This topic investigates the quality and correctness of nine automatically assigned labels for merge-conflict resolutions. The labels were reconstructed by replaying historical Git merges and mapping the tentative conflict representation to the final developer-committed file. Such mappings are reproducible and scalable, but they can be affected by formatting changes, reordered code, structural edits, ambiguous correspondence between conflict chunks, and compound resolutions. The project will develop methods to detect potentially incorrect, ambiguous, or unstable labels and will validate a sample of these cases through systematic inspection. The work combines supervised, unsupervised, and weakly supervised methods for label-quality assessment.