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Mining Local Discourse Annotation for Features of Global Discourse Structure

Publication at Faculty of Mathematics and Physics |
2020

Abstract

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 tree-like interpretation at very low numbers.

We also detect hierarchical organization of local discourse relations of up to 5 levels in the Czech data.