Modeling cuneiform paleography with PaleoCodage

Cuneiform languages and its texts took an interest not only by Near Eastern Studies scholars but also in the computational linguistics major. Cuneiform texts have been edited digitally, cuneiform text corpora have been linguistically classified, information retrieval approaches have been performed, and texts have been annotated in various ways. However, the shape and form of cuneiform signs and other extralinguistic attributes itself usually do not fall into categories of such annotations, despite them playing a possible role in leading to a better understanding of the texts. One major reason for this is the lack of a machine-readable description of cuneiform characters. Other languages like Chinese or Japanese include an encoding of their characters, e.g. in the form of a writing order of strokes and their positioning towards another so that such attributes can be extracted easily (Bishop 2003). These encodings may be used to create, e.g. SVG images for font descriptions and due to the prevailing existence of the given languages can be better formalized per epoch.

A first approach to formalize cuneiform character descriptions by means of cuneiform wedges was developed by Norbert Gottstein. He developed a system which could describe which and how many cuneiform wedges of certain types were included in a cuneiform character. The goal of his work was to create a search system for cuneiform characters which would in many cases give a unique result. He defined four types of cuneiform wedges: Horizontal, vertical, and two diagonal wedge types.

Gottstein System by (Gottstein, 2013). One cuneiform character is described by the number of its corresponding wedge types.

The Near Eastern Studies community took an interest in the Gottstein System, but the system did not find wide adoption in this community. Interestingly, the system has found more of adoption in the computational linguistics community in which some digital tools had been developed using the Gottstein System as a basis.

The tool CuneiPainter is a straightforward Android App which allows the drawing of cuneiform character shapes using a finger on your mobile phone, detects its Gottstein code and presents the user with a list of alternatives of cuneiform characters. The set of cuneiform characters which can be recognized by CuneiPainter was modelled after one particular fonts’ set of characters. Therefore CuneiPainter may only recognize one cuneiform character variant per Unicode code point. For this set of cuneiform characters CuneiPainter acts as a showcase, that to search cuneiform characters, the Gottstein system works without yielding too many ambiguities. 

CuneiPainter also acts as a proof of concept for creating input method engines for cuneiform characters (Homburg, 2015). Input method engines take representations of cuneiform characters either in the Latin alphabet by entering a transliteration or by a Gottstein code possibly recognized from a painted image. The input method engine converts such a representation to its Unicode representation which may be shown using a particular font. An input method engine may also be used to convert an English translation to a Unicode representation.

What the Gottstein system lacks, however, is the inclusion of relations between cuneiform wedges. With a Gottstein code, we may know that a cuneiform character includes 4 horizontal and 4 vertical wedges, but we do not know the relations of these wedges towards another. Are the 4 horizontal wedges above the 4 vertical wedges? Do they cross? If so, how do they cross? In addition, the scientific literature suggests that there are more types of wedges than stated in the Gottstein system, as can be seen in the following pictures. To accurately depict and encode cuneiform signs all wedge variants need to be taken into account.

The positioning of cuneiform characters taken from the literature (Ebeling et. al., 1980). Cuneiform wedges can be found with shown wedge angles which are more granular than Gottsteins suggested rotations of 0°,45° and 90°

To capture and formalize relations between cuneiform wedges, encoding with the following capabilities was developed in a practical study course at Mainz University Of Applied Sciences: The PaleoCodage encoding. Its goals are as follows:

  • Capturing the rotations of all wedges including available angles
  • Capturing relations between wedges
  • Capturing wedge sizes separated into wedge head and the wedge itself
  • A unique identifier for a wedge including its angle
Description of rotations of cuneiform wedges taken from the literature mapped on to PaleoCodage descriptions. Wedges with different angles get different but unique identifiers. Different operators change the angle of

The benefits of such an encoding can be seen in several areas:

  1. The encoding may be used in Machine Learning applications as a classification target to recognize wedge types.
  2. The encoding is a machine-readable way of capturing the shape of cuneiform characters, so that cuneiform characters may be differentiated and possibly classified by computers.
  3. The encoding may be used to capture cuneiform sign variants in a machine-readable way which are often seen on pictures of cuneiform tablets but are rarely systematically collected. Collecting cuneiform character signs systematically allows for more research in the given area.

To show differences in the description of PaleoCodage vs. Gottstein code descriptions the following table gives an idea about its capabilities:

Cuneiform signSign nameGottstein CodePaleoCode
PaleoCodage vs. Gottstein code examples for the same Gottstein sign code These cuneiform signs include the same cuneiform wedges but in different positions. The PaleoCode allows a distinction between the different forms..

Further information about PaleoCodage and the PaleoCodage JavaScript Testing tool can be found on Github and in an extended abstract which has been submitted to the Digital Humanities Conference 2019 (Homburg, 2019). We may discuss further details and applications of PaleoCodage in further articles here at the IDCS blog.

  1. Bishop, T. and Cook, R. (2003) ‘A Specification for CDL Character Description Language’, in Glyph and Typesetting Workshop.
  2. Ebeling, E. et al. (1980) ‘Reallexikon der Assyriologie und Vorderasiatischen Archäologie. Zweiter Band’.
  3. Gottstein, N. (2013) ‘Ein stringentes Identifikations- und Suchsystem für Keilschriftzeichen’, in Mitteilungen der deutschen Orientgesellschaft. Berlin.
  4. Homburg, T. et al. (2015) Learning Cuneiform The Modern Way. Graz, Austria: DHd, 2015. Available at:
  5. Paleo Codage – A machine-readable way to describe cuneiform characters paleographically. Homburg, T. In Utrecht, Netherlands, July 2019.
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