The Archaeology of the Mind Lab
Prof. Orly Goldwasser
The Archaeology of the Mind Lab studies how different cultures, past and present, organize knowledge about the world.
Ancient Egyptian
Sumerian
Ancient Chinese
Corpus-based
classifier networks

© Goldwasser/Harel/Nikolaev

Mindmapping of ancient cultures

New Project
Exploring the minds of Ancient Egypt and Ancient China —A comparative network analysis of the classifier systems of the scripts
ISF grant no.1704/22,
PI Prof. Orly Goldwasser,
co-investigator, Prof. Zev Handel.
Congratualtions
- Dr. Jorke Grotenhuis, is awardee of the Israel Academy of Sciences and Humanities & Council for Higher Education Excellence Fellowship Program for International Postdoctoral Researchers.
- Yanru Xu, is awardee of the Plaks Fellowship in Traditional China field, awarded by the Department of Asian Studies, HUJI, 2022.
A classifier network of Sumerian, based on the ePSD2 database.
Data collected by Bo Zhang in iClassifier.
Selz, Gebhard. 2021. “Appositive semantic classification in Sumerian Cuneiform and the implementation of iClassifier.” Ash-sharq: Bulletin of the Ancient Near East 6, 142–171.

A classifier network of lexical borrowings in New Kingdom texts
Created by Haleli Harel in iClassifier
To appear in:
Harel, Haleli, Orly Goldwasser and Dmitry Nikolaev. 2023. ‘Mapping the ancient Egyptian mind: Introducing iClassifier, a new platform for systematic analysis of classifiers in Egyptian and beyond.’ In Ancient Egypt and New Technology: The Present and Future of Computer Visualization, Virtual Reality and other Digital Humanities in Egyptology. Edited by J. A. Roberson, R. Lucarelli and S. Vinson. Leiden: Brill.
And in Harel, Haleli. Forthcoming. A Network of Lexical Borrowings in Egyptian Texts of the New Kingdom: Organizing Knowledge according to the Classifier System. Doctoral dissertation. The Hebrew University of Jerusalem.
Blue lines link classifiers and lemmas (=words) they occur with.
Red lines link classifiers that co-occur with a host lemma.
Click the image to zoom into a detail.

