Reformulation and Equivalence of Bock's Algorithm for Exact Dependency Parsing
Yuxi Wang, Jungyeul Park
Abstract
Bock's algorithm provides a matrix-based alternative to Chu--Liu/Edmonds (CL/E) for exact dependency parsing. We present a reformulation that retains original node and arc identities through component labels, column adjustments, and star-and-bar transfers. In exact arithmetic, we prove operational equivalence to original Bock under matching scan and tie rules, and establish correspondence with corrected Tarjan under a prescribed component schedule. A separate analysis establishes optimal-value equivalence with Dozat-derived CL/E under the stated score and single-root conventions. We integrate reformulated Bock into a biaffine dependency parser and evaluate decoding and structured training on the Penn Treebank and Chinese Treebank. These results establish Bock as an alternative exact oracle for dependency parsing and structured training, while distinguishing equality of optimal values from identity of returned trees and training trajectories.