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Multilingual Unsupervised Dependency Parsing with Unsupervised POS tags

Publication at Faculty of Mathematics and Physics |
2015

Abstract

In this paper, we present experiments with unsupervised dependency parser without using any part-of-speech tags learned from manually annotated data. We use only unsupervised word-classes and therefore propose fully unsupervised approach of sentence structure induction from a raw text.

We show that the results are not much worse than the results with supervised part-of-speech tags.