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Stop-probability estimates computed on a large corpus improve Unsupervised Dependency Parsing
David Mareček
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Milan Straka
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Paper Details:
Month: August
Year: 2013
Location: Sofia, Bulgaria
Venue:
ACL |
Citations
URL
Combining Supervised and Unsupervised Parsing for Distributional Similarity
Martin Riedl
|
Irina Alles
|
Chris Biemann
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Quantifying training challenges of dependency parsers
Lauriane Aufrant
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Guillaume Wisniewski
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François Yvon
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Breaking Out of Local Optima with Count Transforms and Model Recombination: A Study in Grammar Induction
Valentin I. Spitkovsky
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Hiyan Alshawi
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Daniel Jurafsky
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Density-Driven Cross-Lingual Transfer of Dependency Parsers
Mohammad Sadegh Rasooli
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Michael Collins
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Dependency Grammar Induction with Neural Lexicalization and Big Training Data
Wenjuan Han
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Yong Jiang
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Kewei Tu
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Unsupervised Dependency Parsing: Let’s Use Supervised Parsers
Phong Le
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Willem Zuidema
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Unsupervised Dependency Parsing with Transferring Distribution via Parallel Guidance and Entropy Regularization
Xuezhe Ma
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Fei Xia
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Parse Imputation for Dependency Annotations
Jason Mielens
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Liang Sun
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Jason Baldridge
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Probing the Linguistic Strengths and Limitations of Unsupervised Grammar Induction
Yonatan Bisk
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Julia Hockenmaier
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Surface Statistics of an Unknown Language Indicate How to Parse It
Dingquan Wang
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Jason Eisner
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Merged bilingual trees based on Universal Dependencies in Machine Translation
David Mareček
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http://ufal.mff.cuni.cz/
Field Of Study
Task
Tagging
Approach
Generative Model
Language
Chinese
English
Japanese
Spanish
French
Arabic
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