The core-adjunct argument distinction is a basic one in the theory of argument struc- ture. The task of distinguishing between the two has strong relations to various ba- sic NLP tasks such as syntactic parsing, semantic role labeling and subcategoriza- tion acquisition. This paper presents a novel unsupervised algorithm for the task that uses no supervised models, utilizing instead state-of-the-art syntactic induction algorithms. This is the first work to tackle this task in a fully unsupervised scenario.

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