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Annotating the regions, text lines and characters of document images is an important, but tedious and expensive task. A ground-truthing tool may largely alleviate the human burden in this process. This paper describes an automated recognition-based tool GTLC for finding the best alignment between the text transcript and the connected components of unconstrained handwritten document image. The alignment process is formulated as an optimization problem involving candidate character segmentation and recognition. We have validated the effectiveness of this tool and have used it for annotating a large number of handwritten Chinese documents.