In this paper, some experiments with a Rule-Based Discourse Structure Builder (DSB) Engine are presented. The DSB discussed here is a Rule-Based Engine that identifies discourse relations based on centering status of entities in the text, rather than on cohesive devices. In the design of the DSB Engine some abstract notions have been defined. Addressing these notions according to a set of theories in natural language processing provides an engine for revealing discourse structure. Here in this paper, experiments with one of the possible settings are presented. The results show that the engine reveals discourse structures of the texts significantly. Although the Rule Set that was used in this experiment was a hand-tuned one, it produced Discourse Trees with 80% accuracy comparing to the ones suggested by human annotators.

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The paper introduces a two-tier writing support tool that helps students at school in writing more coherent essays.At one tier, students enter their essays and submit it for further process. At the other tier, the tutor receives the segmented format of their essays. The software prepares an environment to tutors for annotating students' essays in terms of a specific kind of annotation. Based-on the annotation the software produces a tree-shape graph representative of discourse structure of essays and sends it to the respective student.By observing many trees of this kind, we hope students understand the concept of discourse and write more coherent essays as a result. In the software, a novel Discourse Structure Builder Engine that has been recently proposed by researchers constructs the Discourse Tree based on a set of optimized discourse cue rules. In this paper it has been also shown why the software effectively reaches its aim, having looked at known theories in the concept of writing.