A precise syntacto-semantic analysis of English requires a large detailed lexicon with the possibility of treating multiple tokens as a single meaning-bearing unit, a word-with-spaces. However parsing with such a lexicon, as included in the English Resource Grammar, can be very slow. We show that we can apply supertagging techniques over an ambiguous token lattice without resorting to previously used heuristics, a process we call ubertagging. Our model achieves an ubertagging accuracy that can lead to a four to eight fold speed up while improving parser accuracy.
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Ubertagging: Joint Segmentation and Supertagging for English
Semantic Scholar · Computer Science · 2013
Abstract
A precise syntacto-semantic analysis of English requires a large detailed lexicon with the possibility of treating multiple tokens as a single meaning-bearing unit, a word-with-spaces. However parsing with such a lexicon, as included in the English Resource Grammar, can be very slow. We show that we can apply supertagging techniques over an ambiguous token lattice without resorting to previously used heuristics, a process we call ubertagging. Our model achieves an ubertagging accuracy that can lead to a four to eight fold speed up while improving parser accuracy.
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