While much of the research and labor in treebanks has focused on modern languages, recent scholarship has also seen the rise of treebanks for historical languages as well, such as Middle English (Kroch and Taylor [15]), Early Modern English (Kroch et al. [16]), Old English (Taylor et al. [28]), Early New High German (Demske et al. [11]) and Medieval Portuguese (Rocio et al. [27]). Like their modern counterparts, these historical treebanks serve two distinct ends and often two different audiences: they provide crucial datasets for NLP projects such as automatic parsing and grammar induction while also providing a valuable corpus for scholars researching the state of a language and its progression across time. Historical treebanks, however, also offer one additional benefit over modern treebanks: they provide an annotated set of texts that scholars actually care about. When linguists of modern languages base theories on corpus evidence, their analysis is generally directed toward the language at large; few, if any, pore over the Wall Street Journal examining its use of an arcane literary device. If the corpus is Vergil, however, we do. The sheer volume of Latin texts available electronically1 not to mention the enormous mass still locked in print is much larger than the small community of scholars and students who can read it. This alone justifies a treebank as a resource for those attempting to learn the language, but it also highlights the need for automatic methods of parsing and machine translation. To this end a Latin treebank will well serve the NLP community, which has a long history of applying such research to modern languages.2 Classical scholars, however, largely operate on a fixed canon of texts. The value of a treebank for them is not so much in training