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