Mean Hierarchical Distance Augmenting Mean Dependency Distance

نویسندگان

  • Yingqi Jing
  • Haitao Liu
چکیده

With a dependency grammar, this study provides a unified method for calculating the syntactic complexity in linear and hierarchical dimensions. Two metrics, mean dependency distance (MDD) and mean hierarchical distance (MHD), one for each dimension, are adopted. Some results from the Czech-English dependency treebank are revealed: (1) Positive asymmetries in the distributions of the two metrics are observed in English and Czech, which indicates both languages prefer the minimalization of structural complexity in each dimension. (2) There are significantly positive correlations between sentence length (SL), MDD, and MHD. For longer sentences, English prefers to increase the MDD, while Czech tends to enhance the MHD. (3) A trade-off relationship of syntactic complexity in two dimensions is shown between the two languages. English tends to reduce the complexity of production in the hierarchical dimension, whereas Czech prefers to lessen the processing load in the linear dimension. (4) The threshold of the MDD2 and MHD2 in English and

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تاریخ انتشار 2015