Rhetorical Role Identification for Portuguese Legal Documents

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

Rhetorical Role Identification for Portuguese Legal Documents. / Aragy, Roberto; Fernandes, Eraldo Rezende; Caceres, Edson Norberto.
Intelligent Systems: 10th Brazilian Conference, BRACIS 2021, Virtual Event, November 29 – December 3, 2021, Proceedings, Part II. ed. / André Britto; Karina Valdivia Delgado. Cham: Springer Schweiz, 2021. p. 557-571 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13074 LNAI).

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Aragy, R, Fernandes, ER & Caceres, EN 2021, Rhetorical Role Identification for Portuguese Legal Documents. in A Britto & K Valdivia Delgado (eds), Intelligent Systems: 10th Brazilian Conference, BRACIS 2021, Virtual Event, November 29 – December 3, 2021, Proceedings, Part II. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13074 LNAI, Springer Schweiz, Cham, pp. 557-571, Brazilian Conference on Intelligent Systems - BRACIS 2021, Virtual, Online, 29.11.21. https://doi.org/10.1007/978-3-030-91699-2_38

APA

Aragy, R., Fernandes, E. R., & Caceres, E. N. (2021). Rhetorical Role Identification for Portuguese Legal Documents. In A. Britto, & K. Valdivia Delgado (Eds.), Intelligent Systems: 10th Brazilian Conference, BRACIS 2021, Virtual Event, November 29 – December 3, 2021, Proceedings, Part II (pp. 557-571). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13074 LNAI). Springer Schweiz. https://doi.org/10.1007/978-3-030-91699-2_38

Vancouver

Aragy R, Fernandes ER, Caceres EN. Rhetorical Role Identification for Portuguese Legal Documents. In Britto A, Valdivia Delgado K, editors, Intelligent Systems: 10th Brazilian Conference, BRACIS 2021, Virtual Event, November 29 – December 3, 2021, Proceedings, Part II. Cham: Springer Schweiz. 2021. p. 557-571. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-91699-2_38

Bibtex

@inbook{8e748af0e31e481b94e65089a44e5949,
title = "Rhetorical Role Identification for Portuguese Legal Documents",
abstract = "In this paper, we present a new corpus for Rhetorical Role Identification in Portuguese legal documents. The corpus comprises petitions from 70 civil lawsuits filed in TJMS court and was manually labeled with rhetorical roles specifically tailored for petitions. Since petition documents are created without a standard structure, we had to deal with several issues to clean the extracted textual content. We assessed classic and deep learning machine learning methods on the proposed corpus. The best performing method obtained an F-score of 80.50. At the best of our knowledge, this is the first work to deal with rhetorical role identification for petitions, given that previous works focused only on judicial decisions. Additionally, it is also the first work to tackle this task for the Portuguese language. The proposed corpus, as well as the proposed rhetorical roles, can foster new research in the judicial area and also lead to new solutions to improve the flow of Brazilian court houses.",
keywords = "Corpus, Legal sentence classification, Natural language processing, Rhetorical role identification, Informatics, Business informatics",
author = "Roberto Aragy and Fernandes, {Eraldo Rezende} and Caceres, {Edson Norberto}",
year = "2021",
doi = "10.1007/978-3-030-91699-2_38",
language = "English",
isbn = "978-3-030-91698-5",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Schweiz",
pages = "557--571",
editor = "Andr{\'e} Britto and {Valdivia Delgado}, Karina",
booktitle = "Intelligent Systems",
address = "Switzerland",
note = "Brazilian Conference on Intelligent Systems - BRACIS 2021 ; Conference date: 29-11-2021 Through 03-12-2021",
url = "https://c4ai.inova.usp.br/bracis2021/#:~:text=Organized%20by%20C4AI%2C%20the%2010th,29th%20to%20December%203rd%2C%202021.",

}

RIS

TY - CHAP

T1 - Rhetorical Role Identification for Portuguese Legal Documents

AU - Aragy, Roberto

AU - Fernandes, Eraldo Rezende

AU - Caceres, Edson Norberto

N1 - Conference code: 10

PY - 2021

Y1 - 2021

N2 - In this paper, we present a new corpus for Rhetorical Role Identification in Portuguese legal documents. The corpus comprises petitions from 70 civil lawsuits filed in TJMS court and was manually labeled with rhetorical roles specifically tailored for petitions. Since petition documents are created without a standard structure, we had to deal with several issues to clean the extracted textual content. We assessed classic and deep learning machine learning methods on the proposed corpus. The best performing method obtained an F-score of 80.50. At the best of our knowledge, this is the first work to deal with rhetorical role identification for petitions, given that previous works focused only on judicial decisions. Additionally, it is also the first work to tackle this task for the Portuguese language. The proposed corpus, as well as the proposed rhetorical roles, can foster new research in the judicial area and also lead to new solutions to improve the flow of Brazilian court houses.

AB - In this paper, we present a new corpus for Rhetorical Role Identification in Portuguese legal documents. The corpus comprises petitions from 70 civil lawsuits filed in TJMS court and was manually labeled with rhetorical roles specifically tailored for petitions. Since petition documents are created without a standard structure, we had to deal with several issues to clean the extracted textual content. We assessed classic and deep learning machine learning methods on the proposed corpus. The best performing method obtained an F-score of 80.50. At the best of our knowledge, this is the first work to deal with rhetorical role identification for petitions, given that previous works focused only on judicial decisions. Additionally, it is also the first work to tackle this task for the Portuguese language. The proposed corpus, as well as the proposed rhetorical roles, can foster new research in the judicial area and also lead to new solutions to improve the flow of Brazilian court houses.

KW - Corpus

KW - Legal sentence classification

KW - Natural language processing

KW - Rhetorical role identification

KW - Informatics

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=85121825188&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-91699-2_38

DO - 10.1007/978-3-030-91699-2_38

M3 - Article in conference proceedings

AN - SCOPUS:85121825188

SN - 978-3-030-91698-5

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 557

EP - 571

BT - Intelligent Systems

A2 - Britto, André

A2 - Valdivia Delgado, Karina

PB - Springer Schweiz

CY - Cham

T2 - Brazilian Conference on Intelligent Systems - BRACIS 2021

Y2 - 29 November 2021 through 3 December 2021

ER -