Ambiguous Question Answering over Knowledge Graph refers to the task of accurately retrieving and interpreting answers from a knowledge graph in response to queries that are unclear or have multiple potential meanings. This process involves addressing the challenges posed by ambiguous language, which can lead to uncertainty in the interpretation of query intent. To overcome these challenges, advanced techniques such as semantic analysis, context understanding, and query reformulation are employed. By combining symbolic structural information from the knowledge graph with neural network models, we aim to clarify queries and find the most relevant and accurate answers. This chapter explores the application of neural-symbolic reasoning methods to resolve ambiguous questions effectively.