords, Keyphrases, and Events
4.3. Building Knowledge Subgraphs
5. Datasets
5.1. Story Corpora
5.2. Structured Knowledge Datasets
6. Evaluation Metrics
6.2. Neural Network-based Evaluation Metrics
6.3. Manual Evaluation Metrics
7. Discussion on Challenges
7.1. Limitation of PLMs for Storytelling
7.2. Limitation of Knowledge Sources
7.4. Limitation on Controllability
7.5. Limitation on Commonsense Inference
7.6. Limitations of Automatic Evaluation Metrics
8. Future Directions
8.1. Non-text Storytelling
8.2. Different Narrative Techniques
8.3. Collaborative Storytelling
8.4. Generating Long Stories
9. Conclusion