CICLing 2004: Computational Linguistics and Intelligent Text Processing pp 112-123 | Cite as
Unlexicalized Dependency Parser for Variable Word Order Languages Based on Local Contextual Pattern
Conference paper
Abstract
We investigate the effect of unlexicalization in a dependency parser for variable word order languages and propose an unlexicalized parser which can utilize some contextual information in order to achieve performance comparable to that of lexicalized parsers. Unlexicalization of an early dependency parser makes performance decrease by 3.6%. However, when we modify the unlexicalized parser into the one which can consider additional contextual information, the parser performs better than some lexicalized dependency parsers, while it requires simpler smoothing processes, less time and space for parsing.
Keywords
Word Order Dependency Relation Distance Probability Dependency Parser Phrase Structure Grammar
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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