Unsupervised Discourse Constituency Parsing Using Viterbi EM
In this paper, we introduce an unsupervised discourse constituency parsing algorithm. We use Viterbi EM with a margin-based criterion to train a span-based discourse parser in an unsupervised manner. We also propose initialization methods for Viterbi training of discourse constituents based on our prior knowledge of text structures. Experimental results demonstrate that our unsupervised parser achieves comparable or even superior performance to fully supervised parsers. We also investigate discourse constituents that are learned by our method.
Code (1)
Tasks
Constituency ParsingDiscourse ParsingSimilar Papers 제목 키워드 기반
A Dependency Perspective on RST Discourse Parsing and Evaluation
Computational text-level discourse analysis mostly happens within Rhetorical Structure Theory (RST), whose structures have classically been presented as constituency trees, and relies on data from the RST Discourse Treeb…
Constituency ParsingDependency ParsingDiscourse ParsingJoint Syntacto-Discourse Parsing and the Syntacto-Discourse Treebank
Discourse parsing has long been treated as a stand-alone problem independent from constituency or dependency parsing. Most attempts at this problem are pipelined rather than end-to-end, sophisticated, and not self-contai…
Dependency ParsingDiscourse ParsingA Conditional Splitting Framework for Efficient Constituency Parsing
We introduce a generic seq2seq parsing framework that casts constituency parsing problems (syntactic and discourse parsing) into a series of conditional splitting decisions. Our parsing model estimates the conditional pr…
Constituency ParsingDiscourse ParsingDiscourse SegmentationSegmentationLinear-Time Constituency Parsing with RNNs and Dynamic Programming
Recently, span-based constituency parsing has achieved competitive accuracies with extremely simple models by using bidirectional RNNs to model "spans". However, the minimal span parser of Stern et al (2017a) which holds…
Boundary DetectionConstituency ParsingDiscourse ParsingSentenceStructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling
There are two major classes of natural language grammar -- the dependency grammar that models one-to-one correspondences between words and the constituency grammar that models the assembly of one or several corresponded …
Constituency ParsingDependency ParsingLanguage ModelingLanguage Modelling+2