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--- |
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license: cc-by-nc-sa-4.0 |
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language: |
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- en |
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tags: |
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- argument mining |
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datasets: |
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- US2016 |
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- QT30 |
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metrics: |
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- macro-f1 |
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--- |
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# Argument Relation Mining |
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Argument Mining model trained with English (EN) data for the Argument Relation Identification (ARI) task using the US2016 and the QT30 corpora. |
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Extending the best performing RoBERTa-large model trained in the "Transformer-Based Models for Automatic Detection of Argument Relations: A Cross-Domain Evaluation" paper. |
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macro-F1 (4-class classification): **0.70** |
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Conf. Matrix on test: |
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| Class | **None** | **Inference** | **Conflict** | **Rephrase** | |
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|---------------|----------|---------------|--------------|--------------| |
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| **None** | 2991 | 133 | 13 | 24 | |
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| **Inference** | 139 | 547 | 51 | 103 | |
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| **Conflict** | 38 | 54 | 98 | 21 | |
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| **Rephrase** | 55 | 128 | 25 | 443 | |
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Cite: |
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``` |
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@article{ruiz2021transformer, |
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author = {R. Ruiz-Dolz and J. Alemany and S. Barbera and A. Garcia-Fornes}, |
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journal = {IEEE Intelligent Systems}, |
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title = {Transformer-Based Models for Automatic Identification of Argument Relations: A Cross-Domain Evaluation}, |
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year = {2021}, |
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volume = {36}, |
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number = {06}, |
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issn = {1941-1294}, |
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pages = {62-70}, |
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doi = {10.1109/MIS.2021.3073993}, |
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publisher = {IEEE Computer Society} |
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} |
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``` |
