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- W2250817354 abstract "Prepositional phrases (PPs) express crucial information that knowledge base construction methods need to extract. However, PPs are a major source of syntactic ambiguity and still pose problems in parsing. We present a method for resolving ambiguities arising from PPs, making extensive use of semantic knowledge from various resources. As training data, we use both labeled and unlabeled data, utilizing an expectation maximization algorithm for parameter estimation. Experiments show that our method yields improvements over existing methods including a state of the art dependency parser." @default.
- W2250817354 created "2016-06-24" @default.
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- W2250817354 date "2015-01-01" @default.
- W2250817354 modified "2023-09-27" @default.
- W2250817354 title "A Knowledge-Intensive Model for Prepositional Phrase Attachment" @default.
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- W2250817354 doi "https://doi.org/10.3115/v1/p15-1036" @default.
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