Getting computers to talk like you and me
Getting computers to talk like you and me
Attention, intentions, and the structure of discourse
Computational Linguistics
Tailoring object descriptions to a user's level of expertise
Computational Linguistics - Special issue on user modeling
Generating Natural Language under Pragmatic Constraints
Generating Natural Language under Pragmatic Constraints
Reconstruction Proofs at the Assertion Level
CADE-12 Proceedings of the 12th International Conference on Automated Deduction
A reactive approach to explanation in expert and advice-giving systems
A reactive approach to explanation in expert and advice-giving systems
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
A fast algorithm for the generation of referring expressions
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 1
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This paper deals with the reference choices involved in the generation of argumentative text. A piece of argumentative text such as the proof of a mathematical theorem conveys a sequence of derivations. For each step of derivation, the premises (previously conveyed intermediate results) and the inference method (such as the application of a particular theorem or definition) must be made clear. The appropriateness of these references crucially affects the quality of the text produced. Although not restricted to nominal phrases, our reference decisions are similar to those concerning nominal subsequent referring expressions: they depend on the availability of the object referred to within a context and are sensitive to its attentional hierarchy. In this paper, we show how the current context can be appropriately segmented into an attentional hierarchy by viewing text generation as a combination of planned and unplanned behavior, and how the discourse theory of Reichmann can be adapted to handle our special reference problem.