@inproceedings{kimura-etal-2022-budget,
title = "Budget Argument Mining Dataset Using {J}apanese Minutes from the National Diet and Local Assemblies",
author = "Kimura, Yasutomo and
Ototake, Hokuto and
Sasaki, Minoru",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.659/",
pages = "6131--6138",
abstract = "Budget argument mining attempts to identify argumentative components related to a budget item, and then classifies these argumentative components, given budget information and minutes. We describe the construction of the dataset for budget argument mining, a subtask of QA Lab-PoliInfo-3 in NTCIR-16. Budget argument mining analyses the argument structure of the minutes, focusing on monetary expressions (amount of money). In this task, given sufficient budget information (budget item, budget amount, etc.), relevant argumentative components in the minutes are identified and argument labels (claim, premise, and other) are assigned their components. In this paper, we describe the design of the data format, the annotation procedure, and release information of budget argument mining dataset, to link budget information to minutes."
}
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<abstract>Budget argument mining attempts to identify argumentative components related to a budget item, and then classifies these argumentative components, given budget information and minutes. We describe the construction of the dataset for budget argument mining, a subtask of QA Lab-PoliInfo-3 in NTCIR-16. Budget argument mining analyses the argument structure of the minutes, focusing on monetary expressions (amount of money). In this task, given sufficient budget information (budget item, budget amount, etc.), relevant argumentative components in the minutes are identified and argument labels (claim, premise, and other) are assigned their components. In this paper, we describe the design of the data format, the annotation procedure, and release information of budget argument mining dataset, to link budget information to minutes.</abstract>
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%0 Conference Proceedings
%T Budget Argument Mining Dataset Using Japanese Minutes from the National Diet and Local Assemblies
%A Kimura, Yasutomo
%A Ototake, Hokuto
%A Sasaki, Minoru
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Thirteenth Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F kimura-etal-2022-budget
%X Budget argument mining attempts to identify argumentative components related to a budget item, and then classifies these argumentative components, given budget information and minutes. We describe the construction of the dataset for budget argument mining, a subtask of QA Lab-PoliInfo-3 in NTCIR-16. Budget argument mining analyses the argument structure of the minutes, focusing on monetary expressions (amount of money). In this task, given sufficient budget information (budget item, budget amount, etc.), relevant argumentative components in the minutes are identified and argument labels (claim, premise, and other) are assigned their components. In this paper, we describe the design of the data format, the annotation procedure, and release information of budget argument mining dataset, to link budget information to minutes.
%U https://aclanthology.org/2022.lrec-1.659/
%P 6131-6138
Markdown (Informal)
[Budget Argument Mining Dataset Using Japanese Minutes from the National Diet and Local Assemblies](https://aclanthology.org/2022.lrec-1.659/) (Kimura et al., LREC 2022)
ACL