Language is inextricably linked to the activities and events that make up our daily lives. For a child learning language, everyday activities provide an important context for learning first words. This work builds on the corpus collected for the Human Speechome Project, the largest multimodal corpus of one child's early life, to explore how experience with language ties to space, time, and daily activity to support word learning. We use manual and fully automatic methods, ranging from direct annotation to computer vision and unsupervised latent variable approaches, to identify the abstract "stuff of life" that makes up early experience. We show how a word's contextual grounding predicts when it will be learned.