Discourse Parsing
56 papers with code • 4 benchmarks • 10 datasets
Most implemented papers
Fast Rhetorical Structure Theory Discourse Parsing
In recent years, There has been a variety of research on discourse parsing, particularly RST discourse parsing.
The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error
Our results not only motivate our proposal and help us to understand its limitations, but also provide insight on the properties of discourse models and datasets which improve performance in domain adaptation.
A Unified Linear-Time Framework for Sentence-Level Discourse Parsing
We propose an efficient neural framework for sentence-level discourse analysis in accordance with Rhetorical Structure Theory (RST).
ABCD: A Graph Framework to Convert Complex Sentences to a Covering Set of Simple Sentences
On DeSSE, which has a more even balance of complex sentence types, our model achieves higher accuracy on the number of atomic sentences than an encoder-decoder baseline.
Multi-view and multi-task training of RST discourse parsers
We experiment with different ways of training LSTM networks to predict RST discourse trees.
Cross-lingual RST Discourse Parsing
Discourse parsing is an integral part of understanding information flow and argumentative structure in documents.
The CLaC Discourse Parser at CoNLL-2015
This paper describes our submission (kosseim15) to the CoNLL-2015 shared task on shallow discourse parsing.
Joint 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.