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Annotation of argument structure in Japanese legal documents

Published in Proceedings of the 4th Workshop on Argument Mining (ArgMining2017), 2017

We propose a method for the annotation of Japanese civil judgment documents, with the purpose of creating flexible summaries of these. The first step, described in the current paper, concerns content selection, i.e., the question of which material should be extracted initially for the summary. In particular, we utilize the hierarchical argu-ment structure of the judgment documents. Our main contributions are a) the design of an annotation scheme that stresses the connection between legal issues (called issue topics) and argument structure, b) an adaptation of rhetorical status to suit the Japanese legal system and c) the definition of a linked argument structure based on le-gal sub-arguments. In this paper, we report agreement between two annotators on sev-eral aspects of the overall task.

Recommended citation: Hiroaki Yamada, Simone Teufel and Takenobu Tokunaga. 2017. Annotation of argument structure in Japanese legal documents. In Proceedings of the 4th Workshop on Argument Mining (ArgMining2017). pages 22-31. http://www.aclweb.org/anthology/W17-5103

Designing an annotation scheme for summarizing Japanese judgment documents

Published in Proceedings of the 9th International Conference on Knowledge and Systems Engineering (KSE 2017), 2017

We propose an annotation scheme for the summarization of Japanese judgment documents. This paper reports the details of the development of our annotation scheme for this task. We also conduct a human study where we compare the annotation of independent annotators. The end goal of our work is summarization, and our categories and the link system is a consequence of this. We propose three types of generic summaries which are focused on specific legal issues relevant to a given legal case.

Recommended citation: Hiroaki Yamada, Simone Teufel and Takenobu Tokunaga. 2017. Designing an annotation scheme for summarizing Japanese judgment documents. In Proceedings of the 9th International Conference on Knowledge and Systems Engineering (KSE 2017). pages 275-280. http://ieeexplore.ieee.org/document/8119471/

publications_nr

Toward Automatic Extraction of Characteristic Features of English Composition by Japanese College Students : Preliminary Experiments and Issues to be Addressed

Published:

We are accumulating electronic files of English composition by university freshmen. For the past ten years or so, about 50 to 90 students enrolled in three English classes taught by the last author are submitting 15 essays per year, each in three different versions. The first is what the students come up with in half hour or so in class after engaging what we call "oral response practice," in which a group of three students in turn read a question card aloud, respond to the question and video record the interaction. Sets of 10 question cards around one topic are prepared by the teacher and distributed to the groups with a video camera. After class, students will spend some time to "complete" their compositions and submit them during the next class and review other students' essays within groups of six. The students are asked to revise the essays and submit the final version during the following class. In addition to the students' peer review comments, it would be desirable if the students can get feedback by statistical analysis of parsing and other processing of their own essays but the files submitted has to go through some pre-processing for the parser and analyzers to work properly. In this presentation, we report on your preliminary study and experimentation.

Recommended citation: 山田寛章, 石井雄隆, 原田康也. 日本人大学生の英語作文からの特徴量の自動抽出に向けて : 予備実験と今後の課題 (思考と言語). 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 114(100). pages 55-60, Jun 2014. ISSN 0913-5685. https://ci.nii.ac.jp/naid/110009925596

判決書自動要約のための修辞役割分類

Published:

我々は,日本国の判決書に対する情報アクセスの容易化・効率化を目指し,検索の手掛かりとなる判決の要約を機械的に生成することを目指している.判決書に内包される共通の議論構造を適切に利用できれば,極めて高い品質の自動要約を実現することが可能となる.本研究の目的はそのための議論構造抽出である。本稿では、独自に作成した議論構造注釈付き判決書コーパスを利用し、形態素bigram等に加えて、モダリティ表現、機能表現、法律の名称、手掛かり句等の素性を導入し、SVMを用いた機械学習によって議論構造の基本となる修辞役割の自動分類を行い、基本的な素性のみでも判決書中の議論的テキストの弁別が可能であるという知見を得た。

Recommended citation: 山田寛章, Simone Teufel, 徳永健伸. 判決書自動要約のための修辞役割分類. 言語処理学会第24回年次大会発表論文集, pp. 785-788, 2018年3月. http://anlp.jp/proceedings/annual_meeting/2018/pdf_dir/P7-8.pdf