A Nearest-Neighbor Approach to the Automatic Analysis of Ancient Greek Morphology

We propose a data-driven method for automatically analyzing the morphology of ancient Greek. This method improves on existing ancient Greek analyzers in two ways. First, through the use of a nearestneighbor machine learning framework, the analyzer requires no hand-crafted rules. Second, it is able to predict novel roots, and to rerank its predictions by exploiting a large, unlabelled corpus of ancient Greek.