Github for the 2024 international course on Ancient Language Processing given by Eliese-Sophia Lincke and Shai Gordin
How do we turn an ancient text into data? How do we apply data science techniques to historical, cultural, and linguistic questions? What are the ramifications of such transformations when confronted with classical approaches to ancient texts? The Ancient Language Processing course will focus specifically on how to answer the above questions when working with ancient languages and scripts from the emergence of writing in Mesopotamia and Egypt, to the rest of the world up till 800 CE. This course will introduce students of ancient history, ancient Near Eastern languages, and computer science to the computational processing of ancient texts. They will engage with inscribed artefacts--from dataset pre-processing to computational analysis via text parsing, vector space models (VSMs), statistical approaches, and graph theory.
Ancient languages contain rich human historical and cultural wealth. So far there has been good advancement in applying language technologies to ancient languages such as Sumerian, Akkadian, Latin, Ancient Greek, and Ancient Chinese, especially in the construction of digital language resources and resources to facilitate automatic analysis. For example, the Universal Dependencies (UD) project has made treebanks available for a series of ancient languages. The objective of this course is to computationally engage with ancient datasets of inscribed artefacts, mostly texts, from data exploration to publication of computational analysis. We will analyze classical studies and consider emerging research questions in the field of ancient Near Eastern studies, in order to address them computationally using ancient language processing.
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