{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00047833","sets":["1164:4179:4187:4191"]},"path":["4191"],"owner":"1","recid":"47833","title":["依存構造を用いた中国語事象の時間関係のタグ付きコーパスの構築"],"pubdate":{"attribute_name":"公開日","attribute_value":"2007-05-25"},"_buckets":{"deposit":"04c6baaf-d0e0-4c34-84f4-3f58bb0771b6"},"_deposit":{"id":"47833","pid":{"type":"depid","value":"47833","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"依存構造を用いた中国語事象の時間関係のタグ付きコーパスの構築","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"依存構造を用いた中国語事象の時間関係のタグ付きコーパスの構築"},{"subitem_title":"Constructing a Temporal Relation Tagged Corpus of Chinese based on Dependency Structure Analysis","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2007-05-25","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"},{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"},{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science Nara Institute of Science and Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/47833/files/IPSJ-NL07179011.pdf"},"date":[{"dateType":"Available","dateValue":"2009-05-25"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL07179011.pdf","filesize":[{"value":"639.2 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"23"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"ecc90026-76fc-463c-9db6-6971b9ca26c8","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2007 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"鄭育昌"},{"creatorName":"浅原, 正幸"},{"creatorName":"松本, 裕治"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuchang, CHENG","creatorNameLang":"en"},{"creatorName":"Masayuki, ASAHARA","creatorNameLang":"en"},{"creatorName":"Yuji, MATSUMOTO","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10115061","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では中国語新聞記事に事象間の時間関係のタグ付け作業を説明するガイドラインを示す。本研究の目的は機械学習で事象間の時間関係を自動的に解析するため、事象間の時間関係のタグ付きコーパスを構築することである。文章の全ての事象の組合せを考慮する解析は非効率であるため、依存構造の導入によって、内容の理解に重要な事象間時間関係を同定する手法を提案する。本手法の有効性を図るため、本稿では小規模コーパスを人手で構築し、本手法の有効性を検証した。依存構造の導入により、事象間の可能な時間関係が約49%再現でき、コーパス構築するための作業量が減少できることが判明した。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper describes an annotation guideline for a temporal relation tagged corpus. Our goal is to construct a machine learnable model that automatically analyzes temporal events and rela-tions between events. Since analyzing all combinations of events is inefficient, we examine use of dependency structure analysis to efficiently recognize meaningful temporal relations. We survey a small tagged data set to investigate the coverage of our method. Although the coverage of our meth-ods is about 49%, we find that the dependency structure appears useful for reducing manual efforts in constructing a tagged corpus with temporal relations.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"66","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告自然言語処理(NL)"}],"bibliographicPageStart":"61","bibliographicIssueDates":{"bibliographicIssueDate":"2007-05-25","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"47(2007-NL-179)","bibliographicVolumeNumber":"2007"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":47833,"updated":"2025-01-22T08:48:31.948505+00:00","links":{},"created":"2025-01-18T23:13:13.105404+00:00"}