Presentation 2005/7/2
Interpretation of Utterances based on Relevance Theory : Toward the Generation of Explicature with the Maximal Relevance
Sayaka Minewaki, Kazutaka Shimada, Tsutomu Endo,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper proposes an interpretation method of utterances using relevance theory. Sperber and Wilson have said that humans adopt the maximal relevance in interpretation of utterances. The maximal relevance has a high cognitive effect with low processing efforts. We focus on explicatures which are explicitly communicated meaning. We generate explicatures according to pragmatic inference, and compute maximal relevance using multi-objective optimization. We regard Pareto-optimal solutions as explicatures with the maximal relevance.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Relevance Theory / Interpretation of utterances / Contextual processing / Explicature
Paper # TL2005-1
Date of Issue

Conference Information
Committee TL
Conference Date 2005/7/2(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Thought and Language (TL)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Interpretation of Utterances based on Relevance Theory : Toward the Generation of Explicature with the Maximal Relevance
Sub Title (in English)
Keyword(1) Relevance Theory
Keyword(2) Interpretation of utterances
Keyword(3) Contextual processing
Keyword(4) Explicature
1st Author's Name Sayaka Minewaki
1st Author's Affiliation Department of Artificial Intelligence, Kyusyu Institute of Technology Kawatsu, Iizuka, Fukuoka()
2nd Author's Name Kazutaka Shimada
2nd Author's Affiliation Department of Artificial Intelligence, Kyusyu Institute of Technology Kawatsu, Iizuka, Fukuoka
3rd Author's Name Tsutomu Endo
3rd Author's Affiliation Department of Artificial Intelligence, Kyusyu Institute of Technology Kawatsu, Iizuka, Fukuoka
Date 2005/7/2
Paper # TL2005-1
Volume (vol) vol.105
Number (no) 170
Page pp.pp.-
#Pages 6
Date of Issue