Detecting Sexual Content at the Sentence Level in First Millennium Latin Texts

arXiv:2309.14974v2 Announce Type: replace
Abstract: In this study, we propose to evaluate the use of deep learning methods for semantic classification at the sentence level to accelerate the process of corpus building in the field of humanities and linguistics, a traditional and time-consuming task. We introduce a novel corpus comprising around 2500 sentences spanning from 300 BCE to 900 CE including sexual semantics (medical, erotica, etc.). We evaluate various sentence classification approaches and different input embedding layers, and show that …

abstract arxiv building classification cs.ai cs.cl deep learning humanities linguistics novel process semantic study type