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--- |
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license: mit |
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size_categories: |
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- n<1K |
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task_categories: |
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- text-classification |
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pretty_name: liaisons IBM's Claim Stance Dataset Sample |
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dataset_info: |
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features: |
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- name: topic |
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dtype: string |
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- name: parent_argument |
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dtype: string |
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- name: child_argument |
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dtype: string |
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- name: relation |
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dtype: string |
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splits: |
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- name: binary |
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num_bytes: 21165 |
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num_examples: 110 |
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- name: ternary |
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num_bytes: 13861 |
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num_examples: 72 |
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download_size: 22681 |
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dataset_size: 35026 |
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configs: |
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- config_name: default |
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data_files: |
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- split: binary |
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path: data/binary-* |
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- split: ternary |
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path: data/ternary-* |
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tags: |
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- relation-based argument mining |
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- argument mining |
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- sample |
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--- |
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--- |
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⚠️ This repository is a part of an academical project for the Heriot-Watt University, no third-party contributions are accepted. |
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# Dataset Card for Liaison's IBM Claim Stance Dataset Sample |
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## Table of Contents |
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- [About the Dataset](#about-the-dataset) |
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- [About Contributions](#about-contributions) |
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- [Associated Works](#associated-works) |
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- [Licensing Information](#licensing-information) |
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- [Credits](#credits) |
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- [Special Thanks](#special-thanks) |
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## About the Dataset |
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### Dataset Summary |
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The present dataset is a result of processing the [IBM Debater Claim Stance Dataset](https://huggingface.co/datasets/ibm/claim_stance) to create representative samples. The size has been reduced to roughly 100 entries, enabling the benchmarking of models for relation-based argument mining tasks with limited resources. |
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You can also find here the associated benchmarking [framework](https://github.com/coding-kelps/liaisons-experiments) and [results](https://huggingface.co/datasets/coding-kelps/liaisons-experiments-results). |
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The sample also modifies the original dataset to achieve a more balanced plurality of stances and topics, and creates a new "unrelated" class in argument relation (following a simple rule-based data augmentation algorithm). Further details on the preprocessing can be found on [GitHub](https://github.com/coding-kelps/liaisons-preprocess). |
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### Dataset Structure |
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* parent_argument - The first argument that states a position regarding a topic |
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* child_argument - Another argument that is compared to the parent argument |
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* relation - The argumentative relation of the child argument to the parent argument. It can either be support/attack in the binary split or support/attack/unrelated in the ternary split |
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## About Contributions |
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As mentioned earlier, this work is part of an academic project for the validation of my Master's Degree at Heriot-Watt University, preventing me from accepting any contributions until the final release of my project. Thank you for your understanding. |
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## Associated Works |
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This work is part of a collection of works whose ultimate goal is to deliver a framework to automatically analyze social media content (e.g., X, Reddit) to extract their argumentative value and predict their relations, leveraging Large Language Models' (LLMs) abilities: |
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- [liaisons](https://github.com/coding-kelps/liaisons) (the developed client for social media content analysis) |
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- [liaisons-preprocess](https://github.com/coding-kelps/liaisons-preprocess) (the preprocessing of the original IBM dataset) |
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- [liaisons-experiments](https://github.com/coding-kelps/liaisons-experiments) (the benchmarking framework that the sample is intended to be used with) |
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- [liaisons-experiments-results](https://huggingface.co/datasets/coding-kelps/liaisons-experiments-results) (the obtained results with this benchmarking) |
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- [mantis-shrimp](https://github.com/coding-kelps/mantis-shrimp) (the configuration-as-code used to set up my workstation for this project) |
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## Licensing Information |
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This work includes data from the following sources: |
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* Wikipedia content licensed under CC BY-SA 3.0: [Wikipedia](https://en.wikipedia.org/wiki/Wikipedia:Copyrights#Reusers.27_rights_and_obligations) |
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* IBM content licensed under CC BY-SA 3.0: (c) Copyright IBM 2014. Released under [CC-BY-SA 3.0](http://creativecommons.org/licenses/by-sa/3.0/) |
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Modifications and preprocessing have been made to the original data. This derivative work is licensed under the same CC BY-SA 3.0 license. |
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## Credits |
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Further information about the original dataset can be found on its original [HuggingFace page](https://huggingface.co/datasets/ibm/claim_stance) and its associated research papers: [Stance Classification of Context-Dependent Claims](https://aclanthology.org/E17-1024/) and [Improving Claim Stance Classification with Lexical Knowledge Expansion and Context Utilization](https://aclanthology.org/W17-5104/). |
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## Special Thanks |
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I would like to credits [Andrew Ireland](http://www.macs.hw.ac.uk/~air/), my supervisor for this project. |
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<img src="https://upload.wikimedia.org/wikipedia/commons/thumb/0/03/Heriot-Watt_University_logo.svg/1200px-Heriot-Watt_University_logo.svg.png" width="300"> |
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