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A parallel parsing algorithm for natural language using tree adjoining grammar

机译:利用树邻接语法的自然语言并行解析算法

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Tree Adjoining Grammar (TAG) is a powerful grammatical formalism for large-scale natural language processing. However, the computational complexity of parsing algorithms for TAG is high. We introduce a new parallel TAG parsing algorithm for MIMD hypercube multicomputers, using large-granularity grammar partitioning, asynchronous communication, and distributed termination detection. We describe our implementation on the nCUBE/2 parallel computer, and provide experimental results on both random and English grammars. Our algorithm delivers the best performance of any TAG parsing algorithm to date, yielding an almost two order-of-magnitude speedup and good efficiency on up to 256 processors. TAG parsing is a highly unstructured problem. Based on our experience developing a parallel TAG parser, we draw some general conclusions for solving other unstructured problems.
机译:树邻接语法(TAG)是用于大规模自然语言处理的强大语法形式。然而,用于TAG的解析算法的计算复杂度很高。我们使用大粒度语法分区,异步通信和分布式终止检测为MIMD超立方体多计算机引入了一种新的并行TAG解析算法。我们描述了在nCUBE / 2并行计算机上的实现,并提供了随机和英语语法的实验结果。我们的算法提供了迄今为止所有TAG解析算法中最好的性能,在多达256个处理器上产生了近两个数量级的加速,并具有良好的效率。 TAG解析是一个高度非结构化的问题。根据我们开发并行TAG解析器的经验,我们得出了解决其他非结构化问题的一些一般性结论。

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