Function-based reasoning is widely cited in design research and is argued to be effective in solving design problems creatively. Knowledge of a system’s function and its functioning, i.e., how a natural or engineered system works, can act as a powerful stimulus in design ideation and is useful for developing innovative products. The choice of inspiration matters, and design research suggests that text-based stimuli are used as inspiration. While research on how inspiration occurs is often carried out in laboratory settings, how this happens with ordinary designers in regular design tasks is not well documented. Our observations from design projects by university students outside of lab settings, as detailed in this paper, did not reveal much about how designers identify, explore, evaluate, and assimilate design inspirations. Additionally, the literature does not explain how to identify the function of a system from natural language text and check the completeness of the information. In this research, we present a set of rules for identifying information relevant to the functioning of a system from a description in natural language text and validate these rules. Additionally, we propose a simple process to check the completeness of information relevant to system functioning by using the SAPPhIRE model of causality and present an illustration of the process.