  The referential properties of noun phrases in the Japanese language, which
has no articles, are useful for article generation in Japanese-English machine
translation and for anaphora resolution in Japanese noun phrases. They are
generally classified as generic noun phrases, definite noun phrases, and
indefinite noun phrases. In the previous work, referential properties were
estimated by developing rules that used clue words. If two or more rules were
in conflict with each other, the category having the maximum total score given
by the rules was selected as the desired category. The score given by each rule
was established by hand, so the manpower cost was high. In this work, we
automatically adjusted these scores by using a machine-learning method and
succeeded in reducing the amount of manpower needed to adjust these scores.
