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Mining Local Discourse Annotation for Features of Global Discourse Structure

机译:基于全球话语结构特征的局部话语标注挖掘

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Descriptive approaches to discourse (text) structure and coherence typically proceed either in a bottom-up or a top-down analytic way. The former ones analyze how the smallest discourse units (clauses, sentences) are connected in their closest neighbourhood, locally, in a linear way. The latter ones postulate a hierarchical organization of smaller and larger units, sometimes also represent the whole text as a tree-like graph. In the present study, we mine a Czech corpus of 50k sentences annotated in the local coherence fashion (Penn Discourse Treebank style) for indices signalling higher discourse structure. We analyze patterns of overlapping discourse relations and look into hierarchies they form. The types and distributions of the detected patterns correspond to the results for English local annotation, with patterns not complying with the treelike interpretation at very low numbers. We also detect hierarchical organization of local discourse relations of up to 5 levels in the Czech data.
机译:话语(文本)结构和连贯性的描述性方法通常以自下而上或自上而下的分析方式进行。前者分析最小的话语单元(子句,句子)如何以线性方式在其最近邻域中本地连接。后者假定较小单位和较大单位的层次结构,有时也将整个文本表示为树状图。在本研究中,我们挖掘了一个捷克语语料库,该语料库以本地连贯方式(Penn话语树库样式)标注了5万个句子,以指示更高的话语结构。我们分析重叠的话语关系的模式,并研究它们形成的层次结构。检测到的模式的类型和分布与英语本地注释的结果相对应,其中模式以非常低的数量不符合树状解释。我们还可以在捷克语数据中检测多达5个级别的本地话语关系的层次结构。

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