Rome Wasn't Digitized in a Day - Council on Library and Information ...

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First, it utilizes a nearest neighbor framework that requires no hand-crafted rules, and provides
analogies to facilitate learn<strong>in</strong>g. Second, and perhaps more significantly, it exploits a large,
unlabelled corpus to improve the prediction of novel roots (Lee 2008).
Lee observed that many students of Ancient Greek memorized “paradigmatic” verbs that could be used
as analogies to identify the roots of unseen verbs. From this <strong>in</strong>sight, Lee utilized a “nearest-neighbor”
mach<strong>in</strong>e-learn<strong>in</strong>g framework to model this process. When given a word <strong>in</strong> an <strong>in</strong>flected form, the
algorithm searched for the root form among its “neighbors” by mak<strong>in</strong>g substitutions to its prefix and
suffix. Valid substitutions are harvested from pairs of <strong>in</strong>flected and root forms <strong>in</strong> a tra<strong>in</strong><strong>in</strong>g set of data,
and these pairs are then used to serve as “analogies to re<strong>in</strong>force learn<strong>in</strong>g.” Nonetheless, Ancient Greek
still posed some challenges that complicated a m<strong>in</strong>imally supervised approach. Lee expla<strong>in</strong>ed that
heavily <strong>in</strong>flected languages such as Greek suffer from “data sparseness” s<strong>in</strong>ce many <strong>in</strong>flected forms
appear at most a few times and many root forms may not appear at all <strong>in</strong> a corpus. As a rule-based
system, Morpheus needed a priori knowledge of possible stems and affixes, all of which had to be
crafted by hand. To provide a more scalable approach, Lee used a data-driven approach that
automatically determ<strong>in</strong>ed stems and affixes from tra<strong>in</strong><strong>in</strong>g data (morphology data for the Greek
Septuag<strong>in</strong>t from the University of Pennsylvania) and then used the TLG as a source of unlabeled data
to guide prediction of novel roots.
While Lee made use of mach<strong>in</strong>e learn<strong>in</strong>g and unlabeled corpora, Tambouratzis (2008) automated the
morphological segmentation of Greek by “coupl<strong>in</strong>g an iterative pattern-recognition algorithm with a
modest amount of l<strong>in</strong>guistic knowledge, expressed via a set of <strong>in</strong>teractions associated with weights.”
He used an “ant colony optimization (ACO) metaheuristic” to automatically determ<strong>in</strong>e optimal weight
values and found that <strong>in</strong> several cases the automatic system provided better results than those that had
been manually determ<strong>in</strong>ed by scholars. In contrast to Lee, Tambouratzis used only a subset of the TLG
for tra<strong>in</strong><strong>in</strong>g data (<strong>in</strong> this case, the speeches of several Greek orators).
In addition to the work done by Dik and Whal<strong>in</strong>g for “Perseus Under PhiloLogic,” other research <strong>in</strong>to
automatic morphological analysis of Lat<strong>in</strong> has been conducted by (F<strong>in</strong>kel and Stump 2009). These
authors reported on computational experiments to generate the morphology of Lat<strong>in</strong> verbs.
Lexicons
Lexicons are reference tools that have long played an important role <strong>in</strong> classical scholarship and
particularly <strong>in</strong> the study of historical languages. 153 As previously noted, the lack of a computational
lexicon for Sanskrit is a major research challenge. This section explores some important lexicons for
classical languages and suggests new roles for these traditional reference works <strong>in</strong> a digital
environment.
The Comprehensive Aramaic Lexicon 154 (CAL) hopes to serve as a “new dictionary of the Aramaic
language.” Aramaic is a Semitic language, and numerous <strong>in</strong>scriptions and papyri, as well as Biblical
and other religious texts, are written <strong>in</strong> it. This project, currently <strong>in</strong> preparation by an <strong>in</strong>ternational
team of scholars, is based at Hebrew Union College <strong>in</strong> C<strong>in</strong>c<strong>in</strong>nati. The goal is to create a
comprehensive lexicon that will take all of ancient Aramaic <strong>in</strong>to account, be based on a compilation of
all Aramaic literature, and <strong>in</strong>clude extensive references to modern scholarly literature. Although a
153 This section focuses on larger projects that plan to create onl<strong>in</strong>e or digital lexicons <strong>in</strong> addition to pr<strong>in</strong>ted ones, but there are also a number of lexicons
for classical languages that have been placed onl<strong>in</strong>e as PDFs or <strong>in</strong> other static formats, such as the Chicago Demotic Dictionary
(http://oi.uchicago.edu/research/projects/dem/); other projects have scanned historical dictionaries and provided onl<strong>in</strong>e search<strong>in</strong>g capabilities, such as
Sanskrit, Tamil and Pahlavi Dictionaries, http://webapps.uni-koeln.de/tamil/
154 http://cal1.cn.huc.edu/