The Open Argument Mining Framework

Debela Gemechu; Ramon Ruiz-Dolz; Kamila Gorska; Somaye Moslemnejad; Eimear Maguire; Dimitra Zografistou; Yohan Jo; John Lawrence; Chris Reed

doi:10.18653/v1/2025.acl-demo.31

The Open Argument Mining Framework

Debela Gemechu (Lead / Corresponding author)
, Ramon Ruiz-Dolz
, Kamila Gorska
, Somaye Moslemnejad
, Eimear Maguire
, Dimitra Zografistou
, Yohan Jo
, John Lawrence
, Chris Reed

Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Downloads (Pure)

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.

Original language	English
Title of host publication	Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics
Editors	Pushkar Mishra, Smaranda Muresan, Tao Yu
Place of Publication	Kerrville, TX
Publisher	Association for Computational Linguistics
Pages	318-328
Number of pages	11
Volume	3
ISBN (Print)	9798891762534
DOIs	https://doi.org/10.18653/v1/2025.acl-demo.31
Publication status	Published - Jul 2025
Event	The 63rd Annual Meeting of the Association for Computational Linguistics - Austria Center Vienna, Vienna, Austria Duration: 27 Jul 2025 → 1 Aug 2025 https://2025.aclweb.org/

Conference

Conference	The 63rd Annual Meeting of the Association for Computational Linguistics
Abbreviated title	ACL 2025
Country/Territory	Austria
City	Vienna
Period	27/07/25 → 1/08/25
Internet address	https://2025.aclweb.org/

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10.18653/v1/2025.acl-demo.31Licence: CC BY

Final Published VersionFinal published version, 1.6 MBLicence: CC BY

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Gemechu, D., Ruiz-Dolz, R., Gorska, K., Moslemnejad, S., Maguire, E., Zografistou, D., Jo, Y., Lawrence, J., & Reed, C. (2025). The Open Argument Mining Framework. In P. Mishra, S. Muresan, & T. Yu (Eds.), Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Vol. 3, pp. 318-328). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.acl-demo.31

@inproceedings{7436f28d8f8746e2b3206b788b198004,

title = "The Open Argument Mining Framework",

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.",

author = "Debela Gemechu and Ramon Ruiz-Dolz and Kamila Gorska and Somaye Moslemnejad and Eimear Maguire and Dimitra Zografistou and Yohan Jo and John Lawrence and Chris Reed",

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language = "English",

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pages = "318--328",

editor = "Pushkar Mishra and Smaranda Muresan and Tao Yu",

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}

Gemechu, D , Ruiz-Dolz, R, Gorska, K, Moslemnejad, S, Maguire, E, Zografistou, D, Jo, Y, Lawrence, J & Reed, C 2025, The Open Argument Mining Framework. in P Mishra, S Muresan & T Yu (eds), Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics. vol. 3, Association for Computational Linguistics, Kerrville, TX, pp. 318-328, The 63rd Annual Meeting of the Association for Computational Linguistics, Vienna, Austria, 27/07/25. https://doi.org/10.18653/v1/2025.acl-demo.31

The Open Argument Mining Framework. / Gemechu, Debela (Lead / Corresponding author); Ruiz-Dolz, Ramon; Gorska, Kamila et al.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics. ed. / Pushkar Mishra; Smaranda Muresan; Tao Yu. Vol. 3 Kerrville, TX: Association for Computational Linguistics, 2025. p. 318-328.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - The Open Argument Mining Framework

AU - Gemechu, Debela

AU - Ruiz-Dolz, Ramon

AU - Gorska, Kamila

AU - Moslemnejad, Somaye

AU - Maguire, Eimear

AU - Zografistou, Dimitra

AU - Jo, Yohan

AU - Lawrence, John

AU - Reed, Chris

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AB - 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.

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BT - Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics

A2 - Mishra, Pushkar

A2 - Muresan, Smaranda

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T2 - The 63rd Annual Meeting of the Association for Computational Linguistics

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ER -

The Open Argument Mining Framework

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Deliberation Laboratory (Joint with University of Gottingen, University of Maastricht, Warsaw University of Technology And University of Konstanz)

AI for Citizen Intelligent Coaching against Disinformation (TITAN)

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The Open Argument Mining Framework

Abstract

Conference

Access to Document

Other files and links

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Deliberation Laboratory (Joint with University of Gottingen, University of Maastricht, Warsaw University of Technology And University of Konstanz)

AI for Citizen Intelligent Coaching against Disinformation (TITAN)

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