Discourse Segmentation

13 papers with code • 0 benchmarks • 4 datasets

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Most implemented papers

Two-pass Discourse Segmentation with Pairing and Global Features

arne-cl/feng-hirst-rst-parser 30 Jul 2014

Previous attempts at RST-style discourse segmentation typically adopt features centered on a single token to predict whether to insert a boundary before that token.

Cross-lingual and cross-domain discourse segmentation of entire documents

chloebt/discourse 13 Apr 2017

Discourse segmentation is a crucial step in building end-to-end discourse parsers.

Does syntax help discourse segmentation? Not so much

chloebt/discourse EMNLP 2017

Discourse segmentation is the first step in building discourse parsers.

Toward Fast and Accurate Neural Discourse Segmentation


Discourse segmentation, which segments texts into Elementary Discourse Units, is a fundamental step in discourse analysis.

From News to Medical: Cross-domain Discourse Segmentation

elisaF/news-med-segmentation WS 2019

The first step in discourse analysis involves dividing a text into segments.

GumDrop at the DISRPT2019 Shared Task: A Model Stacking Approach to Discourse Unit Segmentation and Connective Detection

gucorpling/GumDrop WS 2019

In this paper we present GumDrop, Georgetown University's entry at the DISRPT 2019 Shared Task on automatic discourse unit segmentation and connective detection.

Text Segmentation by Cross Segment Attention

aakash222/text-segmentation-NLP EMNLP 2020

Document and discourse segmentation are two fundamental NLP tasks pertaining to breaking up text into constituents, which are commonly used to help downstream tasks such as information retrieval or text summarization.

Joint Learning of Syntactic Features Helps Discourse Segmentation

takshakpdesai/discourse-segmenter LREC 2020

This paper describes an accurate framework for carrying out multi-lingual discourse segmentation with BERT (Devlin et al., 2019).

Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading

Yifan-Gao/Discern EMNLP 2020

Based on the learned EDU and entailment representations, we either reply to the user our final decision "yes/no/irrelevant" of the initial question, or generate a follow-up question to inquiry more information.

Open-Retrieval Conversational Machine Reading

yifan-gao/open_retrieval_conversational_machine_reading 17 Feb 2021

On our created OR-ShARC dataset, MUDERN achieves the state-of-the-art performance, outperforming existing single-passage conversational machine reading models as well as a new multi-passage conversational machine reading baseline by a large margin.