Abstract
In previous work we introduced the idea of supertagging as a means of improving the efficiency of a lexicalized grammar parser. In this paper, we present supertagging in conjunction with a lightweight dependency analyzer as a robust and efficient partial parser. The present work is significant for two reasons. First, we have vastly improved our results; 92% accurate for supertag disambiguation using lexical information, larger training corpus and smoothing techniques. Second, we show how supertagging can be used for partial parsing and provide detailed evaluation results for detecting noun chunks, verb chunks, preposition phrase attachment and a variety of other linguistic constructions.
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Bangalore, S. (2000). Performance Evaluation of Supertagging for Partial Parsing. In: Bunt, H., Nijholt, A. (eds) Advances in Probabilistic and Other Parsing Technologies. Text, Speech and Language Technology, vol 16. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9470-7_11
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DOI: https://doi.org/10.1007/978-94-015-9470-7_11
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