Referring Expression Generation as a Search Problem

One of the most widely explored issues in natural language generation is the generation of referring expressions (gre): given an entity we want to refer to, how do we work out the content of a referring expression that uniquely identifies the intended referent? Over the last 15 years, a number of authors have proposed a wide range of algorithms for addressing different aspects of this problem, but the different approaches taken have made it very difficult to compare and contrast the algorithms provided in any meaningful way. In this paper, we propose a characterisation of the problem of referring expression generation as a search problem; this allows us to recast existing algorithms in a way that makes their similarities and differences clear.

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