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This paper proposes a methodology for generating specialized Japanese data sets for the extraction of causal relations, in which temporal, causal and discourse relations at both the fact level and the epistemic level, are annotated. We applied our methodology to a number of text fragments taken from the Balanced Corpus of Contemporary Written Japanese. We evaluated the feasibility of our methodology in terms of agreement and frequencies, and discussed the results of the analysis.

Building a Japanese Corpus of Temporal-Causal-Discourse Structures Based on SDRT for Extracting Causal Relations