Referring wisely? or referring when you need help?

Referring Relationships

Images are not simply sets of objects: each image represents a web of interconnected relationships. These relationships between entities carry semantic meaning and help a viewer differentiate between instances of an entity. For example, in an image of a soccer match, there may be multiple persons present, but each participates in different relationships: one is kicking the ball, and the other i...

Using aggregation for selecting content when generating referring expressions

Previous algorithms for the generation of referring expressions have been developed specifically for this purpose. Here we introduce an alternative approach based on a fully generic aggregation method also motivated for other generation tasks. We argue that the alternative contributes to a more integrated and uniform approach to content determination in the context of complete noun phrase gener...

Against Structured Referring Expressions

Generating Contrastive Referring Expressions

The referring expressions (REs) produced by a natural language generation (NLG) system can be misunderstood by the hearer, even when they are semantically correct. In an interactive setting, the NLG system can try to recognize such misunderstandings and correct them. We present an algorithm for generating corrective REs that use contrastive focus (“no, the BLUE button”) to emphasize the informa...

Referring Via Document Parts

Documents in a wide range of genres often contain references to their own sections, pictures etc. We call such referring expressions instances of Document Deixis. The present work focuses on the generation of Document Deixis in the context of a particular kind of natural language generation system in which these descriptions are not specified as part of the input, i.e., when it is up to the sys...