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Simile or Not Simile? : Automatic Detection of Metonymic Relations in Japanese Literal Comparisons

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/63858

Title: Simile or Not Simile? : Automatic Detection of Metonymic Relations in Japanese Literal Comparisons
Authors: Dybala, Pawel Browse this author
Rzepka, Rafal Browse this author →KAKEN DB
Araki, Kenji Browse this author →KAKEN DB
Sayama, Kohichi Browse this author →KAKEN DB
Keywords: NLP
AI
metaphor processing
similes
metonymies
Issue Date: 2016
Publisher: Springer
Citation: Human Language Technology. Challenges for Computer Science and Linguistics, ISBN:978-3-319-43807-8
Journal Title: Lecture Notes in Computer Science
Volume: 9561
Start Page: 277
End Page: 289
Publisher DOI: 10.1007/978-3-319-43808-5_21
Abstract: In this paper we propose a method of automatic distinction between two types of formally identical expressions in Japanese: similes and “metonymical comparisosn”, i.e. literal comparisons that include metonymic relations between elements. Expression like "kujira no you na chiisai me" can be translated into English as "eyes small as whale's", while in Japanese, due to the lack of possessive case, it can be misunderstood as "eyes small as a whale". The reason behind this is the presence of metonymic relation between components of such expressions. In the abovegiven example the word “whale” is a metonymy and represents “whale’s eye”. This is naturally understandable for humans, although formally difficult to detect by automatic algorithms, as both types of expressions (similes and metonymical comparisons) realize the same template. In this work we present a system able to distinguish between these two types of expressions. The system takes a Japanese expession as input and uses the Internet to check possessive relations between its elements. We propose a method of calculating a score based on co-occurrence of source and target pairs in Google (e.g. "whale's eye"). Evaluation experiment showed that the system distinguishes between similes and metonimical comparisons with the accuracy of 74%. We discuss the results and give some ideas for the future.
Rights: The final publication is available at link.springer.com
Type: article (author version)
URI: http://hdl.handle.net/2115/63858
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: Rzepka, Rafal

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