An Accurate Morphological Analysis and Proper Name ldentification for Japanese Text Processing

• Item type: Journal(1)
• 公開日: 1994-03-15
• タイトル: An Accurate Morphological Analysis and Proper Name ldentification for Japanese Text Processing
• タイトル / 言語: en
• タイトル: An Accurate Morphological Analysis and Proper Name ldentification for Japanese Text Processing
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 論文
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• その他タイトル / その他のタイトル: プログラミング言語
• 著者所属: Center for Machine Translation Carnegie Mellon University/Visiting researcher from NTT Data Communications Systems Corp.
• 著者所属: Center for Machine Translation Carnegie Mellon University
• 著者所属(英): en
• 著者所属(英): Center for Machine Translation, Carnegie Mellon University/Visiting researcher from NTT Data Communications Systems Corp.
• 著者所属(英): en
• 著者所属(英): Center for Machine Translation, Carnegie Mellon University
• 著者名: Tsuyoshi, Kitani; Teruko, Mitamura
• 著者名(英): Tsuyoshi, Kitani; Teruko, Mitamura
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This paper describes a Japanese preprocessor used for syntactic and semantic parsing. It consists of three major components: ( l) a morphological analyzer called MAJESTY (Morphological Analyzer for Japanese Text Analysis) (2) a proper name identification and grouping program and (3) a format conversion program for an input to Tomita's generalized LR parser. To enable the parser to perform efficiently the original morphological analyzer was modified to disambiguate its output when multiple possibilities for segmentations and parts of speech were found and to pack ambiguous segments locally in the output. The grouping program identifies several segments forming one con cept which is often the case with proper names and puts them together to provide a meaningful set of segments for the parser. The grouped segments are finally converted into a Lisp readab]e f. ormat and fed into the parser. Tested on financial news articles the preprocessor success-fully segmented text and tagged parts of speech with a greater than 98% accuracy. Company names have been identified with over 80% in both recall and precision. Person and place names have also been recognized with over 90% accuracy. The preprocessor has been successfully integrated into the SHOGUN and TF.XTRACT information extraction systems which process texts in the TIPSTER domains of corporate joint ventures and microelectronics.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This paper describes a Japanese preprocessor used for syntactic and semantic parsing. It consists of three major components: ( l) a morphological analyzer called MAJESTY (Morphological Analyzer for Japanese Text Analysis) , (2) a proper name identification and grouping program, and (3) a format conversion program for an input to Tomita's generalized LR parser. To enable the parser to perform efficiently, the original morphological analyzer was modified to disambiguate its output when multiple possibilities for segmentations and parts of speech were found, and to pack ambiguous segments locally in the output. The grouping program identifies several segments forming one con, cept, which is often the case with proper names, and puts them together to provide a meaningful set of segments for the parser. The grouped segments are finally converted into a Lisp readab]e f. ormat and fed into the parser. Tested on financial news articles, the preprocessor success-fully segmented text and tagged parts of speech with a greater than 98% accuracy. Company names have been identified with over 80% in both recall and precision. Person and place names have also been recognized with over 90% accuracy. The preprocessor has been successfully integrated into the SHOGUN and TF.XTRACT information extraction systems which process texts in the TIPSTER domains of corporate joint ventures and microelectronics.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 35, 号 3, p. 404-413, 発行日 1994-03-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764