Unsupervised Dependency Parsing using Reducibility and Fertility features

Exploiting Reducibility in Unsupervised Dependency Parsing

CRF Autoencoder for Unsupervised Dependency Parsing

Unsupervised dependency parsing, which tries to discover linguistic dependency structures from unannotated data, is a very challenging task. Almost all previous work on this task focuses on learning generative models. In…

Adapting Unsupervised Syntactic Parsing Methodology for Discourse Dependency Parsing

One of the main bottlenecks in developing discourse dependency parsers is the lack of annotated training data. A potential solution is to utilize abundant unlabeled data by using unsupervised techniques, but there is so …

A Survey of Unsupervised Dependency Parsing

Syntactic dependency parsing is an important task in natural language processing. Unsupervised dependency parsing aims to learn a dependency parser from sentences that have no annotation of their correct parse trees. Des…

Unsupervised Domain Adaptation Method with Semantic-Structural Alignment for Dependency Parsing

Unsupervised cross-domain dependency parsing is to accomplish domain adaptation for dependency parsing without using labeled data in target domain. Existing methods are often of the pseudo-annotation type, which generate…