Lecture
This lecture covers syntactic parsing, dependency grammar, and graph-based neural network parsing. It discusses the importance of sentence structure, attachment ambiguities, and coordination scope ambiguity. The instructor explains the history of dependency structure, the rise of annotated data, and different methods of dependency parsing. The lecture also delves into projectivity, transition-based parsing, and the use of neural networks in parsing. It concludes with a summary of syntactic structure and the advancements in graph-based dependency parsing.