loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.230.35.103

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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