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

Takashi Inui, Kentaro Inui, Yuji Matsumoto

研究成果: Article査読

19 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)180-193
ページ数14
ジャーナルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2843
DOI
出版ステータスPublished - 2003
外部発表はい

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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