Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases

Ilias Chalkidis, Manos Fergadiotis, Dimitrios Tsarapatsanis, Nikolaos Aletras, Ion Androutsopoulos, Prodromos Malakasiotis


Abstract
Interpretability or explainability is an emerging research field in NLP. From a user-centric point of view, the goal is to build models that provide proper justification for their decisions, similar to those of humans, by requiring the models to satisfy additional constraints. To this end, we introduce a new application on legal text where, contrary to mainstream literature targeting word-level rationales, we conceive rationales as selected paragraphs in multi-paragraph structured court cases. We also release a new dataset comprising European Court of Human Rights cases, including annotations for paragraph-level rationales. We use this dataset to study the effect of already proposed rationale constraints, i.e., sparsity, continuity, and comprehensiveness, formulated as regularizers. Our findings indicate that some of these constraints are not beneficial in paragraph-level rationale extraction, while others need re-formulation to better handle the multi-label nature of the task we consider. We also introduce a new constraint, singularity, which further improves the quality of rationales, even compared with noisy rationale supervision. Experimental results indicate that the newly introduced task is very challenging and there is a large scope for further research.
Anthology ID:
2021.naacl-main.22
Volume:
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
June
Year:
2021
Address:
Online
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
226–241
Language:
URL:
https://aclanthology.org/2021.naacl-main.22
DOI:
10.18653/v1/2021.naacl-main.22
Bibkey:
Cite (ACL):
Ilias Chalkidis, Manos Fergadiotis, Dimitrios Tsarapatsanis, Nikolaos Aletras, Ion Androutsopoulos, and Prodromos Malakasiotis. 2021. Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 226–241, Online. Association for Computational Linguistics.
Cite (Informal):
Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases (Chalkidis et al., NAACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.naacl-main.22.pdf
Video:
 https://aclanthology.org/2021.naacl-main.22.mp4
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