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EMNLP
2010

Using Universal Linguistic Knowledge to Guide Grammar Induction

10 years 11 months ago
Using Universal Linguistic Knowledge to Guide Grammar Induction
We present an approach to grammar induction that utilizes syntactic universals to improve dependency parsing across a range of languages. Our method uses a single set of manually-specified language-independent rules that identify syntactic dependencies between pairs of syntactic categories that commonly occur across languages. During inference of the probabilistic model, we use posterior expectation constraints to require that a minimum proportion of the dependencies we infer be instances of these rules. We also automatically refine the syntactic categories given in our coarsely tagged input. Across six languages our approach outperforms state-of-theart unsupervised methods by a significant margin.1
Tahira Naseem, Harr Chen, Regina Barzilay, Mark Jo
Added 11 Feb 2011
Updated 11 Feb 2011
Type Journal
Year 2010
Where EMNLP
Authors Tahira Naseem, Harr Chen, Regina Barzilay, Mark Johnson
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