@inproceedings{takamaru-etal-2020-extraction,
title = "Extraction of the Argument Structure of {T}okyo Metropolitan Assembly Minutes: Segmentation of Question-and-Answer Sets",
author = "Takamaru, Keiichi and
Kimura, Yasutomo and
Shibuki, Hideyuki and
Ototake, Hokuto and
Uchida, Yuzu and
Sakamoto, Kotaro and
Ishioroshi, Madoka and
Mitamura, Teruko and
Kando, Noriko",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.253",
pages = "2064--2068",
abstract = "In this study, we construct a corpus of Japanese local assembly minutes. All speeches in an assembly were transcribed into a local assembly minutes based on the local autonomy law. Therefore, the local assembly minutes form an extremely large amount of text data. Our ultimate objectives were to summarize and present the arguments in the assemblies, and to use the minutes as primary information for arguments in local politics. To achieve this, we structured all statements in assembly minutes. We focused on the structure of the discussion, i.e., the extraction of question and answer pairs. We organized the shared task {``}QA Lab-PoliInfo{''} in NTCIR 14. We conducted a {``}segmentation task{''} to identify the scope of one question and answer in the minutes as a sub task of the shared task. For the segmentation task, 24 runs from five teams were submitted. Based on the obtained results, the best recall was 1.000, best precision was 0.940, and best F-measure was 0.895.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>In this study, we construct a corpus of Japanese local assembly minutes. All speeches in an assembly were transcribed into a local assembly minutes based on the local autonomy law. Therefore, the local assembly minutes form an extremely large amount of text data. Our ultimate objectives were to summarize and present the arguments in the assemblies, and to use the minutes as primary information for arguments in local politics. To achieve this, we structured all statements in assembly minutes. We focused on the structure of the discussion, i.e., the extraction of question and answer pairs. We organized the shared task “QA Lab-PoliInfo” in NTCIR 14. We conducted a “segmentation task” to identify the scope of one question and answer in the minutes as a sub task of the shared task. For the segmentation task, 24 runs from five teams were submitted. Based on the obtained results, the best recall was 1.000, best precision was 0.940, and best F-measure was 0.895.</abstract>
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<date>2020-05</date>
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<start>2064</start>
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%0 Conference Proceedings
%T Extraction of the Argument Structure of Tokyo Metropolitan Assembly Minutes: Segmentation of Question-and-Answer Sets
%A Takamaru, Keiichi
%A Kimura, Yasutomo
%A Shibuki, Hideyuki
%A Ototake, Hokuto
%A Uchida, Yuzu
%A Sakamoto, Kotaro
%A Ishioroshi, Madoka
%A Mitamura, Teruko
%A Kando, Noriko
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F takamaru-etal-2020-extraction
%X In this study, we construct a corpus of Japanese local assembly minutes. All speeches in an assembly were transcribed into a local assembly minutes based on the local autonomy law. Therefore, the local assembly minutes form an extremely large amount of text data. Our ultimate objectives were to summarize and present the arguments in the assemblies, and to use the minutes as primary information for arguments in local politics. To achieve this, we structured all statements in assembly minutes. We focused on the structure of the discussion, i.e., the extraction of question and answer pairs. We organized the shared task “QA Lab-PoliInfo” in NTCIR 14. We conducted a “segmentation task” to identify the scope of one question and answer in the minutes as a sub task of the shared task. For the segmentation task, 24 runs from five teams were submitted. Based on the obtained results, the best recall was 1.000, best precision was 0.940, and best F-measure was 0.895.
%U https://aclanthology.org/2020.lrec-1.253
%P 2064-2068
Markdown (Informal)
[Extraction of the Argument Structure of Tokyo Metropolitan Assembly Minutes: Segmentation of Question-and-Answer Sets](https://aclanthology.org/2020.lrec-1.253) (Takamaru et al., LREC 2020)
ACL
- Keiichi Takamaru, Yasutomo Kimura, Hideyuki Shibuki, Hokuto Ototake, Yuzu Uchida, Kotaro Sakamoto, Madoka Ishioroshi, Teruko Mitamura, and Noriko Kando. 2020. Extraction of the Argument Structure of Tokyo Metropolitan Assembly Minutes: Segmentation of Question-and-Answer Sets. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2064–2068, Marseille, France. European Language Resources Association.