Using and evaluating TRACER for an Index fontium computatus of the Summa contra Gentiles of Thomas Aquinas
Authors: Greta Franzini, Marco Carlo Passarotti, Maria Moritz, Marco Buechler (Università Cattolica del Sacro Cuore, Georg-August-Universität Göttingen, 2018)
Topic: Latin Resources

Abstract
This article describes a computaEnglish. This article describes a computational text reuse study on Latin texts designed to evaluate the performance of TRACER, a language-agnostic text reuse detection engine. As a case study, we use the Index Thomisticus as a gold standard to measure the performance of the tool in identifying text reuse between Thomas Aquinas’ Summa contra Gentiles and his sources.

Introduction
Thomas Aquinas (1225-1274) was a proliﬁc medieval author from Italy: his 118 works, known as the Corpus Thomisticum, amount to 8,767,883 words (Portalupi, 1994, p. 583) and discuss a variety of topics, ranging from metaphysical to legal, political and moral theory (Kretzmann and Stump, 1993). The web of references to biblical, ecclesiastical and classical literature that stretches the whole Corpus Thomisticum speaks to daunting erudition. In the late 1940s, Humanities Computing pioneer Father Roberto Busa (1913-2011) spearheaded a scholarly effort, known as the Index Thomisticus, to manually annotate reuse, both explicit (i.e., explicitly introduced by Aquinas as a quote) and implicit (i.e., reference to works without quotation), in the texts of Thomas Aquinas (Busa, 1980). Four decades later, Portalupi noted: Ancora pi`u difﬁcile sar`a [...] il tentativo di confrontare automaticamente tutto Tommaso con tutti i testi di uno o pi`u autori, per rintracciare in modo globale la presenza implicita di una fonte. Per fare questo occorrerebbe che si veriﬁcassero due condizioni: in primo luogo, gli autori di cui si studiano le presenze implicite in Tommaso dovrebbero essere informatizzati e interrogabili nella totalit`a delle loro opere; in secondo luogo, bisognerebbe disporre di un software molto potente e rafﬁnato. (Portalupi, 1994, p. 583) 1 Today, a once visionary task is conceivable, giving way to studies such as the present, which poses the following research question: to which extent can historical text reuse detection (HTRD) software detect explicit and implicit text reuse in the writings of Thomas Aquinas? To this end, we test the performance of TRACER, a text reuse detection framework, for the creation of an Index fontium computatus (a computed index of text reuse). The Summa contra Gentiles (ScG) was chosen as a case study because the critical edition used for the Index Thomisticus, the 1961 Marietti Editio Leonina (Gauthier et al., 1882), is still in use today and because an ongoing treebanking effort of the text will, in future, provide us with the linguistic data needed to further reﬁne the experiments described here (Passarotti, 2011). 1. Our English translation reads: ‘It will be even harder to automatically compare all of Thomas against all of the texts of one or multiple authors to check for the presence of implicit sources. Such a task would only be possible under two conditions: ﬁrstly, the texts of the authors quoted by Thomas would have to be digitised and searchable in their entirety; secondly, one would need very powerful and sophisticated software’.

Conclusion
This article describes a computational text reuse study on Latin texts designed to evaluate the performance of TRACER, a language-agnostic IR text reuse detection engine. The results obtained were manually evaluated against a gold standard and are contributing to the creation of an Index fontium computatus to both assess TRACER’s efﬁcacy and to provide a test-bed against which analogous IR systems can be measured and thus compared to TRACER. Our study shows that despite the known limitations of existing linguistic resources for Latin, the diverse spectrum of paraphrastic reuse encountered and its own languageagnosticism, TRACER is equipped to detect a wide range of explicit text reuse in the ScG, be that short or long, verbatim or paraphrastic, and implicit reuse only if coupled with explicit. To increase the detection accuracy, we are implementing a black/white list to give users the power to control words or multi-word expressions to be ignored or retained in the detection; furthermore, we plan on re-running these analyses with the disambiguated linguistic annotation currently being added to the text of the ScG (Passarotti, 2015) to measure its impact on this particular IR task. The data used and generated in the current study is available from: https://github. com/CIRCSE/text-reuse-aquinas.