Context-awareness refers to computing systems that are able to sense and to comprehend their environment in order to adapt themselves in dependence to the available and relevant contextual information they depend upon. Gathering such contextual information involves real world entities such as sensors, which, for various reasons, are often prone to certain degrees of uncertainty and inaccuracy. Nevertheless, high quality context information plays a vital role in ensuring correct system behavior as well as dynamic system and service adaptation. Thus, a set of indicators is required which allows determining the quality of contextual information, which is commonly known as Quality of Context (QoC). One of the most relevant parameter of the QoC is the Probability of Correctness (PoC), which expresses the level of confidence, that the contextual information sensed, are in fact correct or not. In this paper, we propose an approach for measuring the PoC of context information by firstly analyzing the nature of context information and, secondly, revisiting the concept of Quality of Context also discussing other QoC parameters. Finally, we present a novel approach for quantifying the PoC for specific context information and evaluate the proposed method on a concrete case study.