Presentation 2002/7/9
Extracting Causal Knowledge from Text The Case of Resultative Connectives "tame"
Takashi INUI, Kentaro INUI, Yuji MATSUMOTO,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper discusses how to extract causal knowledge from a large text collection. Our goal is to develop an automatic method of identifing the causal knowledge that supports the underlying coherence of a given causal expression. We report our ongoing attempts to design the overall problem setting and to explore the feasibility of pursue the goal, forcusing on a class of target sentences including a resultative conjunction "tame". While the recall was not very high, the precision we achieved in an experiment empirically proved that our approach is promising.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) causal relation / causal knowledge / knowledge acquisition / knowledge representation / causal marker
Paper # NLC2002-34
Date of Issue

Conference Information
Committee NLC
Conference Date 2002/7/9(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 Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Extracting Causal Knowledge from Text The Case of Resultative Connectives "tame"
Sub Title (in English)
Keyword(1) causal relation
Keyword(2) causal knowledge
Keyword(3) knowledge acquisition
Keyword(4) knowledge representation
Keyword(5) causal marker
1st Author's Name Takashi INUI
1st Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology()
2nd Author's Name Kentaro INUI
2nd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
3rd Author's Name Yuji MATSUMOTO
3rd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
Date 2002/7/9
Paper # NLC2002-34
Volume (vol) vol.102
Number (no) 200
Page pp.pp.-
#Pages 8
Date of Issue