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Dependency-length minimization in natural and artificial languages*

机译:自然语言和人工语言中的依赖长度最小化*

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摘要

A wide range of evidence points to a preference for syntactic structures in which dependencies are short. Here we examine the question: what kinds of dependency configurations minimize dependency length? We consider two well-established principles of dependency-length minimization; that dependencies should be consistently right-branching or left-branching, and that shorter dependent phrases should be closer to the head. We also add a third, novel, principle; that some “opposite-branching” of one-word phrases is desirable. In a series of computational experiments, using unordered dependency trees gathered from written English, we examine the effect of these three principles on dependency length, and show that all three contribute significantly to dependency-length reduction. Finally, we present what appears to be the optimal “grammar” for dependency-length minimization.
机译:大量证据表明,人们倾向于偏爱依赖关系短的句法结构。在这里,我们研究以下问题:哪种类型的依赖项配置可以最小化依赖项长度?我们考虑了两个建立良好的依赖长度最小化原则;依存关系应始终为右分支或左分支,较短的依存短语应更接近头部。我们还增加了第三条新颖的原则。一个单词词组的一些“相反分支”是可取的。在一系列计算实验中,使用从书面英语中收集的无序依赖树,我们检查了这三个原理对依赖长度的影响,并表明这三个原理都对减少依赖长度起到了重要作用。最后,我们介绍了对于依赖项长度最小化而言似乎是最佳的“语法”。

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