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• W2142333053 abstract "We introduce a shift-reduce parsing algorithm for phrase-based string-todependency translation. As the algorithm generates dependency trees for partial translations left-to-right in decoding, it allows for efficient integration of both n-gram and dependency language models. To resolve conflicts in shift-reduce parsing, we propose a maximum entropy model trained on the derivation graph of training data. As our approach combines the merits of phrase-based and string-todependency models, it achieves significant improvements over the two baselines on the NIST Chinese-English datasets." @default.
• W2142333053 created "2016-06-24" @default.
• W2142333053 creator A5086000078 @default.
• W2142333053 date "2013-08-01" @default.
• W2142333053 modified "2023-09-26" @default.
• W2142333053 title "A Shift-Reduce Parsing Algorithm for Phrase-based String-to-Dependency Translation" @default.
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