Puns and Intertextuality: A Digital Approach to Greek Wordplay in Latin
Literature

Evan Brubaker

ebrubak@tulane.edu

Tulane University, United States of America

Brandon LaFreniere

blaf@startmail.com

Tulane University, United States of America

Background

As one of the defining features of Latin literature, the influence exerted by
the Greek linguistic and textual traditions has remained a key focus of the
Classics. One of the manifestations of this intersection of cultures is in the
topic of wordplay, or puns. Authors such as Vergil and Lucretius have been
shown to utilize the metrical rules of pronunciation to embed Greek word forms
in their poetry, and in the process, reference others works of literature and
convey ideas beyond the superficial level of the text. While the influence
of Greek writings upon Latin literature has received considerable scrutiny, the
use of Greek puns has received only limited inquiry. Previous studies on puns,
notably those of Snyder (1980) and Ahl (1985) are limited in scope and focus
mainly on the relationship of Latin puns to Latin literature. Furthermore,
studies which focus on Greek puns within Latin are limited primarily to writing
about specific examples or a specific Latin author, such as O'Hara (1996) and
his discussion of Greek word use in Vergil. Similarly, the recent (2013)
 compilation of studies edited by Kwapisz, Szymanski, and Petrain examining
Greek and Latin wordplay does not look at the intersection of the two. Building
upon previous strategies for data mining including the Tesserae Project, this
paper seeks to offer a digital means to cross-reference Latin literature with
Greek texts in order to find puns.

The program

Since the formation of our collaboration, we have produced software capable of
detecting potential candidates for Greek puns. To achieve this end, we first
set out to account for the rules of pronunciation within

Latin poetry by referencing works such as Halporn et al. (1980), with issues
such as elision and the lack of pronunciation of certain syllables addressed
within the software. We then looked to set equivalence of pronunciation between
Greek and Latin letters and groups of syllables, such as diphthongs. This was
accomplished through examining transliterated Greek names and words which
appear in Latin literature and using grammars including Smyth (1920).
Additionally, certain Greek vowels and consonants which could correspond to
multiple vowels, consonants, or syllables in Latin were also considered.

Accounting for these rules, we developed a processing system whereby Greek
pronunciation equivalence is run through strands of Latin text. The software
begins by reading one chosen Latin text in .txt format and then reading one or
more Greek texts in .txt format, with all texts requiring UNICODE encoding
for proper registration within the identification system. Once a Latin and
Greek text(s) have been selected, the file paths are passed asynchronously into
the model for processing. Both texts are then processed at the same time on
different threads and the calling method waits for the completion of both
methods.

The Greek text string is first processed by stripping off any accent or
breathing mark and returning the base letter to lower case. While iterating
through all characters in the text, when a space or new line character is
reached, the previous word captured is added to a list. A word is not added to
the list if it has previously been added to the list or the length of the
word is less than a number for which the program allows specification. The
result of this method is a list of those unique Greek words which appear in a
chosen Greek text.

The Latin text string is first processed by converting all letters to lower
case and taking account of the rules of elision and pronunciation. Similar to
the Greek processing, the processed Latin text is converted into words. Each
Latin word in the list is processed to determine if part of the word should be
elided, based on the starting letter of the next word. The final step is
to condense all the Latin words together into one text string without spaces,
while keeping a list of the starting position of each word in the text string.

Once the two processing methods reach completion, the model has the list of
unique Greek words and a string of Latin words, including the starting
position in the original text of each word. The final processing method
compares the Greek words to the Latin text string to find matches and returns a
list of matches, which include the starting position of the match, ending
position of the match, and the Greek word that matched. First, each letter of
every Greek word is converted to a list of possible Latin characters or pairs
of characters. A dictionary exists that for each base Greek lower case letter
there corresponds a list of Latin letters or pairs of letters. Similarly, the
existence of a diphthong is determined by referencing the values of a
Greek-Latin diphthong dictionary. Both dictionaries were developed by examining
those grammars and references noted earlier. By iterating though every Greek
letter in a Greek word the possible Latin letters can be looked up in the
dictionary, and, if the current letter and next letter in the Greek word are in
the diphthong dictionary, this will override the regular dictionary lookup
function. Once a list of every possible Latin correspondence for every letter
in a Greek word exists, all permutations of letters are returned in a list
of strings. This list is the list of every possible Latin series of characters
that could match a Greek word. Using a regular expression every match in the
Latin text string is found based on the previous list. These results
are returned as a list of Greek words, including the starting and ending
position in the original Latin text of the match.

The unique list of Latin-to-Greek results is returned to the view and is
displayed in a grid, which can be sorted alphabetically, wherein the left
column contains the uncompressed Latin character matches and the right column
the Greek word equivalent in Greek characters. Also, a flow document is created
which contains the original text with the matches highlighted in yellow and the
matching Greek words to the right for each line. The Greek words in brackets
are words that correspond to the same Latin text location, thus assisting the
program user in contextualizing and applying significance to the results.

Results and applications

Through operation of the software, possible candidates for Greek puns within
various Latin authors have been identified. By cross-referencing opensource
texts of Vergil's Aeneid and the Carmina of Catullus with the Homeric epics and
Argonautica, we have discovered hereto unnoticed Greek words, the meanings of
which often correspond to the thematic concerns of the passage. Considering the
limited extent of the search, both in duration and in those texts analyzed,
these results seem to suggest that there are a considerable number of Greek
puns remaining to be found within the corpus of Latin literature. While we are
currently still in the process of refining the software and in consideration of
more comprehensive ways to cross-reference Greek texts, we are still looking to
expand the search both towards those texts already analyzed and to other Latin
authors. With a view to the future, it is our hope that this software
will eventually become available for public use and that it can lead to a more
nuanced view of the role which Greek culture and language plays in Latin
literature.

Program diagram

Input one Latin and one or more Greektexts in .txt format

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