@inproceedings{ruiz-dolz-etal-2023-automatic,
title = "Automatic Debate Evaluation with Argumentation Semantics and Natural Language Argument Graph Networks",
author = "Ruiz-Dolz, Ramon and
Heras, Stella and
Garcia, Ana",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-main.368",
doi = "10.18653/v1/2023.emnlp-main.368",
pages = "6030--6040",
abstract = "The lack of annotated data on professional argumentation and complete argumentative debates has led to the oversimplification and the inability of approaching more complex natural language processing tasks. Such is the case of the automatic evaluation of complete professional argumentative debates. In this paper, we propose an original hybrid method to automatically predict the winning stance in this kind of debates. For that purpose, we combine concepts from argumentation theory such as argumentation frameworks and semantics, with Transformer-based architectures and neural graph networks. Furthermore, we obtain promising results that lay the basis on an unexplored new instance of the automatic analysis of natural language arguments.",
}
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%0 Conference Proceedings
%T Automatic Debate Evaluation with Argumentation Semantics and Natural Language Argument Graph Networks
%A Ruiz-Dolz, Ramon
%A Heras, Stella
%A Garcia, Ana
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F ruiz-dolz-etal-2023-automatic
%X The lack of annotated data on professional argumentation and complete argumentative debates has led to the oversimplification and the inability of approaching more complex natural language processing tasks. Such is the case of the automatic evaluation of complete professional argumentative debates. In this paper, we propose an original hybrid method to automatically predict the winning stance in this kind of debates. For that purpose, we combine concepts from argumentation theory such as argumentation frameworks and semantics, with Transformer-based architectures and neural graph networks. Furthermore, we obtain promising results that lay the basis on an unexplored new instance of the automatic analysis of natural language arguments.
%R 10.18653/v1/2023.emnlp-main.368
%U https://aclanthology.org/2023.emnlp-main.368
%U https://doi.org/10.18653/v1/2023.emnlp-main.368
%P 6030-6040
Markdown (Informal)
[Automatic Debate Evaluation with Argumentation Semantics and Natural Language Argument Graph Networks](https://aclanthology.org/2023.emnlp-main.368) (Ruiz-Dolz et al., EMNLP 2023)
ACL