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    <abstract>RST-based discourse parsing is an important NLP task with numerous downstream applications, such as summarization, machine translation and opinion mining. In this paper, we demonstrate a simple, yet highly accurate discourse parser, incorporating recent contextual language models. Our parser establishes the new state-of-the-art (SOTA) performance for predicting structure and nuclearity on two key RST datasets, RST-DT and Instr-DT. We further demonstrate that pretraining our parser on the recently available large-scale “silver-standard” discourse treebank MEGA-DT provides even larger performance benefits, suggesting a novel and promising research direction in the field of discourse analysis.</abstract>
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%0 Conference Proceedings
%T Unleashing the Power of Neural Discourse Parsers - A Context and Structure Aware Approach Using Large Scale Pretraining
%A Guz, Grigorii
%A Huber, Patrick
%A Carenini, Giuseppe
%Y Scott, Donia
%Y Bel, Nuria
%Y Zong, Chengqing
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F guz-etal-2020-unleashing
%X RST-based discourse parsing is an important NLP task with numerous downstream applications, such as summarization, machine translation and opinion mining. In this paper, we demonstrate a simple, yet highly accurate discourse parser, incorporating recent contextual language models. Our parser establishes the new state-of-the-art (SOTA) performance for predicting structure and nuclearity on two key RST datasets, RST-DT and Instr-DT. We further demonstrate that pretraining our parser on the recently available large-scale “silver-standard” discourse treebank MEGA-DT provides even larger performance benefits, suggesting a novel and promising research direction in the field of discourse analysis.
%R 10.18653/v1/2020.coling-main.337
%U https://aclanthology.org/2020.coling-main.337
%U https://doi.org/10.18653/v1/2020.coling-main.337
%P 3794-3805

Markdown (Informal)

[Unleashing the Power of Neural Discourse Parsers - A Context and Structure Aware Approach Using Large Scale Pretraining](https://aclanthology.org/2020.coling-main.337) (Guz et al., COLING 2020)

• Unleashing the Power of Neural Discourse Parsers - A Context and Structure Aware Approach Using Large Scale Pretraining (Guz et al., COLING 2020)

ACL

• Grigorii Guz, Patrick Huber, and Giuseppe Carenini. 2020. Unleashing the Power of Neural Discourse Parsers - A Context and Structure Aware Approach Using Large Scale Pretraining. In Proceedings of the 28th International Conference on Computational Linguistics, pages 3794–3805, Barcelona, Spain (Online). International Committee on Computational Linguistics.