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, precond(ition) 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.
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Inui, T., Inui, K., Matsumoto, Y. (2003). What Kinds and Amounts of Causal Knowledge Can Be Acquired from Text by Using Connective Markers as Clues?. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds) Discovery Science. DS 2003. Lecture Notes in Computer Science(), vol 2843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39644-4_16
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DOI: https://doi.org/10.1007/978-3-540-39644-4_16
Publisher Name: Springer, Berlin, Heidelberg
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