Abstract The United Kingdom’s Maritime Heritage records hold vital information on heritage assets and archaeological contexts key to addressing current research priorities. These records stand alone, rarely connecting, demanding an arduous and time-consuming process of investigation and cross-referencing for synthesis to occur. Challenges intensify due to the qualities of this data; they stem partly from legacy information not initially intended for heritage recording purposes. Complications also arise from the varied methods of recording, storing, and disseminating this information deployed over time. However, archaeologists now possess Named Entity Recognition (NER) and Natural Language Processing (NLP) tools with the potential to organize and search such fragmented databases. This paper explores a method to enhance and enrich these datasets by employing Few Shot learning techniques to perform Multiclass Text Classification. The Welsh National Monuments Record (NMR), a glimpse into the U.K.’s maritime heritage, has been utilized to test these approaches.
Pink et al. (Mon,) studied this question.