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Authors: Ha Thanh Nguyen and Le Minh Nguyen

Affiliation: Japan Advanced Institute of Science and Technology, Japan

Keyword(s): Logical Structure, Law, Pretrained Model.

Abstract: In recent years, we have witnessed breakthroughs in natural language processing coming from pretrained models based on the Transformer architecture. In the field of legal text processing, a special sub-domain of NLP, pretrained models also show promising results. For a legal sentence, although the natural language is used for expression, the real meaning lies in its logical structure. From that observation, we have a hypothesis that the knowledge of recognizing logical structures can support deep learning models to understand the legal text better and achieve a higher performance in the related tasks. To verify our assumption, we design a novel framework to inject the knowledge about recognizing the requisite and effectuation part of a law sentence into Transformer models. Our proposed method is effective and general. By our experiments, we provide informative results about our approach and its performance compared with the baselines.

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Paper citation in several formats:
Nguyen, H. and Nguyen, L. (2022). Logical Structure-based Pretrained Models for Legal Text Processing. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-547-0; ISSN 2184-433X, SciTePress, pages 524-531. DOI: 10.5220/0010852000003116

@conference{icaart22,
author={Ha Thanh Nguyen and Le Minh Nguyen},
title={Logical Structure-based Pretrained Models for Legal Text Processing},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2022},
pages={524-531},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010852000003116},
isbn={978-989-758-547-0},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Logical Structure-based Pretrained Models for Legal Text Processing
SN - 978-989-758-547-0
IS - 2184-433X
AU - Nguyen, H.
AU - Nguyen, L.
PY - 2022
SP - 524
EP - 531
DO - 10.5220/0010852000003116
PB - SciTePress

- Science and Technology Publications, Lda.
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