Exploiting Lexical Dependencies from Large-Scale Data for Better Shift-Reduce Constituency Parsing. In Proceedings of COLING 2012, pages 3171–3186, Mumbai, ...
A set of novel features defined on lexical dependency information obtained from a large amount of auto-parsed data are incorporated into the shift-reduce ...
This paper proposes a method to improve shift-reduce constituency parsing by using lexical dependencies. The lexical dependency information is obtained from ...
Constituency parsing aims to extract a constituency ... Exploiting Lexical Dependencies from Large-Scale Data for Better Shift-Reduce Constituency Parsing.
Second, we enhance shift-reduce parsing models with novel features that are defined on lexical dependency information. Both stages depend on the use of large- ...
A semi-supervised approach for advancing shift-reduce constituency parsing with improved part-of-speech taggers and novel features that are defined on ...
... reduce parsing models with novel features that are defined on lexical dependency information. Both stages depend on the use of large-scale unlabeled data.
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(2012) enriched feature representations of shift-reduce parsing by exploiting lexical dependencies extracted from large-scale automatically parsed data. Zhu et ...
Exploiting Lexical Dependencies from Large-Scale Data for Better Shift-Reduce Constituency Parsing · Muhua Zhu. This paper proposes a method to improve shift ...
Exploiting lexical dependencies from large scale data for better shift-reduce constituent parsing. ... Shift-Reduce Constituency Parser Using Feature ...