Neural Generative Rhetorical Structure Parsing

Understand

Rhetorical structure trees have been shown to be useful for several document-level tasks including summarization and document classification.

• Previous approaches to RST parsing have used discriminative models; however, these are less sample efficient than generative models, and RST parsing datasets are typically small.
• In this paper, we present the first generative model for RST parsing.
• Our model is a document-level RNN grammar (RNNG) with a bottom-up traversal order.