@inproceedings{lambropoulos-ishihara-2024-towards,
title = "Towards an Implementation of {R}hetorical {S}tructure {T}heory in Discourse Coherence Modelling",
author = "Lambropoulos, Michael and
Ishihara, Shunichi",
editor = "Baldwin, Tim and
Rodr{\'i}guez M{\'e}ndez, Sergio Jos{\'e} and
Kuo, Nicholas",
booktitle = "Proceedings of the 22nd Annual Workshop of the Australasian Language Technology Association",
month = dec,
year = "2024",
address = "Canberra, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.alta-1.1/",
pages = "1--11",
abstract = "In this paper, we combine the discourse coherence principles of Elementary Discourse Unit segmentation and Rhetorical Structure Theory parsing to construct meaningful graph-based text representations. We then evaluate a Graph Convolutional Network and a Graph Attention Network on these representations. Our results establish a new benchmark in F1-score assessment for discourse coherence modelling while also showing that Graph Convolutional Network models are generally more computationally efficient and provide superior accuracy."
}
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%0 Conference Proceedings
%T Towards an Implementation of Rhetorical Structure Theory in Discourse Coherence Modelling
%A Lambropoulos, Michael
%A Ishihara, Shunichi
%Y Baldwin, Tim
%Y Rodríguez Méndez, Sergio José
%Y Kuo, Nicholas
%S Proceedings of the 22nd Annual Workshop of the Australasian Language Technology Association
%D 2024
%8 December
%I Association for Computational Linguistics
%C Canberra, Australia
%F lambropoulos-ishihara-2024-towards
%X In this paper, we combine the discourse coherence principles of Elementary Discourse Unit segmentation and Rhetorical Structure Theory parsing to construct meaningful graph-based text representations. We then evaluate a Graph Convolutional Network and a Graph Attention Network on these representations. Our results establish a new benchmark in F1-score assessment for discourse coherence modelling while also showing that Graph Convolutional Network models are generally more computationally efficient and provide superior accuracy.
%U https://aclanthology.org/2024.alta-1.1/
%P 1-11
Markdown (Informal)
[Towards an Implementation of Rhetorical Structure Theory in Discourse Coherence Modelling](https://aclanthology.org/2024.alta-1.1/) (Lambropoulos & Ishihara, ALTA 2024)
ACL