Abstract
This paper proposes an unsupervised method for distinguishing mass and countnouns in context using decision lists.The mass count distinction is particularly im-portant in detecting errors concerning the articles and the singular/plural usage inthe writing of Japanese learners of English.Decision lists are learned from a set oftraining data that consist of instances of the target noun used as mass or count. Ingeneral, it is costly and time-consuming to acquire a set of training data.To solvethe problem, this paper also proposes a method for automatically generating trainingdata.Experiments show that the proposed method achieves an accuracy of 83.9%in distinguishing mass and count nouns in context.
