@inproceedings{gemechu-etal-2025-open,
title = "The Open Argument Mining Framework",
author = "Gemechu, Debela and
Ruiz-Dolz, Ramon and
G{\'o}rska, Kamila and
Moslemnejad, Somaye and
Maguire, Eimear and
Zografistou, Dimitra and
Jo, Yohan and
Lawrence, John and
Reed, Chris",
editor = "Mishra, Pushkar and
Muresan, Smaranda and
Yu, Tao",
booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.acl-demo.31/",
doi = "10.18653/v1/2025.acl-demo.31",
pages = "318--328",
ISBN = "979-8-89176-253-4",
abstract = "Despite extensive research in Argument Mining (AM), the field faces significant challenges in limited reproducibility, difficulty in comparing systems due to varying task combinations, and a lack of interoperability caused by the heterogeneous nature of argumentation theory. These challenges are further exacerbated by the absence of dedicated tools, with most advancements remaining isolated research outputs rather than reusable systems. The $\texttt{oAMF}$ (Open Argument Mining Framework) addresses these issues by providing an open-source, modular, and scalable platform that unifies diverse AM methods. Initially released with seventeen integrated modules, the $\texttt{oAMF}$ serves as a starting point for researchers and developers to build, experiment with, and deploy AM pipelines while ensuring interoperability and allowing multiple theories of argumentation to co-exist within the same framework. Its flexible design supports integration via Python APIs, drag-and-drop tools, and web interfaces, streamlining AM development for research and industry setup, facilitating method comparison, and reproducibility."
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<abstract>Despite extensive research in Argument Mining (AM), the field faces significant challenges in limited reproducibility, difficulty in comparing systems due to varying task combinations, and a lack of interoperability caused by the heterogeneous nature of argumentation theory. These challenges are further exacerbated by the absence of dedicated tools, with most advancements remaining isolated research outputs rather than reusable systems. The oAMF (Open Argument Mining Framework) addresses these issues by providing an open-source, modular, and scalable platform that unifies diverse AM methods. Initially released with seventeen integrated modules, the oAMF serves as a starting point for researchers and developers to build, experiment with, and deploy AM pipelines while ensuring interoperability and allowing multiple theories of argumentation to co-exist within the same framework. Its flexible design supports integration via Python APIs, drag-and-drop tools, and web interfaces, streamlining AM development for research and industry setup, facilitating method comparison, and reproducibility.</abstract>
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%0 Conference Proceedings
%T The Open Argument Mining Framework
%A Gemechu, Debela
%A Ruiz-Dolz, Ramon
%A Górska, Kamila
%A Moslemnejad, Somaye
%A Maguire, Eimear
%A Zografistou, Dimitra
%A Jo, Yohan
%A Lawrence, John
%A Reed, Chris
%Y Mishra, Pushkar
%Y Muresan, Smaranda
%Y Yu, Tao
%S Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-253-4
%F gemechu-etal-2025-open
%X Despite extensive research in Argument Mining (AM), the field faces significant challenges in limited reproducibility, difficulty in comparing systems due to varying task combinations, and a lack of interoperability caused by the heterogeneous nature of argumentation theory. These challenges are further exacerbated by the absence of dedicated tools, with most advancements remaining isolated research outputs rather than reusable systems. The oAMF (Open Argument Mining Framework) addresses these issues by providing an open-source, modular, and scalable platform that unifies diverse AM methods. Initially released with seventeen integrated modules, the oAMF serves as a starting point for researchers and developers to build, experiment with, and deploy AM pipelines while ensuring interoperability and allowing multiple theories of argumentation to co-exist within the same framework. Its flexible design supports integration via Python APIs, drag-and-drop tools, and web interfaces, streamlining AM development for research and industry setup, facilitating method comparison, and reproducibility.
%R 10.18653/v1/2025.acl-demo.31
%U https://aclanthology.org/2025.acl-demo.31/
%U https://doi.org/10.18653/v1/2025.acl-demo.31
%P 318-328
Markdown (Informal)
[The Open Argument Mining Framework](https://aclanthology.org/2025.acl-demo.31/) (Gemechu et al., ACL 2025)
ACL
- Debela Gemechu, Ramon Ruiz-Dolz, Kamila Górska, Somaye Moslemnejad, Eimear Maguire, Dimitra Zografistou, Yohan Jo, John Lawrence, and Chris Reed. 2025. The Open Argument Mining Framework. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 318–328, Vienna, Austria. Association for Computational Linguistics.