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date: 20 April 2018

Abstract and Keywords

Probabilistic linguistics takes all linguistic evidence as positive evidence and lets statistics decide. It allows for accurate modelling of gradient phenomena in production and perception, and suggests that rule-like behaviour is no more than a side effect of maximizing probability. This chapter addressing the following issues: How far can probabilistic linguistics be stretched? What can data-oriented parsing (DOP) explain? How can probabilistic linguistics deal with language acquisition? What can Unsupervised DOP learn?

Keywords: linguistic theory, gradient phenomena, probability, statistics, data-oriented parsing, language acquisition

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