Automatic Linguistic Analysis for Language Teachers: The Case of Zeros

This paper presents the Natural Language Processing-based linguistic analysis tool that we have developed for Japanese as a Second Language teachers. This program, Zero Detector (ZD), aims to promote effective instruction of zero anaphora, on the basis of a hypothesis about ideal conditions for second language acquisition, by making invisible zeros visible. ZD takes Japanese written narrative discourse as input and provides the zero-specified texts and their underlying structures as output. We evaluated ZD’s performance in terms of its zero detecting accuracy. We also present an experimental report of its validity for practical use. As a result, ZD has proven to be pedagogically feasible in terms of its accuracy and its impact on effective instruction.