# Persian Rhetorical Structure Theory

arXiv: https://arxiv.org/abs/2106.13833 · HTML: https://mlsanity.com/paper/2106.13833/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 34 references that are in the map.
- First posted on arXiv 25 Jun 2021.

## Builds on (most cited first, 2 of 2)

- [Fast Rhetorical Structure Theory Discourse Parsing](https://mlsanity.com/paper/1505.02425/) (2015)
- [Two-pass Discourse Segmentation with Pairing and Global Features](https://mlsanity.com/paper/1407.8215/) (2014)

## Built on by (most cited first, 7 of 7)

- [GCDT: A Chinese RST Treebank for Multigenre and Multilingual Discourse Parsing](https://mlsanity.com/paper/2210.10449/) (2022)
- [Bridging Discourse Treebanks with a Unified Rhetorical Structure Parser](https://mlsanity.com/paper/2510.06427/) (2025)
- [DeDisCo at the DISRPT 2025 Shared Task: A System for Discourse Relation Classification](https://mlsanity.com/paper/2509.11498/) (2025)
- [CLaC at DISRPT 2025: Hierarchical Adapters for Cross-Framework Multi-lingual Discourse Relation Classification](https://mlsanity.com/paper/2509.16903/) (2025)
- [DiscoExplorer: An Open Interface for the Study of Multilingual Discourse Relations](https://mlsanity.com/paper/2605.15304/) (2026)
- [The Annotation Bottleneck in Persian Text NLP: Persian as an Annotation-Scarce Language](https://mlsanity.com/paper/2608.24698/) (2026)
- [Worth Their Weights? Evaluating Generative Models for Discourse Parsing](https://mlsanity.com/paper/2610.17658/) (2026)

## Abstract (arXiv)

Over the past years, interest in discourse analysis and discourse parsing has steadily grown, and many discourse-annotated corpora and, as a result, discourse parsers have been built. In this paper, we present a discourse-annotated corpus for the Persian language built in the framework of Rhetorical Structure Theory as well as a discourse parser built upon the DPLP parser, an open-source discourse parser. Our corpus consists of 150 journalistic texts, each text having an average of around 400 words. Corpus texts were annotated using 18 discourse relations and based on the annotation guideline of the English RST Discourse Treebank corpus. Our text-level discourse parser is trained using gold segmentation and is built upon the DPLP discourse parser, which uses a large-margin transition-based approach to solve the problem of discourse parsing. The performance of our discourse parser in span (S), nuclearity (N) and relation (R) detection is around 78%, 64%, 44% respectively, in terms of F1 measure.