These guidelines explain how to proceed in the correction and validation of multilingual corpora created via annotation projection techniques. They outline the goal of the task, the framework used, the necessary actions and the specific rules to be considered. The ultimate goal is to leverage high quality datasets written in one language to train artificial intelligence systems in as many languages as needed. They have been used for multiple datasets, including but not limited to: Datasets for "Exploring the potential of neural machine translation for cross-language clinical NLP resource generation through annotation projection" License This work is licensed under a Creative Commons Attribution 4.0 International License. Contact If you have any questions or suggestions, please contact us at: - Salvador Lima-López ()- Martin Krallinger ()