CLFLNov 1, 2020

A Unifying Theory of Transition-based and Sequence Labeling Parsing

arXiv:2011.00584v1996 citations
Originality Incremental advance
AI Analysis

This work provides a unifying framework for parsing researchers, though it is incremental as it builds on existing transition-based parsers.

The paper establishes a theoretical mapping between transition-based and sequence-labeling parsing, enabling new encodings for fast parsing, and demonstrates this in dependency parsing with four algorithms achieving comparable performance to existing methods.

We define a mapping from transition-based parsing algorithms that read sentences from left to right to sequence labeling encodings of syntactic trees. This not only establishes a theoretical relation between transition-based parsing and sequence-labeling parsing, but also provides a method to obtain new encodings for fast and simple sequence labeling parsing from the many existing transition-based parsers for different formalisms. Applying it to dependency parsing, we implement sequence labeling versions of four algorithms, showing that they are learnable and obtain comparable performance to existing encodings.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes