 Bar-Hillel and Carnap define two distinct methods for quantitative calculations of semantic information—a content measure (cont), and an information measure (inf). They start with an a priori probability measure of a sentence \(s\), \(p(s)\), which is gotten from an a priori distribution. The a priori distribution onto \(W\) sums to 1, and we assume that all assignments are equiprobable, hence the a priori probability measure is the value of \(p(s)\) that results from this distribution. In this case, cont and inf can be defined as follows: