Clarifying Stratigraphic Terminology in Paleolithic Archaeology Using Natural Language Processing

Abstract

Abstract Archaeological context is a foundational concept, yet its definition remains ambiguous and inconsistent. Traditionally, lithostratigraphic frameworks rooted in geology have long dominated, but recent computational and spatial approaches increasingly redefine stratigraphic units. This shift raises a critical challenge: the lack of clear and consistent terminology for defining stratigraphic units. To explore this issue, we applied natural language processing (NLP) to a broad corpus of Paleolithic literature, focusing on the use of key terms such as “layer,” “level,” “occupation,” and “horizon.” Using SciBERT (Scientific BERT; BERT = Bidirectional Encoder Representations from Transformers) to generate contextual embeddings, we compared their semantic distributions with a control set of distinct terms (lithic, bone, flake, charcoal). The control set produced stable, separable clusters, whereas contextual terms showed extensive semantic overlap and instability, reflecting their interchangeable and inconsistent use. These results underscore that the problem is not only linguistic but theoretical: without clear terminological baselines, new methodological advances risk conflating analytical tools with interpretive outcomes. We argue that terminological precision is essential for comparability across sites and for cumulative research. NLP offers a replicable framework for auditing and clarifying terminology, contributing to greater rigor and interoperability in archaeological interpretation.