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Given the richness and diversity of artistic events and currents that have followed
one another over the centuries in Italy, Italian art lexicon has become the research object
in various fields (art history, literature, linguistics etc.) and for diverse professionals
(translators, tour guides, exhibition curators etc.) (Billero, 2017). At present, the
monolingual dictionaries and corpora of art lexicon are both done perfectly in Italian
and Chinese, but bilingual tools of the same quality are not available: in fact, there is
only one bilingual dictionary of terms classified by field - Glossario Cinese-Italiano
(Qiu, 2013), in which the part of art lexicon takes only 3 pages. What’s more, it only
provides Italian translations of some Chinese artistic terms.
This paper intends to bridge this gap by establishing a bilingual corpus which will
achieve parallel alignment at the sentence level. However, there are no direct
translations from Italian to Chinese in terms of Renaissance artistic texts, for example,
Alberti’s De Pictura, Vasari’s Lives, Serlio’s I Setti Libri dell’architettura are all
translated from English, so it seems difficult to conduct diachronic research. This also
explains why the data collected in this project is constituted by contemporary Italian
texts and their direct Chinese translation versions.
The building tool is Sketch Engine, a multi-functional software that allows users to
annotate the parts of speech, analyze the frequency of lemma, extract terms and
compare the translation. The methodology adopted in this study is mixed: it starts with
the corpus-driven analysis (Tognini, 2001) which involves a more objective extraction
of lexicon by resorting to statistically significant co-occurrence models in the text, then
integrates with a qualitative analysis. Because of the great differences between Chinese
and Italian language and culture, manual annotations will be a salient point of this
project.
Till now the ongoing parallel database has counted over 23,000 words. Table 1 shows
the type of texts collected (...)