@inproceedings{grundler-etal-2024-amelia,
title = "{AMELIA} - Argument Mining Evaluation on Legal documents in {I}t{A}lian: A {CALAMITA} Challenge",
author = "Grundler, Giulia and
Galassi, Andrea and
Santin, Piera and
Fidelangeli, Alessia and
Galli, Federico and
Palmieri, Elena and
Lagioia, Francesca and
Sartor, Giovanni and
Torroni, Paolo",
editor = "Dell'Orletta, Felice and
Lenci, Alessandro and
Montemagni, Simonetta and
Sprugnoli, Rachele",
booktitle = "Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)",
month = dec,
year = "2024",
address = "Pisa, Italy",
publisher = "CEUR Workshop Proceedings",
url = "https://aclanthology.org/2024.clicit-1.124/",
pages = "1125--1134",
ISBN = "979-12-210-7060-6",
abstract = "This challenge consists of three classification tasks, in the context of argument mining in the legal domain. The tasks are based on a dataset of 225 Italian decisions on Value Added Tax, annotated to identify and categorize argumentative text. The objective of the first task is to classify each argumentative component as premise or conclusion, while the second and third tasks aim at classifying the type of premise: legal vs factual, and its corresponding argumentation scheme. The classes are highly unbalanced, hence evaluation is based on the macro F1 score."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="grundler-etal-2024-amelia">
<titleInfo>
<title>AMELIA - Argument Mining Evaluation on Legal documents in ItAlian: A CALAMITA Challenge</title>
</titleInfo>
<name type="personal">
<namePart type="given">Giulia</namePart>
<namePart type="family">Grundler</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Andrea</namePart>
<namePart type="family">Galassi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Piera</namePart>
<namePart type="family">Santin</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alessia</namePart>
<namePart type="family">Fidelangeli</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Federico</namePart>
<namePart type="family">Galli</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Elena</namePart>
<namePart type="family">Palmieri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Francesca</namePart>
<namePart type="family">Lagioia</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Giovanni</namePart>
<namePart type="family">Sartor</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Paolo</namePart>
<namePart type="family">Torroni</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Felice</namePart>
<namePart type="family">Dell’Orletta</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alessandro</namePart>
<namePart type="family">Lenci</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Simonetta</namePart>
<namePart type="family">Montemagni</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rachele</namePart>
<namePart type="family">Sprugnoli</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>CEUR Workshop Proceedings</publisher>
<place>
<placeTerm type="text">Pisa, Italy</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-12-210-7060-6</identifier>
</relatedItem>
<abstract>This challenge consists of three classification tasks, in the context of argument mining in the legal domain. The tasks are based on a dataset of 225 Italian decisions on Value Added Tax, annotated to identify and categorize argumentative text. The objective of the first task is to classify each argumentative component as premise or conclusion, while the second and third tasks aim at classifying the type of premise: legal vs factual, and its corresponding argumentation scheme. The classes are highly unbalanced, hence evaluation is based on the macro F1 score.</abstract>
<identifier type="citekey">grundler-etal-2024-amelia</identifier>
<location>
<url>https://aclanthology.org/2024.clicit-1.124/</url>
</location>
<part>
<date>2024-12</date>
<extent unit="page">
<start>1125</start>
<end>1134</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T AMELIA - Argument Mining Evaluation on Legal documents in ItAlian: A CALAMITA Challenge
%A Grundler, Giulia
%A Galassi, Andrea
%A Santin, Piera
%A Fidelangeli, Alessia
%A Galli, Federico
%A Palmieri, Elena
%A Lagioia, Francesca
%A Sartor, Giovanni
%A Torroni, Paolo
%Y Dell’Orletta, Felice
%Y Lenci, Alessandro
%Y Montemagni, Simonetta
%Y Sprugnoli, Rachele
%S Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)
%D 2024
%8 December
%I CEUR Workshop Proceedings
%C Pisa, Italy
%@ 979-12-210-7060-6
%F grundler-etal-2024-amelia
%X This challenge consists of three classification tasks, in the context of argument mining in the legal domain. The tasks are based on a dataset of 225 Italian decisions on Value Added Tax, annotated to identify and categorize argumentative text. The objective of the first task is to classify each argumentative component as premise or conclusion, while the second and third tasks aim at classifying the type of premise: legal vs factual, and its corresponding argumentation scheme. The classes are highly unbalanced, hence evaluation is based on the macro F1 score.
%U https://aclanthology.org/2024.clicit-1.124/
%P 1125-1134
Markdown (Informal)
[AMELIA - Argument Mining Evaluation on Legal documents in ItAlian: A CALAMITA Challenge](https://aclanthology.org/2024.clicit-1.124/) (Grundler et al., CLiC-it 2024)
ACL
- Giulia Grundler, Andrea Galassi, Piera Santin, Alessia Fidelangeli, Federico Galli, Elena Palmieri, Francesca Lagioia, Giovanni Sartor, and Paolo Torroni. 2024. AMELIA - Argument Mining Evaluation on Legal documents in ItAlian: A CALAMITA Challenge. In Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024), pages 1125–1134, Pisa, Italy. CEUR Workshop Proceedings.