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ACL
2008
13 years 10 months ago
Semi-Supervised Convex Training for Dependency Parsing
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Qin Iris Wang, Dale Schuurmans, Dekang Lin
NIPS
2001
13 years 10 months ago
A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing
Narayanan and Jurafsky (1998) proposed that human language comprehension can be modeled by treating human comprehenders as Bayesian reasoners, and modeling the comprehension proce...
S. Narayanan, Daniel Jurafsky
ACL
2010
13 years 7 months ago
Detecting Errors in Automatically-Parsed Dependency Relations
We outline different methods to detect errors in automatically-parsed dependency corpora, by comparing so-called dependency rules to their representation in the training data and ...
Markus Dickinson
ACL
2006
13 years 10 months ago
QuestionBank: Creating a Corpus of Parse-Annotated Questions
This paper describes the development of QuestionBank, a corpus of 4000 parseannotated questions for (i) use in training parsers employed in QA, and (ii) evaluation of question par...
John Judge, Aoife Cahill, Josef van Genabith
EMNLP
2008
13 years 10 months ago
A Tale of Two Parsers: Investigating and Combining Graph-based and Transition-based Dependency Parsing
Graph-based and transition-based approaches to dependency parsing adopt very different views of the problem, each view having its own strengths and limitations. We study both appr...
Yue Zhang 0004, Stephen Clark