Reconstruction of Cuneiform Literary Texts as Text Matching

Abstract

Ancient Mesopotamian literature is riddled with gaps, caused by the decay and fragmentation of its writing material, clay tablets. The discovery of overlaps between fragments allows reconstruction to advance, but it is a slow and unsystematic process. Since new pieces are found and digitized constantly, NLP techniques can help to identify fragments and match them with existing text collections to restore complete literary works. We compare a number of approaches and determine that a character-level n-gram-based similarity matching approach works well for this problem, leading to a large speed-up for researchers in Assyriology.

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