{"created":"2023-05-15T14:24:09.414890+00:00","id":2554,"links":{},"metadata":{"_buckets":{"deposit":"62cd4143-1993-4bdc-b034-795d06914b67"},"_deposit":{"created_by":3,"id":"2554","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"2554"},"status":"published"},"_oai":{"id":"oai:repository.ninjal.ac.jp:00002554","sets":["320:324"]},"author_link":["8489"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2019-11","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"14","bibliographicPageStart":"6","bibliographic_titles":[{"bibliographic_title":"Proceedings of the First Workshop on Aggregating and Analysing Crowdsourced Annotations for NLP"}]}]},"item_10001_description_19":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf ","subitem_description_type":"Other"}]},"item_10001_description_25":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_description":"National Institute for Japanese Language and Linguistics","subitem_description_type":"Other"}]},"item_10001_description_26":{"attribute_name":"抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper presents research on word familiarity rate estimation using the 'Word List by Semantic Principles'. We collected rating information on 96,557 words in the 'Word List by Semantic Principles' via Yahoo! crowdsourcing . We asked 3,392 subject participants to use their introspection to rate the familiarity of words based on the five perspectives of 'KNOW', 'WRITE', 'READ', 'SPEAK', and 'LISTEN', and each word was rated by at least 16 subject participants. We used Bayesian linear mixed models to estimate the word familiarity rates. We also explored the ratings with the semantic labels used in the 'Word List by Semantic Principles'.","subitem_description_type":"Other"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Association for Computational Linguistics"}]},"item_10001_relation_14":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isIdenticalTo","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.18653/v1/D19-5902","subitem_relation_type_select":"DOI"}}]},"item_10001_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Asahara, Masayuki","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"8489","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-12-20"}],"displaytype":"detail","filename":"D19-5902.pdf","filesize":[{"value":"402.8 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"D19-5902.pdf","url":"https://repository.ninjal.ac.jp/record/2554/files/D19-5902.pdf"},"version_id":"8b9090be-9e92-4ea8-b843-ea770f344ea4"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Word Familiarity Rate Estimation Using a Bayesian Linear Mixed Model","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Word Familiarity Rate Estimation Using a Bayesian Linear Mixed Model","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"3","path":["324"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-12-21"},"publish_date":"2019-12-21","publish_status":"0","recid":"2554","relation_version_is_last":true,"title":["Word Familiarity Rate Estimation Using a Bayesian Linear Mixed Model"],"weko_creator_id":"3","weko_shared_id":3},"updated":"2023-05-15T15:13:45.859420+00:00"}