Towards a psycholinguistically motivated algorithm for referring to sets: The role of semantic similarity

This paper explores the role of semantic similarity in content selection and aggregation of expressions referring to sets. Similarity plays a role in ensuring that a referring expression corresponds to a coherent conceptual gestalt. On the basis of corpusbased and experimental evidence we propose an algorithm which (a) separates content selection and aggregation to avoid a combinatorial explosion; (b) uses similarity between entities to prioritise among search alternatives.