TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Corpus-based induction of syntactic structure: models of dependency and constituency
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Improving unsupervised dependency parsing with richer contexts and smoothing
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
TectoMT: modular NLP framework
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
Posterior Sparsity in Unsupervised Dependency Parsing
The Journal of Machine Learning Research
Modeling syntax of free word-order languages: dependency analysis by reduction
TSD'05 Proceedings of the 8th international conference on Text, Speech and Dialogue
Lateen EM: unsupervised training with multiple objectives, applied to dependency grammar induction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
The PASCAL Challenge on Grammar Induction
WILS '12 Proceedings of the NAACL-HLT Workshop on the Induction of Linguistic Structure
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This paper describes a system for unsupervised dependency parsing based on Gibbs sampling algorithm. The novel approach introduces a fertility model and reducibility model, which assumes that dependent words can be removed from a sentence without violating its syntactic correctness.