MiG

Masood Ghayoomi

From HPSG-based Persian Treebanking to Parsing

Betreuer: Raúl Rojas , Stefan Müller, Ivanov Simov
Abschluss: PhD
Abgabedatum: 27.06.2014

Kurzbeschreibung

Parsing is a step for understanding a natural language to find out about the words and their grammatical relations in a sentence. Statistical parsers require a set of annotated data, called a treebank, to learn the grammar of a language and apply the learnt model on new, unseen data. This set of annotated data is not available for all languages, and its development is very time-consuming, tedious, and expensive. In this dissertation, we propose a method for treebanking from scratch using machine learning methods.

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