Discourse Structuring of Dynamic Content

One of Natural Language Generation’s continuing challenges is to determine the structure and words of the generated linguistic output in accordance with the expertise of the user, the content, the appropriate genre, style, etc. We focus on the determination of the discourse structure. Most often, it is assumed that between two content units always the same discourse relation holds. Approaches in which the choice of discourse relations and the ordering of propositions depends on the interpretation of the content are still scarce. However, such an interpretation is extremely important especially if the content is highly dynamic as, e.g., in the case of data parameter time series. We present a text planner that takes into account the constraints imposed by dynamic data to make decisions at every stage of the text planning, and in particular, for the selection of discourse relations and the ordering of propositions.