FrameNet-Based Shallow Semantic Parsing with a POS Tagger(Artificial Intelligence II)

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概要

• 論文の詳細を見る

• In this paper we propose a FrameNet-based shallow semantic parsing without syntactic parsing. Previous studies on shallow semantic parsing utilize the results of syntactic parsing of input sentences as input data. However, syntactic parsing has well-known shortfalls, such as large amount of computation and insufficient accuracy etc... Furthermore, when use of syntactic parsing is premised, it limits applicable languages, since good syntactic parser is rarely available. To prevent such undesirable consequences in shallow semantic parsing, we propose to use POS tagger instead of syntactic parsing. Our experiments using FrameNetII data as training and test data showed the same level performance as existing methods using syntactic parsing.

• 一般社団法人情報処理学会の論文
• 2004-12-04

著者

• Shibui Nobukazu

  Faculty Of Science And Technology Keio University

• SAKURAI Akito

  Faculty of Science and Technology, Keio University

• Sakurai Akito

  Faculty Of Science And Technology Keio University

関連論文

• Utilizing "Wisdom of Crowds" for Handling Multimedia Contents(Knowledge, Information and Creativity Support System)
• FrameNet-Based Shallow Semantic Parsing with a POS Tagger(Artificial Intelligence II)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)
• FrameNet-Based Shallow Semantic Parsing with a POS Tagger(Artificial Intelligence II)

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