A fundamental problem in conformance checking is aligning event data with process models. Unfortunately, existing techniques for this task are either complex, or can only be applicable to restricted classes of models. This in practice means that for large inputs, current techniques often fail to produce a result. In this paper we propose a method to approximate alignments for unconstrained process models, which relies on the use of relaxation labelling techniques on top of a partial order representation of the process model. The implementation on the proposed technique achieves a speed-up of several orders of magnitude with respect to the approaches in the literature (either optimal or approximate), often with a reasonable trade-off on the ...