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A parallel parsing algorithm for natural language using tree adjoining grammar

机译:使用树相邻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(标签)是一种强大的语法形式,用于大规模的自然语言处理。然而,标签解析算法的计算复杂性很高。我们使用大粒度语法分区,异步通信和分布式终止检测来介绍用于MIMD HyperCube多电脑的新并行标签解析算法。我们在NCube / 2并行计算机上描述了我们的实现,并为随机和英语语法提供了实验结果。我们的算法迄今为止,提供了任何标签解析算法的最佳性能,产生了几乎两个数量级加速和高达256个处理器的良好效率。标签解析是一个非常非结构化的问题。根据我们开发平行标签解析器的经验,我们得出了一些概括的结论,以解决其他非结构化问题。

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