Generating Inference-Rich Discourse through Revisions of RST-Trees

Helmut Horacek

The majority of generation systems to date are able to communicate information only by uttering it explicitly. Rhetorical Structure Theory (RST), one of the most frequently used discourse theories for text planning in natural language generation, does not support more flexibility either, because it ignores implicit rhetorical relations and accepts only one prominent relation between clauses. In formal systems, however, the underlying information is represented in a very detailed way, which requires easily inferable parts to be left implicit for producing natural and comprehensible discourse. In order to improve the quality of texts generated from fine-grained semantic specifications, we present an approach that successively revises an explicit text plan by introducing addressee dependent short-cuts and communicatively justified reorganizations. Text plan revisions include the compactification of state-action and reasoning sequences, the omission of redundant conditions, and the reorganization of arguments for presentation purposes. Our techniques enable us to generate shorter and better understandable texts from detailed representations, as in formal systems, especially in deduction systems.


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