From Local to Global Coherence: A Bottom-Up Approach to Text Planning

Daniel Marcu

We present a new, data-driven approach to text planning, which can be used not only to map full knowledge pools into natural language texts, but also to generate texts that satisfy multiple, high-level communicative goals. The approach explains how global coherence can be achieved by exploiting the local coherence constraints of rhetorical relations. The local constraints were derived from a corpus analysis.


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