Lifelogging is the digital recording of our everyday behaviour in order to identify human activities and build applications that support daily life. Lifelogs represent a unique form of personal multimedia content in that they are temporal, synchronised, multi-modal and composed of multiple media. Analysing lifelogs with a view to supporting content-based access, presents many challenges. These include the integration of heterogeneous input streams from different sensors, structuring a lifelog into events, representing events, and interpreting and understanding lifelogs. In this paper we demonstrate the potential of semantic web technologies for analysing lifelogs by automatically augmenting descriptions of lifelog events. We report on experiments and demonstrate how our re- sults yield rich descriptions of multi-modal, multimedia lifelog content, opening up even greater possibilities for managing and using lifelogs.