Merging parallel versions of source code is a common and essential activity during the lifespan of large-scale software systems. When a non-trivial number of conflicts is detected, there is a need to support the maintainer in investigating and resolving these conflicts. In this paper, we contribute a cost-benefit approach to ranking the conflicting software entities by leveraging both structural and semantic information of the source code. We present a study by applying our approach to a legacy system developed by computational scientists. The study not only demonstrates the feasibility of our approach, but also sheds light on the future development of conflict resolution recommenders.