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Case-Based Adaptation of Argument Graphs with WordNet and Large Language Models

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Case-Based Reasoning Research and Development (ICCBR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14141))

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Abstract

Finding information online is hard, even more so once you get into the domain of argumentation. There have been developments around the specialized argumentation machines that incorporate structural features of arguments, but all current approaches share one pitfall: They operate on a corpora of limited sizes. Consequently, it may happen that a user searches for a rather general term like cost increases, but the machine is only able to serve arguments concerned with rent increases. We aim to bridge this gap by introducing approaches to generalize/specialize a found argument using a combination of WordNet and Large Language Models. The techniques are evaluated on a new benchmark dataset with diverse queries using our fully featured implementation. Both the dataset and the code are publicly available on GitHub.

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Notes

  1. 1.

    https://github.com/recap-utr/arguegen.

  2. 2.

    https://github.com/recap-utr/arguegen.

  3. 3.

    https://github.com/recap-utr/arguegen.

  4. 4.

    We used the following models: FT: en_core_web_lg from spaCy, USE: v4, STRF: multi-qa-MiniLM-L6-cos-v1, edit-based LLM: text-davinci-edit-001, chat-based LLM: gpt-3.5-turbo.

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Acknowledgements

This work has been funded by the DFG within the project ReCAP-II (No. 375342983) as part of the priority program RATIO (SPP-1999) as well as the Studienstiftung.

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Authors and Affiliations

  1. Trier University, Universitätsring 15, 54296, Trier, Germany

    Mirko Lenz & Ralph Bergmann

  2. German Research Center for Artificial Intelligence (DFKI), Branch Trier University, Behringstr. 21, 54296, Trier, Germany

    Ralph Bergmann

Authors
  1. Mirko Lenz
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  2. Ralph Bergmann
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Correspondence to Mirko Lenz .

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Editors and Affiliations

  1. Robert Gordon University, Aberdeen, UK

    Stewart Massie

  2. Indian Institute of Technology Madras, Chennai, Tamil Nadu, India

    Sutanu Chakraborti

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Lenz, M., Bergmann, R. (2023). Case-Based Adaptation of Argument Graphs with WordNet and Large Language Models. In: Massie, S., Chakraborti, S. (eds) Case-Based Reasoning Research and Development. ICCBR 2023. Lecture Notes in Computer Science(), vol 14141. Springer, Cham. https://doi.org/10.1007/978-3-031-40177-0_17

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  • DOI: https://doi.org/10.1007/978-3-031-40177-0_17

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  • Online ISBN: 978-3-031-40177-0

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