Temporal networks -- sequences of time-stamped contacts among nodes -- constitute the finest-grained representation of dynamic interaction data; however, geometric and topological analyses of such networks have remained largely confined to time-aggregated or snapshot-based approximations. Such reductions destroy the temporal ordering and interevent statistics essential for understanding spreading dynamics, synchronization, and information flow. This study proposes a geometric framework that lifts a contact-sequence temporal network into a genuine simplicial complex through a prism construction adapted from algebraic topology. On this spatiotemporal prism complex, we develop the Forman--Ricci curvature in its original CW-complex form and contrast it with an augmented variant widely used in network science. We prove that the two variants coincide under uniform weights, derive a closed-form expression for their pointwise discrepancy in the general case, and identify the precise conditions under which they diverge -- conditions generically satisfied in temporal networks because temporal edges carry interval-dependent weights. Numerical experiments on three synthetic contact-network models (Erd\H os--Rényi, activity-driven, and bursty) and on the SocioPatterns Hypertext 2009 face-to-face contact dataset quantitatively confirm the theoretical predictions: the two Forman variants disagree on $56$--$67\%$ of the $1$-simplices -- predominantly the temporal and diagonal simplices -- while remaining strongly correlated according to the Pearson coefficient. The proposed framework provides a principled, parameter-free method for assigning discrete Ricci curvature to each contact event, thereby opening a new geometric avenue for temporal data analysis.