Ensuring that a knowledge base with public administration acts contains only facts in accordance with its legislation becomes a challenge for any public manager. To achieve this, given the large volume of data generated by public companies, it is necessary to apply technological resources that assist in the process of analyzing the compliance of these acts. This work presents a computational architecture capable of extracting information published in official gazettes and then serializing it into two knowledge bases, RDF/XML triples of facts and RDF/XML triples of rules formalized in iALC logic, an intuitionistic description logic. To ensure the consistency of this knowledge base, a SAT Solver for iALC was developed in the form of an intuitionistic semantic tableau. An extension of the first-order intuitionist tableau presented by Fitting (1960). This SAT Solver is part of a module that generates models and counter-examples for rules formalized in iALC and generates a preliminary query code in SPARQL. This approach allows infer and certify the quality of the data available in the RDF/XML knowledge base of facts. To guarantee the quality of our SAT Solver, we carry out the soundness proof of its rules. To ensure the quality of our logical approach, we built a set of 21 Competency Questions and applied our tool. The results of this case study showed our approach s effectiveness and efficiency.