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Linguistically Rich Graph Based Data Driven Parsing For Hindi

机译:基于语言丰富的图形数据驱动的数据驱动解析

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In this paper we show how linguistic knowledge can be incorporated during graph based parsing. We use MSTParser and show that the use of a constraint graph, instead of a complete graph, to extract a spanning tree improves parsing accuracy. A constraint graph is formed by using linguistic knowledge of a constraint based parsing system. Through a series of experiments we formulate the optimal constraint graph that gives us the best accuracy. These experiments show that some of the previous MSTParser errors can be corrected consistently. It also shows the limitations of the proposed approach.
机译:在本文中,我们展示了在基于图的解析期间如何纳入语言知识。我们使用MSTParser并显示使用约束图,而不是完整的图形,以提取生成树提高解析精度。通过使用基于约束的解析系统的语言知识来形成约束图。通过一系列实验,我们制定了最佳的约束图,这为我们提供了最佳准确性。这些实验表明,可以一致地纠正了一些先前的MSTParser误差。它还显示了所提出的方法的局限性。

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