Concept location is a common task in program comprehension techniques, essential in many approaches used for software care and software evolution. An important goal of this process is to discover a mapping between source code and human oriented concepts. Although programs are written in a strict and formal language, natural language terms and sentences like identifiers (variables or functions names), constant strings or comments, can still be found embedded in programs. Using terminology concepts and natural language processing techniques these terms can be exploited to discover clues about which real world concepts source code is addressing. This work extends symbol tables build by compilers with ontology driven constructs, extends synonym sets defined by linguistics, with automatically created Probabilistic SynSets from software domain parallel corpora. And using a relational algebra, creates semantic bridges between program elements and human oriented concepts, to enhance concept location tasks.