In the late nineteenth century, two excavators from the University of Oxford uncovered a vast trove of naturally deteriorated papyri, numbering over 500,000 fragments, from the city of Oxyrhynchus. With varying levels and forms of deterioration, the identification of a papyrus fragment can become a repetitive, long, and exhausting process for a professional papyrologist. The University of Oxford's Ancient Lives project aims to accelerate the identification process through citizen science (or crowdsourcing). In the Ancient Lives interface, volunteer users identify letters by clicking on a location in the image to designate the presence of a letter. To date, over 7 million letter identifications from users across the world have been recorded in the Ancient Lives database. In this paper, we present a computational pipeline for converting crowdsourced letter identifications made through the Ancient Lives interface into digital consensus transcriptions of papyrus fragments. We conclude by explaining the usefulness of the pipeline output in the context of additional computational projects that aim to further accelerate the identification process.