RST-style Discourse Parsing Guided by Document-level Content Structures

• URL: http://arxiv.org/abs/2309.04141v1
• Date: Fri, 8 Sep 2023 05:50:27 GMT
• Title: RST-style Discourse Parsing Guided by Document-level Content Structures
• Authors: Ming Li, Ruihong Huang
• Abstract summary: Existing RST parsing pipelines construct rhetorical structures without the knowledge of document-level content structures. We propose a novel pipeline for RST-DP that incorporates structure-aware news content sentence representations.
• Score: 27.28989421841165
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Rhetorical Structure Theory based Discourse Parsing (RST-DP) explores how clauses, sentences, and large text spans compose a whole discourse and presents the rhetorical structure as a hierarchical tree. Existing RST parsing pipelines construct rhetorical structures without the knowledge of document-level content structures, which causes relatively low performance when predicting the discourse relations for large text spans. Recognizing the value of high-level content-related information in facilitating discourse relation recognition, we propose a novel pipeline for RST-DP that incorporates structure-aware news content sentence representations derived from the task of News Discourse Profiling. By incorporating only a few additional layers, this enhanced pipeline exhibits promising performance across various RST parsing metrics.

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