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Dual decomposition method for chinese predicate-argument structure analysis

机译:汉语谓词-参数结构分析的对偶分解方法

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Most of the previous work on predicate-argument(PA) structure analysis utilized pipeline strategies with several subtasks. However, when the subtasks are sequentially processed, the errors propagate from the preceding subtasks to consecutive subtasks. In this paper, the PA structure analysis is divided into three subtasks: predicate sense disambiguation, argument classification and argument identification. A dual decomposition method is used to join the latter two subtasks, which alleviates the error propagation by making the decisions from the two subtasks as consistent as possible. Furthermore the predicate sense disambiguation task is integrated into the argument classification task by handling syntactic dependencies and semantic dependencies between a predicate and its arguments. Experiments show that our approach achieves competitive results compared to the state-of-the-art systems without special feature selection procedures.
机译:先前有关谓词参数(PA)结构分析的大多数工作都使用带有多个子任务的流水线策略。但是,当顺序处理子任务时,错误会从前面的子任务传播到连续的子任务。本文将PA结构分析分为三个子任务:谓词义消歧,论点分类和论点识别。使用双重分解方法来合并后两个子任务,该方法通过使来自两个子任务的决策尽可能一致来减轻错误传播。此外,通过处理谓词及其自变量之间的句法依赖性和语义依赖性,将谓词意义上的歧义消除任务集成到自变量分类任务中。实验表明,与没有特殊功能选择程序的最新系统相比,我们的方法可实现竞争性结果。

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