Commonly, the result of referring expression generation algorithms is a single noun phrase. In interactive settings with a shared workspace, however, human dialog partners often split referring expressions into installments that adapt to changes in the context and to actions of their partners. We present a corpus of human–human interactions in the \textsc{GIVE-2} setting in which instructions are spoken. A first study of object descriptions in this corpus shows that references in installments are quite common in this scenario and suggests that contextual factors partly determine their use. We discuss what new challenges this creates for NLG systems.