Next Article in Journal
Sophimatics: A Two-Dimensional Temporal Cognitive Architecture for Paradox-Resilient Artificial Intelligence
Previous Article in Journal
SpaceTime: A Deep Similarity Defense Against Poisoning Attacks in Federated Learning
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
BDCC
Volume 9
Issue 12
10.3390/bdcc9120315
BDCC-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Sentence-Level Rhetorical Role Labeling in Judicial Decisions

by
Gergely Márk Csányi
1,2,*,
István Üveges
1,3,
Dorina Lakatos
1,
Dóra Ripszám
4,
Kornélia Kozák
5,
Dániel Nagy
1 and
János Pál Vadász
1,4
1
MONTANA Knowledge Management Ltd., H-1029 Budapest, Hungary
2
Department of Electric Power Engineering, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
3
Political and Legal Text Mining & Artificial Intelligence Laboratory (poltextLAB), ELTE Centre for Social Sciences, H-1097 Budapest, Hungary
4
UNESCO Chair on Digital Platforms for Learning Societies, Institute of the Information Society, Ludovika University of Public Service, H-1083 Budapest, Hungary
5
Department of European Public and Private Law, Faculty of Public Governance and International Studies, Ludovika University of Public Service, H-1083 Budapest, Hungary
*
Author to whom correspondence should be addressed.
Big Data Cogn. Comput. 2025, 9(12), 315; https://doi.org/10.3390/bdcc9120315
Submission received: 1 October 2025 / Revised: 25 November 2025 / Accepted: 1 December 2025 / Published: 5 December 2025
Versions Notes

Abstract

This paper presents an in-production Rhetorical Role Labeling (RRL) classifier developed for Hungarian judicial decisions. RRL is a sequential classification problem in Natural Language Processing, aiming to assign functional roles (such as facts, arguments, decision, etc.) to every segment or sentence in a legal document. The study was conducted on a human-annotated sentence-level RRL corpus and compares multiple neural architectures, including BiLSTM, attention-based networks, and a support vector machine as baseline. It further investigates the impact of late chunking during vectorization, in contrast to classical approaches. Results from tests on the labeled dataset and annotator agreement statistics are reported, and performance is analyzed across architecture types and embedding strategies. Contrary to recent findings in retrieval tasks, late chunking does not show consistent improvements for sentence-level RRL, suggesting that contextualization through chunk embeddings may introduce noise rather than useful context in Hungarian legal judgments. The work also discusses the unique structure and labeling challenges of Hungarian cases compared to international datasets and provides empirical insights for future legal NLP research in non-English court decisions.
Keywords: rhetorical role labeling; judicial decisions; sentence classification; late chunking rhetorical role labeling; judicial decisions; sentence classification; late chunking

Share and Cite

MDPI and ACS Style

Csányi, G.M.; Üveges, I.; Lakatos, D.; Ripszám, D.; Kozák, K.; Nagy, D.; Vadász, J.P. Sentence-Level Rhetorical Role Labeling in Judicial Decisions. Big Data Cogn. Comput. 2025, 9, 315. https://doi.org/10.3390/bdcc9120315

AMA Style

Csányi GM, Üveges I, Lakatos D, Ripszám D, Kozák K, Nagy D, Vadász JP. Sentence-Level Rhetorical Role Labeling in Judicial Decisions. Big Data and Cognitive Computing. 2025; 9(12):315. https://doi.org/10.3390/bdcc9120315

Chicago/Turabian Style

Csányi, Gergely Márk, István Üveges, Dorina Lakatos, Dóra Ripszám, Kornélia Kozák, Dániel Nagy, and János Pál Vadász. 2025. "Sentence-Level Rhetorical Role Labeling in Judicial Decisions" Big Data and Cognitive Computing 9, no. 12: 315. https://doi.org/10.3390/bdcc9120315

APA Style

Csányi, G. M., Üveges, I., Lakatos, D., Ripszám, D., Kozák, K., Nagy, D., & Vadász, J. P. (2025). Sentence-Level Rhetorical Role Labeling in Judicial Decisions. Big Data and Cognitive Computing, 9(12), 315. https://doi.org/10.3390/bdcc9120315

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop