Explore neural semantic parsing in this comprehensive lecture from CMU's Neural Networks for NLP course. Delve into graph-based parsing, minimum spanning tree parsing, and structured training techniques. Learn about dynamic programming methods for phrase structure parsing and reranking. Access accompanying slides and code examples to reinforce understanding of key concepts. Gain insights into semantic parsing approaches, including sequence-to-sequence models and tree-based parsing models. Examine various meaning representations such as first-order logic and Abstract Meaning Representation. Investigate syntax-driven semantic parsing, CCG parsing, and semantic role labeling with neural models.