There is considerable interest in natural language conversational interfaces. These allow for complex user interactions with systems, such as fulfilling information requirements in dynamic environments, without requiring extensive training or a technical background (e.g. in formal query languages or schemas). To leverage the advantages of conversational interactions we propose CE-SAM (Controlled English Sensor Assignment to Missions), a system that guides users through refining and satisfying their information needs in the context of Intelligence, Surveillance, and Reconnaissance (ISR) operations. The rapidly-increasing availability of sensing assets and other information sources poses substantial challenges to effective ISR resource management. In a coalition context, the problem is even more complex, because assets may be owned" by different partners. We show how CE-SAM allows a user to refine and relate their ISR information needs to pre-existing concepts in an ISR knowledge base, via conversational interaction implemented on a tablet device. The knowledge base is represented using Controlled English (CE) - a form of controlled natural language that is both human-readable
and machine processable (i.e. can be used to implement automated reasoning). Users interact with the CE-SAM conversational interface using natural language, which the system converts to CE for feeding-back to the user for confirmation (e.g. to reduce misunderstanding). We show that this process not only allows users to access the assets that can support their mission needs, but also assists them in extending the CE knowledge base with new concepts.