What kinds and amounts of causal knowledge can be acquired from text by using connective markers as clues?

Takashi Inui, Kentaro Inui, Yuji Matsumoto

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

This paper reports the results of our ongoing research into the automatic acquisition of causal knowledge. We created a new typology for expressing the causal relations - cause, effect, precondition) and means -based mainly on the volitionality of the related events. From our experiments using the Japanese resultative connective "tame", we achieved 80% recall with over 95% precision for the cause, precond and means relations, and 30% recall with 90% precision for the effect relation. The results indicate that over 27,000 instances of causal relations can be acquired from one year of Japanese newspaper articles.

Original languageEnglish
Pages (from-to)180-193
Number of pages14
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2843
Publication statusPublished - 2003 Dec 1
Externally publishedYes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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