This paper introduces a new corpus of multilin- gual medieval handwritten charter images, annotated with full transcription and named entities. The corpus is used to com- pare two approaches for named entity recognition in historical document images in several languages: on the one hand, a sequential approach, more commonly used, that sequentially applies handwritten text recognition (HTR) and named entity recognition (NER), on the other hand, a combined approach that simultaneously transcribes the image text line and extracts the entities. Experiments conducted on the charter corpus in Latin, early new high German and old Czech for name, date and location recognition demonstrate a superior performance of the combined approach.