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Information Extraction from Public Meeting Articles

Authors :
Felix Giovanni Virgo
Chenhui Chu
Takaya Ogawa
Koji Tanaka
Kazuki Ashihara
Yuta Nakashima
Noriko Takemura
Hajime Nagahara
Takao Fujikawa
Source :
SN Computer Science. 3
Publication Year :
2022
Publisher :
Springer Nature, 2022.

Abstract

Public meeting articles are the key to understanding the history of public opinion and public sphere in Australia. Information extraction from public meeting articles can obtain new insights into Australian history. In this paper, we create an information extraction dataset in the public meeting domain. We manually annotate the date and time, place, purpose, people who requested the meeting, people who convened the meeting, and people who were convened of 1258 public meeting articles. We further present an information extraction system, which formulates information extraction from public meeting articles as a machine reading comprehension task. Experiments indicate that our system can achieve an F1 score of 74.98% for information extraction from public meeting articles.

Details

Language :
English
ISSN :
26618907
Volume :
3
Database :
OpenAIRE
Journal :
SN Computer Science
Accession number :
edsair.doi.dedup.....249b2584dc647fa3632b391b75348358