Semantic Dependency Parsing via Book Embedding

Abstract

We model a dependency graph as a book, a particular kind of topological space, for semantic dependency parsing.The spine of the book is made up of a sequence of words, and each page contains a subset of noncrossing arcs.To build a semantic graph for a given sentence, we design new Maximum Subgraph algorithms to generate noncrossing graphs on each page, and a Lagrangian Relaxation-based algorithm to combine pages into a book.Experiments demonstrate the effectiveness of the book embedding framework across a wide range of conditions.Our parser obtains comparable results with a state-of-the-art transition-based parser.