Abstract
This chapter presents a new technique for selecting the correct parse of ambiguous sentences based on a probabilistic analysis of lexical co-occurrences in semantic forms. The method is called ‘Semco’ (for semantic co-occurrence analysis) and is specifically targeted at the differential distribution of such co-occurrences in correct and incorrect parses. It uses Bayesian Estimation for the co-occurrence probabilities to achieve higher accuracy for sparse data than the more common Maximum Likelihood Estimation would. It has been tested on the Wall Street Journal corpus (in the Perm Treebank) and shown to find the correct parse of 60.9% of parseable sentences of 6–20 words.
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Hektoen, E. (2000). Probabilistic Parse Selection Based on Semantic Co-Occurrences. 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_9
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DOI: https://doi.org/10.1007/978-94-015-9470-7_9
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-5579-8
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